Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) SOCIAL SUPPORT, SELF-EFFICACY, AND STUDENT’S MENTAL HEALTH IN ONLINE LEARNING DURING PANDEMIC Sriwiyanti Sultan Zainal Abidin University, Malaysia Wahyu Saefudin* Sultan Zainal Abidin University, Malaysia Adinda Shofia Universitas Pendidikan Muhammadiyah Sorong, Indonesia Mujib Politeknik Negeri Pontianak, Indonesia Keywords: mental health; online learning; self-efficacy; social support Correspondence: e-mail: si3863@putra.unisza.edu.my *si3864@putra.unisza.edu.my adindashofia@unimudasorong.ac.id mujib@polnep.ac.id Abstract The Covid-19 pandemic influenced education policy in Indonesia; the consequence of traditional learning switched to online learning. This transition affects students’ mental health at various universities in Indonesia. This study aimed to examine the mental health level of 82 students who took online learning course and explained the effect of social support and self-efficacy on students’ mental health. The present study utilized three measuring tools namely the Indonesian versions of Child and Adolescent Social Support Scale (CASSS), General Self-Efficacy Scale, and Mental Health Continuum (MHC-SF). Regression analysis was used to determine the effect of social support and self-efficacy on students’ mental health. The results obtained from this study were that the majority of respondents’ mental health, 81.7% were in the high category, 17.1% were in the moderate category, and 1.2% of respondents were in the low https://ejournal.uinsaid.ac.id/index.php/al-balagh 2 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E Abstrak Pandemi Covid-19 mempengaruhi kebijakan pendidikan di Indonesia, dampaknya pembelajaran tatap muka harus beralih menjadi pembelajaran daring. Peralihan ini berdampak pada kondisi kesehatan mental mahasiswa di berbagai universitas di Indonesia. Penelitian ini bertujuan untuk melihat level kesehatan mental pada 82 mahasiswa yang mengikuti pembelajaran secara daring dan menjelaskan pengaruh dukungan sosial dan efikasi diri terhadap kesehatan mental mahasiswa. Instrumen pengukuran yang digunakan dalam penelitian adalah Child and Adolescent Social Support Scale (CASSS), General Self-Efficacy Scale, and Mental Health Continuum (MHC- SF). Pengaruh dukungan sosial dan efikasi diri terhadap kesehatan mental mahasiswa, peneliti menggunakan analisis regresi ganda. Hasil yang diperoleh dari penelitian ini adalah mayoritas kesehatan mental responden, 81,7% berada pada kategori tinggi, 17,1 % berada pada kategori sedang, dan 1,2% berada pada kategori rendah. Selanjutnya, dukungan sosial dan efikasi diri juga berpengaruh sebesar 71,9% (R Square=0,719, p=0,000) terhadap kesehatan mental, dengan sumbangan efektif sebesar 41,9% oleh dukungan sosial dan 30% efikasi dari. Dengan demikian, dukungan sosial dan efikasi diri merupakan kunci penting yang mampu meningkatkan kesehatan mental mahasiswa dalam mengikuti pembelajaran online. Kata kunci: kesehatan mental; pembelajaran daring; efikasi diri; dukungan sosial category. Furthermore, social support and self-efficacy also affect 71.9% (R Square = 0.719, p = 0.000) of mental health, with an effective contribution of 41.9% by social support and 30% by self-efficacy. Thus, social support and self-efficacy are important keys to improving students’ mental health in online learning. 3Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) How to cite this (APA 7th Edition): Sriwiyanti, Saefudin, W., Shofia, A., & Mujib (2022). Social Support, Self-Efficacy, And Student’s Mental Health In Online Learning During Pandemic. Al-Balagh: Jurnal Dakwah Dan Komunikasi, 7(1), 1–30, https:// doi.org/10.22515/al-balagh.v7i1.4914 INTRODUCTION The pandemic impacts the whole level of public activities, forcing a shift from offline to online mode, including the educational system. However, most students refuse online learning due to technological and financial constraints (Baloran, 2020). The migration process of traditional education settings to online learning also becomes controversial due to the absence of appropriate planning, design, and development of online instructional programs because of the emergency (Adedoyin & Soykan, 2020). This condition leads to decreased student motivation, self-efficacy, and cognitive engagement (Patricia Aguilera-Hermida, 2020). Direct social interactions in school were also related to students’ quality of life (Cleofas, 2020). For example, involvement in school organizations in traditional settings has been known to decreased depression levels. Therefore, the transition to online learning affects student mental health. Recent literature reviews regarding the psychosocial impact of previous epidemics found that fears, anxieties, and depression were common psychological symptoms (Chew et al., 2020). A cross-sectional study involving 746,217 students in China found psychological problems among students during the lockdown (Ma et al., 2020). Students experienced acute stress (34.9%), anxiety (21.1%), and depressive symptoms (11.0%). In addition, 24.9% of college students experienced increased anxiety levels due to disturbance in student academic activities, social distancing, and parental economic prospects (Cao et al., 2020). 4 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E According to Westerhof and Keyes (2010), mental illness and mental health are not opposites but occur and overlap on separate continua. Levels of mental illness co-exist with levels of mental health, creating different states of subjective well-being. In our research, emotional well-being refers to the presence or absence of emotional difficulties on the mental illness continuum. Meanwhile, mental health refers to the continuum between flourishing and languishing, well-functioning, and experiencing subjective feelings of incompleteness, emptiness, or stagnation. Mental health includes the following three core components: emotional health (happiness and satisfaction), psychological well-being (purpose in life, self-realization), and social well-being (being of social value) (Westerhof & Keyes, 2010). Various factors may influence adolescents’ mental health. One critical factor is social support from family members, peers, and significant others. Social support effectively decreases depression and anxiety among adolescents during the outbreak of COVID-19 (Qi et al., 2020). Social support also plays a primary role in mediating trait gratitude and subjective well-being in Chinese adolescents. Adolescents with high trait gratitude can build positive relationships and gain high social support from family, peers, and significant others. It may increase their subjective well-being (Kong et al., 2021). Furthermore, a study by Cohen and Wills (1985) identified the correlation between social support and general well-being. Their findings discuss the structure and function of social support in an individual and whether social support plays a role as a buffering or primary process. They also emphasized that social support could directly affect well-being by enhancing the social network, and on additionally side social support plays a role as stress buffer. Similar to this study, Sarason et al. (1987) also described the implications of social support where the relationship is a provider of support, and the absence of this support drives anxiety. 5Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) Besides that, Sandler and Barrera (1984) explained that when people perceive that they are receiving a proper level of support, the adverse outcomes of stress are not manifested. Furthermore, support satisfaction showed a direct association with any psychological symptomatology. Social support in an educational context focuses on types of support and sources of support perceived by students (Nolten, 1994). This theory was also developed by Malecki and Elliot (1999), which primarily based on a work by Tardy (1985). It emphasized the operational definitions of social support, which primarily discuss the source of support for children and adolescents. Providing support to students in educational and psychological difficulties is a natural disclosure and consequently is a fragment of interventions designed to strengthen the functioning of children and adults. In addition, Malecki and Demaray (2002) stated that social support plays a role in decreased clinical and school maladjustment indicators that arise from family support, friends’ support (peers and close friends), and teachers’ support. Child and Adolescents Social Support Scale (CASSS) is a measurement that encompasses all of those facets. The CASSS contains a different aspect of social support (Malecki & Demaray, 2002). First, emotional support consists of various types such as trust, caring, empathy, acceptance, and intimate interaction (Tardy, 1985). Second, instrumental support consists of helping behaviors in various forms, such as giving money, helping act in a difficult situation, spending precious time together, and providing necessities (Wills & Shinar, 2000). Third, informational support is defined as providing knowledge or advice such as valuable insight as a problem solving, providing information, guidance, and advices. Fourth, appraisal support means providing evaluative feedback and rewards in many ways; e.g., giving verbal affirmation, praising, and delivering feedback regarding the progress (Birch, 1998). It also includes constructive critique or evaluation for maintaining self-evaluation. 6 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E In addition, self-efficacy is also a variable that can reduce the negative impact of anxiety and doubt in online learning (Saefudin et al., 2021a). High self-efficacy prepares an individual to face various online learning difficulties, such as anxiety, stress, and depression (Lemay et al., 2021; Tsuroya, 2020). Various studies related to self-efficacy during the pandemic also confirmed the important role of self-efficacy for students. Self-efficacy was found to be related to procrastination, academic flow, and academic performance (Khotimatussannah et al., 2021; Pantu, 2021; Rahmadina et al., 2020). Furthermore, self-efficacy is a variable that can predict an individual’s mental health. Self-efficacy refers to an individual’s belief in his ability to succeed in something (Bandura, 1977). It includes knowing what needs to be done and being emotionally capable of doing it. People’s belief in their abilities will affect how they respond to certain situations or conditions (Shofia, 2021). In general, self-efficacy is self-confidence or individual belief in their ability to do something, produce something, organize, achieve their goals, and implement actions to realize certain skills (Saefudin, 2020). Self-efficacy affects the mental health of medical students in learning during COVID-19 pandemic (Arima et al., 2020). Therefore, self-efficacy can predict psychological distress in medical students in Japan during the pandemic. In addition, self-efficacy is a strong variable in predicting mental health among people in Turkey (Yıldırım & Güler, 2020). Therefore, if a student has high self-efficacy, the student will also have good mental health. High self-efficacy will help students avoid the negative effects of online learning during the pandemic; including burnout, depression, anxiety, and somatic symptoms (Bolatov et al., 2021). Studies about social support and mental health have been conducted multiple times in many countries (Colarossi & Eccles, 2003; Daly et al., 2015; Laird & Kuhn, 2014; Qi et al., 2020). It also includes studies about 7Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) self-efficacy and mental health (Annisa et al., 2020; Bolatov et al., 2021; Deliviana et al., 2021; Jin et al., 2021; Walean et al., 2021). However, there is a lack of research in the educational context, specifically in pandemic situations, related to the emergency regulation of online learning that bring out various challenges (Adedoyin & Soykan, 2020; Patricia Aguilera- Hermida, 2020). Also, It is crucial to examine the influence of social support and self-efficacy on students’ mental health, which will significantly affect various aspects of the educational system. In addition, this study had two hypotheses. Firstly, the alternative hypotheses: 1. there was a significant effect of social support on students’ mental health in online learning during the pandemic; 2. there was a significant effect of self-efficacy toward students’ mental health in online learning during the pandemic. 3. there was a significant effect of social support and self-efficacy toward students’ mental health in online learning during the pandemic. The study also proposed three null hypotheses: 1. there was no significant effect of social support on students’ mental health in online learning during the pandemic; 2. there was no significant effect of self-efficacy on students’ mental health in online learning during the pandemic. 3. there was no significant effect of social support and self-efficacy toward students’ mental health in online learning during the pandemic. METHODS This study was a correlational research between three variables. First, the study examined the mental health level among university students during online learning. Second, it aimed to identify the effect of social support and self-efficacy on university students’ mental health during online learning. The entire survey consisted of 67 items and took about 15 minutes to complete. The sampling method used in this research is non-probability, namely convenience sampling. Further, the scale was 8 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E delivered using Google Form to distribute the form online to students. We also announced the survey using a flyer on social media to reach eligible participants. Respondents in this study were 82 college students. The data collection period was from December 1-15, 2021. The inclusion criteria include college students in Indonesia, students who at that time underwent online learning in university for at least a semester, and aged 18-25. The instruments used in this study were: the social support scale, the general self-efficacy scale, and the mental health scale. The scale used to measure social support was originally developed by Malecki and Demaray (2002), namely the Child and Adolescent Social Support Scale (CASSS) in Germany and the English language. However, a theses research from the University of Islam Indonesia by Suharti (2020) has modified the scale to Indonesian language and online learning context in senior high school participants. Therefore, this study modified the latest scale based on the research requirement and try-out result. Moreover, the researchers reduced the 48 items into 43 items to fit the participants’ backgrounds. As a result, Cronbach’s alpha score was 0.980, categorized as a high score. The scale used to measure self-efficacy, originally from the General Self-Efficacy Scale from Schwarzer and Jerusalem (1995), consisted of 10 items and was available in Indonesian language. The scale was constructed to assess perceived self-efficacy to predict coping ability to daily hassles and adaptation after experiencing stressful life events. The basis for using this scale is that in a sample of 23 countries, the obtained Cronbach’s alpha scores ranged from 0.76 to 0.90, with the majority being 0.80. The Mental Health Continuum (MHC-SF) assesses mental health as Keyes (2002) defined. This 14-item scale contains three items that assess emotional health, six items that measure Ryff ’s dimensions of psychological well-being (i.e., self-realization, positive relationships, autonomy, mastery, purpose in life, and personal growth), and five items 9Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) that measure Keyes’ dimensions of social well-being (i.e., being of value to society). On a 4-point scale, the MHC-SF measures the frequency of respondents’ experiences of each mental health dimension. This study used the MHC-SF Indonesian version scale by Alfikalia (2020) with a good internal consistency of 0.881 and item discrimination indices ranging between 0.3 – 0.807. High score indicates flourishing mental health, whereas a low score indicates languishing mental health (Keyes, 2002). In conducting the analysis, this study utilized SPSS version 25. Moreover, two statistical analysis techniques were implemented in this study. First, researchers used the normality, linearity, heteroscedasticity, and multicollinearity test to test the assumption. The normality test checked whether the research data comes from a population normally distributed as a requirement for the next analysis step. In this study, the normality test shown from the Kolmogorov Smirnov table was assessed by obtaining skewness and kurtosis values. The probability value is > 0.05 indicates that the data is normally distributed. However, if the probability value is < 0.05, the data is not normally distributed. Then, the skewness or kurtosis value is divided by the Standard Error value, not more than 1.95 (5%) or 2.58 (1%). Furthermore, the linearity test determines whether the dependent variable has a linear relationship (George & Mallery, 2020). If the value of Deviation of linearity Sig>0.05, then there is a significant linear relationship between the independent and dependent variables. Moreover, if the value of Deviation of linearity Sig<0.05, then there is no significant linear relationship between the independent and dependent variables. Moreover, the heteroscedasticity test is a test that assesses whether there is an inequality of variance from the residuals for all observations in the linear regression model. This test is one of the classical assumption tests performed on linear regression. In this study, the researcher focuses on looking at the dots that form a certain regular pattern (wavy, widened, 10 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E narrowed, or vice versa), then indicating that heteroscedasticity occurs. Patterns can also occur with the dots spreading above the Y-axis or below. If there is no clear pattern, homoscedasticity occurs and is declared to meet the classical assumption test. The second analysis used in this study was multiple regression analysis to test the hypothesis. Again, the R square showed the effect of the dependent variable on the independent variable. RESULTS AND DISCUSSION Research Results Descriptive data analysis aims to describe the tendency of respondents’ answers to the questions posed in the questionnaire, then used to obtain respondents’ answers regarding the condition of the variables. Based on the data processing results, the value of the frequency distribution is divided into three categories: low, medium, and high. Figure 1 explains that student’s mental health during online learning was mostly in the high category. Al-Balagh: Jurnal Dakwah dan Komunikasi Vol. 7, No. 1, January – June 2022, pp. xxxx, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN 2527-5704 (P) ISSN 2527-5682 (E) Social Support, Self-Efficacy, And Student's Mental Health In Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib In this study, the researcher focuses on looking at the dots that form a certain regular pattern (wavy, widened, narrowed, or vice versa), then indicating that heteroscedasticity occurs. Patterns can also occur with the dots spreading above the Y-axis or below. If there is no clear pattern, homoscedasticity occurs and is declared to meet the classical assumption test. The second analysis used in this study was multiple regression analysis to test the hypothesis. Again, the R square showed the effect of the dependent variable on the independent variable. RESULTS AND DISCUSSION Research Results Descriptive data analysis aims to describe the tendency of respondents' answers to the questions posed in the questionnaire, then used to obtain respondents' answers regarding the condition of the variables. Based on the data processing results, the value of the frequency distribution is divided into three categories: low, medium, and high. Figure 1 explains that student's mental health during online learning was mostly in the high category. Figure 1. Scatterplot Figure 1. Mental Health’s Respondents Chart. 11Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) Table 1. Frequency Distribution Frequency Percent Valid Percent Cumulative Percent Valid Low 1 1.2 1.2 1.2 Moderate 14 17.1 17.1 18.3 High 67 81.7 81.7 100.0 Total 82 100.0 100.0 Based on the Table 1, most respondents have mental health scores in the high category, with 67 respondents or around 81.7%. Meanwhile, there were 14 respondents in the moderate category or around 17.1%. Finally, respondents who scored in the low category amounted to 1 student or 1.2% from total respondents. The first stage in the classical assumption test is the normality test by looking at the normal probability plots. Data is normally distributed if the lines (dots) follow the diagonal line. Therefore, based on the normal probability plots in Figure 2, it can be concluded that the data in this study are normally distributed. Al-Balagh: Jurnal Dakwah dan Komunikasi Vol. 7, No. 1, January – June 2022, pp. xxxx, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN 2527-5704 (P) ISSN 2527-5682 (E) Social Support, Self-Efficacy, And Student's Mental Health In Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Table 1. Frequency Distribution Frequency Percent Valid Percent Cumulative Percent Valid Low 1 1.2 1.2 1.2 Moderate 14 17.1 17.1 18.3 High 67 81.7 81.7 100.0 Total 82 100.0 100.0 Based on the Table 1, most respondents have mental health scores in the high category, with 67 respondents or around 81.7%. Meanwhile, there were 14 respondents in the moderate category or around 17.1%. Finally, respondents who scored in the low category amounted to 1 student or 1.2% from total respondents. The first stage in the classical assumption test is the normality test by looking at the normal probability plots. Data is normally distributed if the lines (dots) follow the diagonal line. Therefore, based on the normal probability plots in Figure 2, it can be concluded that the data in this study are normally distributed. Figure 2. Normal Probability Plots The second stage in the classical assumption test is the heteroscedasticity test by observing the image scatterplot. Based on the observation in Figure 3, it can be seen that there are points that spread below and above the Y-axis and do not have a regular pattern. Thus, it can be concluded that there is no heteroscedasticity or homoscedasticity between the independent variables. Figure 2. Normal Probability Plots 12 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E The second stage in the classical assumption test is the heteroscedasticity test by observing the image scatterplot. Based on the observation in Figure 3, it can be seen that there are points that spread below and above the Y-axis and do not have a regular pattern. Thus, it can be concluded that there is no heteroscedasticity or homoscedasticity between the independent variables. Al-Balagh: Jurnal Dakwah dan Komunikasi Vol. 7, No. 1, January – June 2022, pp. xxxx, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN 2527-5704 (P) ISSN 2527-5682 (E) Social Support, Self-Efficacy, And Student's Mental Health In Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Figure 3. Scatterplot The third stage in the classical assumption test is the autocorrelation test by observing the results of the Durbin-Watson Test. Based on Table 2, it can be seen that the results of the Durbin-Watson Test are 2.174. This value is greater than the value of the table Durbin-Watson Test, which is 1.45. Therefore, there is no autocorrelation in the residuals in this research data. Table 2. Autocorrelation Test Result R R Square Adjusted R Square R Square Change F Change p Durbin-Watson .848a .719 .712 .719 101.175 .000 2.174 The fourth stage in the classical assumption test is the multicollinearity test by observing the VIF value (Table 3). The magnitude of the value tolerance (a) used is 10 percent, so the VIF is 10, the calculation results show that each independent variable has a VIF value of less than 10, so it can be concluded that there is no multicollinearity between independent variables. Table 3. Multicollinearity Test Result Figure 3. Scatteplot Of Heteroscedasticity. The third stage in the classical assumption test is the autocorrelation test by observing the results of the Durbin-Watson Test. Based on Table 2, it can be seen that the results of the Durbin-Watson Test are 2.174. This value is greater than the value of the table Durbin-Watson Test, which is 1.45. Therefore, there is no autocorrelation in the residuals in this research data. 13Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) Table 2. Autocorrelation Test Result R R Square Adjusted R Square R Square Change F Change p Durbin- Watson .848a .719 .712 .719 101.175 .000 2.174 The fourth stage in the classical assumption test is the multicollinearity test by observing the VIF value (Table 3). The magnitude of the value tolerance (a) used is 10 percent, so the VIF is 10, the calculation results show that each independent variable has a VIF value of less than 10, so it can be concluded that there is no multicollinearity between independent variables. Table 3. Multicollinearity Test Result Variable VIF Tolerance Value Description Social support 2.647 .378 No multicollinearity Self-efficacy 2.647 .378 No multicollinearity Researchers used a multiple linear regression test to determine the effect of social support and self-efficacy on students’ mental health during online learning. Based on the ANOVA table (Table 4), it is found that the social support and self-efficacy variables can predict mental health variables with the regression equation (F= 101.175, p<0.05) and the significance value obtained is 0.000 (p<0.05). This study’s coefficient of determination (R Square) was 0.719 or 71.9% (Table 5). Therefore, the two independent variables can predict the dependent variable by 71.9%. Therefore, social support and self-efficacy can predict students’ mental health during online learning with a prediction rate of 71.9%. 14 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E Table 4. Multiple Linear Regression Test Result Mental health Social support Self-efficacy Pearson Correlation Mental health 1.000 .815 .787 Social support .815 1.000 .789 Self-efficacy .787 .789 1.000 Sig. (1-tailed) Mental health . .000 .000 Social support .000 . .000 Self-efficacy .000 .000 . N Mental health 82 82 82 Social support 82 82 82 Self-efficacy 82 82 82 Table 5. Multiple Regression Analysis Dependent Variable Predictors Contribution F p R R2 Description Mental health Social support 0.419 101.175 0.000 (p<0.05) .848 .719 There is correlation Self-efficacy 0.300 The effective contribution of social support and self-efficacy variables to student’s mental health during online learning is obtained by using the following calculation formula: SE(X)% = β x x r xy x 100% Based on the results of statistical calculations, it is known that several coefficients are shown in Table 5. The calculation results of the effective contribution formula show that the effectiveness of social support provides an effective contribution of 0.419 or 41.9, and self- efficacy provides an effective contribution of 0.300 or 30%. 15Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) The Description Of Student’s Mental Health Based on the research results, most respondents have a high mental health condition. The number of respondents in the high category was 67, or about 81.7% of the total respondents in this study. Furthermore, 14 respondents were in the medium category and one in low. These results are in line with research conducted by Aziz et al. (2021) that the pandemic affects the mental condition of students in online learning. In a study to 123 respondents, 70% reported good mental health conditions, and 30% had poor conditions. In addition, students often experience mental health forms, including burnout, anxiety, depression, anxiety, and somatic symptoms (Annisa et al., 2020; Bolatov et al., 2021). Furthermore, these results are also in line with Hasanah et al.’s (2020) study conducted to measure the psychological state of 190 students. The study results explained that 96.32% of respondents had normal levels of depression, 87.89% had normal stress levels, and 41.5% experienced mild anxiety levels during online learning. Therefore, the score can mean that all students have good mental health. Furthermore, research from Walean et al. (2021) also confirmed that most students have a level of anxiety in the mild category. Good mental health will impact students’ success in following and completing the online learning process. In addition, students with good mental health can also face various situations in life and adapt well (Deliviana et al., 2021). Conversely, poor mental health may cause failure in following online learning. Other negative impacts of declined mental health are burnout, depression, and other anxiety symptoms (Bolatov et al., 2021). Academic burnout due to poor mental health during online learning also causes student to feel tired, become cynical, and experience a sense of incompetence in completing assigned tasks (Novianti, 2021). 16 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E The Effect Of Social Support On Student’s Mental Health According to the result of regression analysis, it can be concluded that social support strongly affects mental health in online learning during the pandemic. This finding has proven the finding to be aligned with some previous studies. A systematic review by Harandi et al. (2017) examined 64 similar studies and concluded that social support is related to mental health. For instance, perceived social support can inhibit the damaging physiological complications of diseases. While in university, students are likely to contact social networks and be more used to receiving social support when encountering stressful situations. Another study by Karaca et al. (2019) found that social support in students’ education is a protective factor for mental health. Students’ main social support sources were their families, peers, and spouses or partners. In a more detailed explanation, every source of social support has also been proven to have a direct link to mental health. For instance, family support as a form of social support, is one of the predictors that lower mental health service use, levels of depression, and the prevalence of suicide attempts (LeCloux et al., 2016). Family support also becomes an effort to prevent mental health problems. Family support program developed by counselor becomes a part of the treatment for adolescents diagnosed with mental health problems (Laird & Kuhn, 2014). Adolescents with warm family relationships believe that their family can be trusted and reliable. This condition leads to higher self-efficacy and motivation to achieve goals (Triana et al., 2019). It means positive mental health in adolescents is affected by family functions as strong support systems. Specifically, family influences emotional well-being, psychological well- being, and social well-being (Florensa et al., 2019). Family support is service-oriented and aims to improve family functioning and conduct supportive relationships. This service is mainly 17Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) about care, psychological support to family members, and economic provision to establish well-being (Daly et al., 2015). Moreover, emotional or esteem support includes giving positive regard and encouragement, tangible or instrumental support such as direct assistance and offering help or money, and informational support such as giving advice or suggestions (Sarafino & Smith, 2011). However, lower emotional support reduces family cohesion and increases conflict (Pierce et al., 1996). Therefore, students living independently at home or dormitory, far away from their families have lower social support and are more vulnerable to those who live with a family (Tahmasbipour & Taheri, 2012). In addition, friends or peer support also plays a role in mental health particularly in relation to self-esteem and the prevalence of depression. Perceived support may affect mental health outcomes by increasing beliefs that are negatively associated with depression and low self-esteem, such as acceptance, self-worth, the belief that significant others will help, and connectedness to others (or lack of loneliness) (Colarossi & Eccles, 2003). Another study found that general friendships and support predict students’ social integration at university. Then, social integration predicts students’ mental health and well-being (Rubin & Kelly, 2015). The next corroborating study (Rubin et al., 2016) also stated that social contact with university friends negatively correlated with depression and positively predicts well-being. Social contact with university friends acts as a significant mediator toward satisfaction with life (Rubin et al., 2016). Additionally, teacher is one of the sources of support in students’ mental health. A better teacher-student relationship is linked to lower student mental health issues. Reversely, the absence of teachers’ support is associated with higher psychological distress (Harding et al., 2018). Teachers also have a role in delivering school mental health interventions as they offer the most effective mental health services to students in school settings (Franklin et al., 2012). Therefore, teachers should implement their 18 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E support in many ways, such as discussions of real cases related to practical guidance on how to help students dealing with difficulties, focused on supporting rather than solving a student’s problem, and engaging and being active in educational processes (Shelemy et al., 2019). We can conclude that in university students, social support can positively affect mental, physical, and social health; it has protective and fundamental effects (Tahmasbipour & Taheri, 2012). Furthermore, perceived social support predicted greater mental health levels in college students, including fewer depressive and anxiety symptoms, lower stress level, and higher satisfaction with life (Shelton et al., 2017). In this study context, a similar insight also arises from the finding; students’ mental health remained high in online learning processes during pandemics and was affected by social support from family, friends, and teachers. Therefore, during difficult times, students need different types of support: emotional support, informational support, instrumental support, and appraisal support. This study also confirmed the previous research conducted by Arima et al. (2020) on students in Japan, explaining that self-efficacy affects students’ mental health during the COVID-19 pandemic. If schools expect students’ mental health to be good, intervention programs are needed to improve their self-efficacy. Furthermore, Yıldırım and Güler’s (2020) study in Turkey supported the findings, that self-efficacy can be used as a preventive measure in preventing mental health. This finding might be explained by high self-efficacy in individuals that helps them deal with stressful conditions experienced during a pandemic, through effective coping strategies (Yunita et al., 2021). Students also experience some negative mental health conditions during the pandemic, including burnout syndrome, depression, anxiety, somatic symptoms, and declined academic performance (Bolatov et al., 2021; Saefudin et al., 2021b). 19Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) High self-efficacy can also reduce student academic stress, so students will handle pressure, demands, competition, and expectations from the environment better (Wistarini & Marheni, 2018). Other studies have demonstrated that high self-efficacy also affects students’ academic procrastination. Students with high self-efficacy will not delay the completion of a given task in ongoing online learning (Rahmadina et al., 2020). Self-efficacy plays an important role in determining attitudes and the amount of effort that students put toward their study, so they can think and react to complete tasks. Concerning online learning activities, self- efficacy also affects strategic self-regulated learning (Lee et al., 2020). Self- regulated learning is one of the important factors influencing academic success in face-to-face learning. Furthermore, Alemany-Arrebola et al. (2020) also confirmed that the COVID-19 pandemic affected student anxiety (state anxiety and trait anxiety). Students with high trait anxiety also showed an increased state anxiety during COVID-19 pandemic. Therefore, it is inseparable from the COVID-19 pandemic, which impacts the stressful situation (Sriwiyanti et al., 2021). Students’ self-efficacy can reduce the anxiety experienced in learning during COVID-19 pandemic. The higher the anxiety rate, the lower the self-efficacy (Alemany-Arrebola et al., 2020). Poor individual self-efficacy may also lead to emotional, physical, and mental exhaustion due to excessive and prolonged stress, a condition known as burnout (Ulfa & Aprianti, 2021). Burnout made individuals feel emotionally exhausted; causing them unable to carry out daily responsibilities. As stressful conditions continue, burnout people can lose interest and motivation. Self-efficacy affects motivation to solve the problems at hand; therefore, high self-efficacy reduces burnout in students (Pellerone, 2021; Ulfa & Aprianti, 2021). A study by Chen et al. (2020) to young Chinese nurses revealed self-efficacy can also be a mediator of job stress and mental health 20 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E problems, including depression and anxiety . Self-efficacy is also able to mediate adverse childhood experiences and mental health. Thus, the effects of adverse childhood experiences such as social, emotional, and health problems can be reduced (Treat et al., 2020). Among children who experienced bullying, self-efficacy can also be a mediator in reducing the prevalence of poor mental health state (Lin et al., 2020). The various studies above confirm that students’ confidence in their ability to master situations and produce positive affects their mental health. In conclusion, this study has proved that social support and self- efficacy can affect the students’ mental health in online learning during a pandemic. The effect of independent variables that conclude social support and self-efficacy can predict students’ mental health during online learning with a predictive rate of 71.9%. There are other variables outside these two independent variables that influence students’ mental health. Moreover, this study does not discuss the demographic factors of the respondent that may contribute to dependent factor. This study also had a small sample size (82 students). CONCLUSION AND SUGGESTION Conclusion This study explained online learning students’ mental health levels during the COVID-19 pandemic. From the results of the data analysis conducted, the majority of respondents have mental health scores in the high category. This study also explained the simultaneous contribution of social support and self-efficacy toward students’ mental health with a coefficient of determination of 0.719. Social support has a bigger contribution towards mental health. The greater the social support students receive and the higher their level of self-efficacy, the moreincrease of mental health conditions they will gain while participating in online learning. 21Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) Suggestion Future researchers can advance this research topic by perfecting the limitations of this study. There is space for further researchers to study other variables in improving students’ mental health. Future studies can analyze other related topics, especially related to the challenges and complex adaptation in pandemic situations. Furthermore, it can be organized by involving more participants from various regions or varying levels of education. Future studies may also involve the demographic factors of the respondents to make the study more holistic. Therefore, the broader research scope will help future researchers to achieve robust results. REFERENCES Adedoyin, O. B., & Soykan, E. (2020). Covid-19 Pandemic And Online Learning: The Challenges And Opportunities. Interactive Learning Environments, 1–14. https://doi.org/10.1080/10494820.2020.181 3180 Alemany-Arrebola, I., Rojas-Ruiz, G., Granda-Vera, J., & Mingorance- Estrada, Á. C. (2020). Influence Of COVID-19 On The Perception Of Academic Self-Efficacy, State Anxiety, And Trait Anxiety In College Students. Frontiers In Psychology, 11(October), 1–7. https:// doi.org/10.3389/fpsyg.2020.570017 Annisa, N., Efendi, R., & Chairani, L. (2020). Hubungan Sistem Pembelajaran Daring Dengan Kesehatan Mental Mahasiswa Di Era Covid-19 Menggunakan Chi-Square Test Dan Dependency Degree. Seminar Nasional Teknologi Informasi Komunikasi Dan Industri (SNTKI), 600–607. Arima, M., Takamiya, Y., Furuta, A., Siriratsivawong, K., Tsuchiya, S., & Izumi, M. (2020). Factors Associated With The Mental Health Status Of Medical Students During The Covid-19 Pandemic: A Cross-Sectional Study In Japan. BMJ Open, 10(12), 1–7. https:// doi.org/10.1136/bmjopen-2020-043728 22 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E Aziz, Z. A., Ayu, D. A., Bancin, F. M., Syara, S. G., Manalu, W. B., Artika S, R., Lia, S. F., Tanjung, L. P., Manalu, A. S. B., Br Karo, S. I. K., Br Bangun, C. A., Limbong, F. W., & Siregar, N. F. (2021). Gambaran Kesehatan Mental Mahasiswa Di Masa Pandemi Covid-19. Jurnal Dunia Kesmas, 10(1), 130–135. https://doi.org/10.33024/jdk. v10i1.3256 Baloran, E. T. (2020). Knowledge, Attitudes, Anxiety, And Coping Strategies Of Students During Covid-19 Pandemic. Journal Of Loss And Trauma, 25(8), 635–642. https://doi.org/10.1080/15325024. 2020.1769300 Bandura, A. (1977). Self-Efficacy: Toward A Unifying Theory Of Behavioral Change. Psychological Review, 84(2), 191–215. https://doi. org/https://psycnet.apa.org/doi/10.1037/0033-295X.84.2.191 Birch, D. (1998). Identifying Source Of Social Support. The Journal Of School Health, 68(4), 159-161. Bolatov, A. K., Seisembekov, T. Z., Askarova, A. Z., Baikanova, R. K., Smailova, D. S., & Fabbro, E. (2021). Online-Learning Due To Covid-19 Improved Mental Health Among Medical Students. Medical Science Educator, 31(1), 183–192. https://doi.org/10.1007/ s40670-020-01165-y Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The Psychological Impact Of The Covid-19 Epidemic On College Students In China. Psychiatry Research, 287(March), 112934. https://doi.org/10.1016/j.psychres.2020.112934 Chen, J., Li, J., Cao, B., Wang, F., Luo, L., & Xu, J. (2020). Mediating Effects Of Self-Efficacy, Coping, Burnout, And Social Support Between Job Stress And Mental Health Among Young Chinese Nurses. Journal Of Advanced Nursing, 76(1), 163–173. https://doi. org/10.1111/jan.14208 Chew, Q. H., Wei, K. C., Vasoo, S., & Sim, K. (2020). Psychological And Coping Responses Of Health Care Workers Toward Emerging Infectious Disease Outbreaks: A Rapid Review And Practical Implications For The Covid-19 Pandemic. The Journal Of Clinical Psychiatry, 81(6), 350–356. https://doi.org/10.4088/JCP.20r13450 Cleofas, J. V. (2020). Student Involvement, Mental Health And Quality Of Life Of College Students In A Selected University In Manila, 23Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) Philippines. International Journal Of Adolescence And Youth, 25(1), 435–447. https://doi.org/10.1080/02673843.2019.1670683 Cohen, S., & Wills, T. A. (1985). Stress, Social Support, And The Buffering Hypothesis. Psychological Bulletin, 98(2), 310–357. https://doi. org/10.1037/0033-2909.98.2.310 Colarossi, L. G., & Eccles, J. S. (2003). Differential Effects Of Support Providers On Adolescents’ Mental Health. Social Work Research, 27(1), 19–30. https://doi.org/10.1093/swr/27.1.19 Daly, M., Bray, R., Bruckauf, Z., Byrne, J., Margaria, A., Pecnik, N., & Samms-Vaughan, M. (2015). Family And Parenting Support. Policy And Provision In A Global Context. Innocenti Insight, 106. Italia: United Nations Children’s Fund Deliviana, E., Maria Helena Erni, Putri Melina Hilery, & Novi Melly Naomi. (2021). Pengelolaan Kesehatan Mental Mahasiswa Bagi Optimalisasi Pembelajaran Online Di Masa Pandemi Covid-19. Jurnal Selaras: Kajian Bimbingan Dan Konseling Serta Psikologi Pendidikan, 3(2), 129–138. Florensa, M. V. A., Keliat, B. A., Wardani, I. Y., & Sulistiowati, N. M. D. (2019). Promoting The Mental Health Of Adolescents Through Cognitive Behavior Group Therapy And Family Psychoeducation. Comprehensive Child And Adolescent Nursing, 42(Sup1), 267–276. https://doi.org/10.1080/24694193.2019.1594459 Franklin, C. G. S., Kim, J. S., Ryan, T. N., Kelly, M. S., & Montgomery, K. L. (2012). Teacher Involvement In School Mental Health Interventions: A Systematic Review. Children And Youth Services Review, 34(5), 973–982. https://doi.org/10.1016/j. childyouth.2012.01.027 George, D., & Mallery, P. (2020). IBM SPSS Statistics 26 Step By Step (A Simple Guide And Reference) (16th Ed.). Milton Park, Abingdon-on- Thames, Oxfordshire United Kingdom: Taylor & Francis. https:// doi.org/10.4324/9780429056765 Harandi, T. F., Taghinasab, M. M., & Nayeri, T. D. (2017). The Correlation Of Social Supprt With Mental Health: A Meta- Analysis. Electornic Physician, 9(9), 5212–5222. https://doi.org/doi. org/10.19082/5212 24 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E Harding, S., Morris, R., Gunnell, D., Ford, T., Hollingworth, W., Tilling, K., & Evans, R. (2018). Is Teachers’ Mental Health And Wellbeing Associated With Students’ Mental Health And Wellbeing? Journal Of Affective Disorders, 242, 180-187. https://doi.org/10.1016/j. jad.2018.08.080 Hasanah, U., Ludiana, Immawati, & PH, L. (2020). Gambaran Psikologis Mahasiswa Dalam Proses Pembelajaran Selama Pandemi Covid-19. Jurnal Keperawatan Jiwa, 8(3), 299–306. https://doi.org/10.26714/ jkj.8.3.2020.299-306 Jin, Y. Q., Lin, C. L., Zhao, Q., Yu, S. W., & Su, Y. S. (2021). A Study On Traditional Teaching Method Transferring To E-Learning Under The Covid-19 Pandemic: From Chinese Students’ Perspectives. Frontiers In Psychology, 12(March), 1–14. https://doi.org/10.3389/ fpsyg.2021.632787 Karaca, A., Yildirim, N., Cangur, S., Acikgoz, F., & Akkus, D. (2019). Relationship Between Mental Health Of Nursing Students And Coping, Self-Esteem And Social Support. Nurse Education Today, 76(December 2018), 44–50. https://doi.org/10.1016/j. nedt.2019.01.029 Khotimatussannah, N., Khairunisya, N., Pitaliki, T., & Anggraeni, A. (2021). Pengaruh Efikasi Diri Terhadap Penyesuaian Akademik Di Masa Pembelajaran Online Pada Mahasiswa Universitas Muhammadiyah Bandung. Jurnal Sosial Dan Humaniora, 3(1), 29–36. Kong, F., Yang, K., Yan, W., & Li, X. (2021). How Does Trait Gratitude Relate To Subjective Well-Being In Chinese Adolescents? The Mediating Role Of Resilience And Social Support. Journal Of Happiness Studies, 22(4), 1611–1622. https://doi.org/10.1007/ s10902-020-00286-w Laird, R., & Kuhn, E. (2014). Family Support Programs And Adolescent Mental Health: Review Of Evidence. Adolescent Health, Medicine And Therapeutics, 5, 127–142. https://doi.org/10.2147/ahmt. s48057 LeCloux, M., Maramaldi, P., Thomas, K., & Wharff, E. (2016). Family Support And Mental Health Service Use Among Suicidal Adolescents. Journal Of Child And Family Studies, 25(8), 2597–2606. https://doi.org/10.1007/s10826-016-0417-6 25Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) Lee, D., Watson, S. L., & Watson, W. R. (2020). The Relationships Between Self-Efficacy, Task Value, And Self-Regulated Learning Strategies In Massive Open Online Courses. International Review Of Research In Open And Distance Learning, 21(1), 1–22. https://doi.org/10.19173/ irrodl.v20i5.4564 Lemay, D. J., Bazelais, P., & Doleck, T. (2021). Transition To Online Learning During The COVID-19 Pandemic. Computers In Human Behavior Reports, 4, 1–9. https://doi.org/10.1016/j.chbr.2021.100130 Lin, M., Wolke, D., Schneider, S., & Margraf, J. (2020). Bullying History And Mental Health In University Students: The Mediator Roles Of Social Support, Personal Resilience, And Self-Efficacy. Frontiers In Psychiatry, 10(January), 1–9. https://doi.org/10.3389/ fpsyt.2019.00960 Ma, Z., Zhao, J., Li, Y., Chen, D., Wang, T., Zhang, Z., Chen, Z., Yu, Q., Jiang, J., Fan, F., & Liu, X. (2020). Mental Health Problems And Correlates Among 746 217 College Students During The Coronavirus Disease 2019 Outbreak In China. Epidemiology And Psychiatric Sciences, 29(e-181), 1-10. https://doi.org/10.1017/ S2045796020000931 Malecki, C. K., & Demaray, M. K. (2002). Measuring Perceived Social Support: Development Of The Child And Adolescent Social Support Scale (CASSS). Psychology In The Schools, 39(1), 1–18. https://doi.org/10.1002/pits.10004 Malecki, C. K., & Elliot, S. N. (1999). Adolescents Rating Of Perceived Social Support And Its Importance: Validation Of The Students Social Support Scale. Psychology In The Schools, 36(6), 475–483. https:// doi.org/10.1002/(SICI)1520-6807(199911)36:6<473::AID- PITS3>3.0.CO;2-0 Nolten, P. W. (1994). Conceptualization And Measurement Of Social Support: The Development Of The Student Social Support Scale. Madison, WI, United States: University of Wisconsin-Madison. Novianti, R. (2021). Academic Burnout Pada Proses Pembelajaran Daring. Jurnal Kesehatan Perintis, 8(2), 128–133. https://doi.org/10.33653/ jkp.v8i2.656 Pantu, E. A. (2021). Online Learning: The Role Of Academic Self- Efficiency In Creating Academic Flow. Psychological Research And 26 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E Intervention, 4(1), 1–8. https://doi.org/10.21831/pri.v4i1.40381 Patricia Aguilera-Hermida, A. (2020). College Students’ Use And Acceptance Of Emergency Online Learning Due To Covid-19. International Journal Of Educational Research Open, 1(July), 100011. https://doi.org/10.1016/j.ijedro.2020.100011 Pellerone, M. (2021). Self-Perceived Instructional Competence, Self- Efficacy And Burnout During The Covid-19 Pandemic: A Study Of A Group Of Italian School Teachers. European Journal Of Investigation In Health, Psychology And Education, 11(2), 496–512. https://doi.org/10.3390/ ejihpe11020035 Pierce, G. R., Sarason, B. R., & Sarason, I. G. (1996). Handbook Of Social Support And The Family. Berlin, Germany: Springer Science+Business Media. Qi, et al. (2020). The Effect Of Social Support On Mental Health In Chinese Adolescents During The Outbreak Of Covid-19. Journal Of Adolescent Health, 67(4), 514–518. https://doi.org/10.1016/j. jadohealth.2020.07.001 Rahmadina, N. A., Sulistiyana, & Arsyad, M. (2020). Kontribusi Dukungan Sosial Dan Efikasi Diri Terhadap Prokrastinasi Akademik Pada Siswa Kelas VII Di SMP Negeri 27 Banjarmasin. Jurnal Bimbingan Dan Konseling Ar-Rahman, 6(2), 83–87. http://dx.doi. org/10.31602/jbkr.v6i2.3510 Rubin, M., Evans, O., & Wilkinson, R. B. (2016). A Longitudinal Study Of The Relations Among University Students’ Subjective Social Status, Social Contact With University Friends, And Mental Health And Well-Being. Journal Of Social And Clinical Psychology, 35(9), 722–737. https://doi.org/10.1521/jscp.2016.35.9.722 Rubin, M., & Kelly, B. M. (2015). A Cross-Sectional Investigation Of Parenting Style And Friendship As Mediators Of The Relation Between Social Class And Mental Health In A University Community. International Journal For Equity In Health, 14(87), 1–11. https://doi.org/10.1186/s12939-015-0227-2 Saefudin, W. (2020). Psikologi Pemasyarakatan. Jakarta: Kencana Prenada Media. Saefudin, W., Sriwiyanti, S., & Yusoff, S. (2021a). Role Of Social Support Toward Student Academic Self-Efficacy In Online Learning 27Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) During Pandemic. Jurnal Tatsqif, 19(2), 133–154. https://doi. org/10.20414/jtq.v19i2.4221 Saefudin, W., Sriwiyanti, S., & Yusoff, S. (2021b). Spiritual Well-Being Sebagai Prediktor Performa Akademik Siswa Di Masa Pandemi. Kariman, 09(02), 247–262. Sandler, I. N., & Barrera, M. (1984). Toward A Multimethod Approach To Assessing The Effects Of Social Support. American Journal Of Community Psychology, 12(1), 37–52. https://doi.org/10.1007/ BF00896927 Sarafino, E. P., & Smith, T. W. (2011). Health Psychology: Biopsychosocial Interactions (7th Ed.). Hoboken, New Jersey, United States: John Wiley & Sons, Inc. Sarason, I. G., Sarason, B. R., Shearin, E. N., & Pierce, G. R. (1987). A Brief Measure Of Social Support: Practical And Theoretical Implications. Journal Of Social And Personal Relationships, 4(4), 497– 510. https://doi.org/10.1177/0265407587044007 Schwarzer, R., & Jerusalem, M. (1995). Generalized Self-Efficacy Scale. In J. Weinman, S. Wright, & M. Johnston (Eds.), Measures In Health Psychology: A User’s Portfolio. Causal And Control Beliefs. NFER- Nelson. Shelemy, L., Harvey, K., & Waite, P. (2019). Supporting Students’ Mental Health In Schools: What Do Teachers Want And Need? Emotional And Behavioural Difficulties, 24(1), 100–116. https://doi.org/10.108 0/13632752.2019.1582742 Shelton, A. J., Wang, C. D. C., & Zhu, W. (2017). Research Perceived Social Support And Mental Health: Cultural Orientations As Moderators. Journal Of College Counseling, 20(October), 194–207. https://doi. org/10.1002/jocc.12062 Shofia, A. (2021). Validasi Modul Pelatihan Komunikasi Interpersonal Untuk Meningkatkan Efikasi Diri Orang Tua Dalam Berkomunikasi Dengan Remaja Di Lingkungan Berisiko. Thesis Master (Unpublished). Yogyakarta: Gadjah Mada University. Sriwiyanti, S., Saefudin, W., & Yusoff, S. (2021). Social Support And Academic Resilience In Online Learning During Pandemic. Al-Tazkiah: Jurnal Bimbingan Dan Konseling Islam, 10(2), 95–114. https://doi.org/10.1201/9781315274508-20 28 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E Suharti, V. (2020). Dukungan Sosial Dan Resiliensi Akademik Dengan Efikasi Diri Akademik Sebagai Mediator Pada Siswa SMK Yang Mengikuti Pembelajaran Jarak Jauh/ Daring. Thesis Master (Unpublished). Yogyakarta: Universitas Islam Indonesia. Tahmasbipour, N., & Taheri, A. (2012). A Survey On The Relation Between Social Support And Mental Health In Students Shahid Rajaee University. Procedia Social And Behavioural Sciences, 47, 5–9. https://doi.org/10.1016/j.sbspro.2012.06.603 Tardy, C. H. (1985). Social Support Measurement. American Journal Of Community Psychology, 13(2), 187–202. https://doi.org/10.1007/ BF00905728 Treat, A. E., Sheffield-Morris, A., Williamson, A. C., & Hays-Grudo, J. (2020). Adverse Childhood Experiences And Young Children’s Social And Emotional Development: The Role Of Maternal Depression, Self-Efficacy, And Social Support. Early Child Development And Care, 190(15), 2422–2436. https://doi.org/10.10 80/03004430.2019.1578220 Triana, R., Keliat, B. A., Wardani, I. Y., Sulistiowati, N. M. D., & Veronika, M. A. (2019). Understanding The Protective Factors (Self-Esteem, Family Relationships, Social Support) And Adolescents’ Mental Health In Jakarta. Enfermeria Clinica, 29(Supplement 2), 629–633. https://doi.org/10.1016/j.enfcli.2019.04.096 Tsuroya, F. I. (2020). Dampak Pembelajaran Online Di Tengah Pandemi Covid-19 Terhadap Proses Pembelajaran Metode Yanbu’a Di Kelas 2 MI At-Taqwa Bondowoso. IQ (Ilmu Al-Qur’an): Jurnal Pendidikan Islam, 3(2), 199–214. https://doi.org/10.37542/iq.v3i02.124 Ulfa, S., & Aprianti, M. (2021). Pengaruh Efikasi Diri Terhadap Burnout Dan Perbedaannya Berdasarkan Gender. Psychosophia: Journal Of Psychology, Religion, And Humanity, 3(1), 24–35. https://doi. org/10.32923/psc.v3i1.1651 Walean, C. J. S., Pali, C., & Sinolungan, J. S. V. (2021). Gambaran Tingkat Kecemasan Pada Mahasiswa Di Masa Pandemi. Jurnal Biomedik (JBM), 13(2), 132–143. https://doi.org/10.35790/ jbm.13.2.2021.31765 Westerhof, G. J., & Keyes, C. L. M. (2010). Mental Illness And Mental Health: The Two Continua Model Across The Lifespan. Journal 29Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E) Of Adult Development, 17(2), 110–119. https://doi.org/10.1007/ s10804-009-9082-y Wills, T. A., & Shinar, O. (2000). Measuring Perceived And Recieved Social Support. In S. Cohen, L. G. Underwood, & B. H. Gottlieb, (Eds.) Social Support Measurement And Intervention (pp. 86–90). Oxford, United Kingdom: Oxford University Press. https://doi. org/10.1093/med:psych/9780195126709.001.0001 Wistarini, N. N. I., & Marheni, A. (2018). Peran Dukungan Sosial Keluarga Dan Efikasi Diri Terhadap Stres Akademik Mahasiswa Baru Fakultas Kedokteran Universitas Udayana Angkatan 2018. Jurnal Psikologi Udayana, 164–173. Yıldırım, M., & Güler, A. (2020). Covid-19 Severity, Self-Efficacy, Knowledge, Preventive Behaviors, And Mental Health In Turkey. Death Studies, 46(4), 979-986. https://doi.org/10.1080/07481187. 2020.1793434 Yunita, R., Isnawati, Ii. A., & Wahyunisari, S. (2021). Efikasi Diri Dengan Koping Mahasiswa Sarjana Keperawatan Menghadapi Pandemi Covid 19. Jurnal Keperawatan, 13(1), 213–226. https://doi. org/10.32583/keperawatan.v13i2.1352 30 Social Support, Self-Efficacy, and Student’s Mental Health in Online Learning During Pandemic Sriwiyanti, Wahyu Saefudin, Adinda Shofia, Mujib Al-Balagh: Jurnal Dakwah dan Komunikasi, Vol. 7, No. 1, January – June 2022, pp. 1 - 30, DOI: https://doi.org/10.22515/al-balagh.v7i1.4914 ISSN: 2527-5704 (P) ISSN: 2527-5682 (E