INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) 1 INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) Yasmin Fitriana Imanuddin1)* 1Departement of Economics, Faculty of Economics and Business, University of Indonesia, Indonesia Abstract Internet usage in Indonesia is growing rapidly each year. Information on the internet is considered to affect the way of thinking and the behaviour of its users. This can be seen, among other things, on the women internet user’s desired or ideal number of children. This research aims to study the patterns and differentials of the ideal number of children among women in Indonesia according to internet usage and the effect of the use of internet on women’s ideal number of children in Indonesia after controlling for the effects of socio-economic factors. This study used data from the results of 2017 Indonesia Demographic and Health Survey (DHS). The method used to analyze the data is multinomial logistic regression. The analysis is conducted on all childbearing-aged women (15-49 years old) and married childbearing-aged women. The results of the study show that childbearing-aged women who used the internet wanted less children compared to those who did not use the internet. The results of this study can be used as a reference by the related stakeholders to formulate policies that support fertility level management in Indonesia using information and communication technology, the internet in particular. Keywords: Childbearing-aged women; ideal number of children; Indonesia; internet; multinomial logistic regression 1. INTRODUCTION Birth is one of the main components of demographics. Birth rate in Indonesia is currently stagnant and tends to decline. This situation is concerning because it could change the structure of the population in Indonesia. Through the National Medium-Term Development Plan (RPJMN) 2020-2024, the government wants to improve the quality of life of Indonesian people by controlling the population so that the population grows in balance. Balanced population growth can be achieved with a fertility condition that is at the replacement level, which total fertility levels of about 2.1 children per woman. This number then becomes the target that the government wants to achieve by 2024. Based on the results of the 2015 Inter-Censal Population Survey (SUPAS), Indonesia's total birth rate in 2015 stands at 2.28. Indonesia still needs to strive to achieve a population that grows with a balance due to the considerable difference between the current total birth rate and the desired total birth rate. According to the 2017 IDHS results, the percentage of women of childbearing age in Indonesia who want a relatively large number of children is still very high. Around 33.95% of women want 3-4 children and 15% of women want 5 or more children or non-numeric, while 51.06% of them want 0-2 *Coressponding author. Email address: fitriana.yasmin@gmail.com mailto:fitriana.yasmin@gmail.com AFEBI Economic and Finance Review (AEFR) Volume 6, No. 1 (2021) 2 children. The high percentage of women who want a relatively large number of children can create problems to reach 2.1 in the total birth rate by 2024. Having children is the result of fertility intentions that were previously formed through a person's fertility desire. Fertility desire is a very broad and varied aspect because it is very personal. The desire for fertility can generally occur due to problems of religious adherence, traditions, economic condition, and so on. Figure 1. Average Ideal Number of Children of Women of Childbearing Age in Indonesia Source: IDHS 1987, 1991, 1994, 1997, 2002, 2007, 2012, dan 2017 Fertility desire is generally measured by the average ideal number of children. The trend in the average ideal number of children according to the IDHS results continues to decline to 2.6 in 2017. This figure indicates the number of children that someone actually wants if they do not have children. Based on the data collected through the IDHS, the more children a person has, the more children are considered ideal. A decline in the total birth rate a few decades ago was necessary, but in the future, this could be a problem for Indonesia. The low state of the total birth rate is a condition that needs to be concerned about and needs to pay attention to, especially for policymakers. The low total birth rate can cause population aging in the future which in turn creates a decrease in productivity and can create new burdens, such as an increase in dependency burden. The increase in dependency burden means that the dependents of the productive age population will be greater in the presence of an aging population. This situation will also harm economic growth, create social problems, and other problems. If this trend continues, there are concerns that by 2045, Indonesia will have the same fate as developed countries, which is the increase of the elderly population and a reduction in the population of the productive labor force if the number of children owned by each household continues to decline. Therefore, it is necessary to think about how to extend the demographic bonus and keep the total birth rate stable at 2.1 because there is a tendency for Indonesian families to wanting fewer number of children. 3.2 3.1 2.9 2.9 2.9 2.8 2.6 2.6 0 0.5 1 1.5 2 2.5 3 3.5 1987 1991 1994 1997 2002 2007 2012 2017A v e ra g e I d e a l N u m b e r o f C h il d re n o f W o m e n o f C h il d b e a ri n g A g e Year INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) 3 The Indonesian Population Projection predicts that in 2015-2020 Indonesian women of childbearing age will give birth to 2.17 children and until 2045 will be stable in giving birth to 2.1 children. The prediction figure from the Indonesian Population Projection is the government's hope to maintain demographic conditions. Unlike the results of the Indonesian Population Projection, the 2019 World Population Prospect projects that by 2045, Indonesia will have a total birth rate of 1.95, which is below the ideal replacement level. For this reason, through the National Medium-Term Development Plan (RPJMN) 2020-2024, the government aims to keep the total birth rate stable at 2.1 or two children per woman. Total birth rate is an important indicator of population problems. The low birth rate in a country can be a threat to the country's resilience, especially the high dependency ratio caused by an aging population. Therefore, to prevent an aging population, it is necessary to analyze the aspects that have caused the decline in the total number of births in the world by looking at the fertility desires that exist in the community. The desire for fertility can be influenced by various information received by the community. In this era, people generally get this information through the internet. The development of technology, especially the internet, can change all aspects of life. The internet has a variety of information from all corners of the world without any restrictions. Various new perspectives can be obtained with the existence of the internet. It is estimated that the internet can affect fertility desires for the world's population. In this era, people's lives cannot be far from the internet. Based on data from Digital 2019 Reports conducted by Hootsuite and We Are Social, there are 4.39 billion internet users in 2019 worldwide and an estimated 11 new users per second. In Indonesia, the overall internet penetration rate according to the World Bank was 39.79% in 2018. Urban and rural areas certainly have different levels of penetration. Based on SUSENAS, internet penetration in Indonesia has a trend that continues to increase every year and there is a significant difference between internet penetration in the two regions. The way people think today is much different from the way people think a few years ago. This is due to the increasingly open access to the outside world, especially for urban communities that have a high level of internet penetration. With the massive development of the internet, researchers have begun to focus on looking at the impact of the internet on life. There are various responses and hypotheses regarding the internet, such as: the internet is a technology that can disrupt traditional family life (Conley, 2009); the internet is a growing medium and has the potential to find a partner (Rosenfeld and Thomas, 2012); and the internet is a technology that allows spill-over from work life to home life or vice versa (Wajcman, 2014). From the background description above, it shows that it is necessary to conduct a study on the fertility desire or the ideal number of children related to the effect of internet use in Indonesia. Research on fertility desires is important because the results of this study can be used to design appropriate policies to support the handling of birth rates. This research on the effect of internet use on the ideal number of children is limited to women in Indonesia aged 15-49 years. Based on the background of the problems related to threats that can arise from the decreasing total birth rate, the problem formulations in this study are how are the patterns and differences in the ideal number of children according to women in Indonesia AFEBI Economic and Finance Review (AEFR) Volume 6, No. 1 (2021) 4 according to internet usage and how does internet use affect the ideal number of children according to women in Indonesia after being controlled with certain socio-economic factors? Based on the problems that have been stated above, this study aims to examine the effect of the internet on the ideal number of children according to women in Indonesia. Meanwhile, the specific objectives of this study are studying the patterns and differences in the ideal number of children according to women in Indonesia according to internet usage and certain social and economic factors and studying the effect of internet use on the ideal number of children according to women in Indonesia after being controlled with the influence of certain social and economic factors. 2. LITERATURE STUDY 1) Determinants of Fertility A person's birth rate is often measured directly using the impact of socio- economic factors on fertility. There are several studies related to socio-economic factors on fertility, one of which is by Davis and Blake (1956). Research conducted by Davis and Blake describes 11 intermediate variables that affect fertility which is then grouped into three categories, namely the stage of sexual relations, the stage of conception, and the stage of pregnancy. Research on socio-economic factors on fertility was also carried out by Becker (1960), particularly on the number of children in a family. The theory carried out by Becker discusses the quality and quantity of children. Becker assumes that the quality and quantity of children have a positive effect on income elasticity at constant prices. However, as income increases with economic growth and development, it is assumed that the demand for quality of children becomes more elastic and increases more rapidly. This results in higher prices for childcare and thus reduces the demand for the number or quantity of children. Income is one of the factors that affect the number of children in the household. Based on the publication of Becker (1960), children have a negative correlation with income, but there is no relationship between children and income. Becker assumes that child ownership preferences are viewed from two sides, namely the quality and quantity of children. According to Becker, children are judged as inferior goods if they do not have good quality. Furthermore, according to Becker (1991), demand for children is the number of children wanted when there are no things that prevent the act of having or not having children. The choice of birth is conditioned by the social, educational, cultural, and economic conditions faced by each individual. This demand for children affects the relative price of the child and the full income of a household, where the relative price of the child is the direct cost of caring for the child (such as health and education costs) and the net cost of caring for the child (the contribution of the child to household income). When the relative price increases, the demand for children will effectively decrease. In addition, other costs related to the time spent caring for children are part of the relative costs. Time spent caring for children can have a significant impact on demand for children. INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) 5 2) Fertility Desire Fertility intention has an important role in fertility itself (Azmoude et al., 2017). The importance of intention in terms of fertility is because fertility is an action based on intention which is then integrated into life (Schoen et al., 1999). Fertility intentions are influenced by different factors for each individual and will lead to the actualization of the pregnancy or childbirth which is formed from the desire for fertility. Fertility desire and fertility intention are different things. Sometimes there is a misunderstanding between fertility desire and fertility intention. The desire for fertility can be in the form of a person's hopes for having children when all potential barriers are not taken into account (Miller, 2011), usually measured by the “ideal number of children”. There is a concept entitled Theory of Planned Behavior which can explain how fertility behavior works (Ajzen 1991, 2005). The main idea of this concept is that what motivates the fertility intention of a person and a partner starts from a sequential process that begins with traits that unconsciously motivate to have or not have children, then it develops into a conscious desire to have or not have children, which eventually develops into an act or act of behavior which is a tool in the act of having or not having children, which then becomes an event of birth (Miller, 2011). The desire for fertility is expected to be a signal for future fertility. The higher the certainty of a person's fertility desire, the greater the likelihood that the desired fertility will occur (Schoen et al., 1999). 3) Information and Communication Technology, Internet Usage, and Its Impact on Society Information and communication technology is a vital component of today's everyday life. Information and communication technology has many roles for human development, from the aspects of education, health, and improving living standards (Bankole and Mimbi, 2017; Yakunina and Bychkov, 2015; Lee et al. 2017). Sociologists have conducted research on one of the information communication technologies, which is the internet, and its effects on people's lives. Daniel Bell (1977) conducted a study on the social impact of digital communication media and predicted that there are major consequences of electronic developments that can accelerate the movement of information. Castells (1996) also argues that the ability of the internet to integrate various forms of information into one system can have an impact on people's lives, create new forms of identity, and build new forms of social organization. The internet can increase efficiency and make humans more productive and provide convenience by eliminating the need to travel to their destination to carry out activities. Because of the internet too, the literacy level of its users is reported to be higher than those who do not use the internet (DiMaggio et al., 2001). 4) Internet Use and Fertility The internet can affect transitions in marriage, especially in finding partners who will become parents of their children (Rosenfeld and Thomas, 2012). With the help of internet mediation, traditional partner formation can be replaced. Marriage, which is a determinant that has an impact on fertility, thus the impact of using the internet AFEBI Economic and Finance Review (AEFR) Volume 6, No. 1 (2021) 6 on fertility can be mediated through marriage (Billari et al., 2017). The internet can also facilitate the balancing of the division of time for work and family. With internet- based work, parents can reduce their time to travel to the office, reduce absenteeism and increase productivity, and of course, increase time spent with family (Dettling, 2017). 5) Internet and Information About Fertility Interest in having children has a strong association with knowledge about fertility. Based on recent research, knowledge about fertility in Japan is lower than in other developed countries. This could be one reason why Japan has a low birth rate (Maeda et al., 2015). Maeda researched the knowledge of men and women aged 18-59 and included people who were trying to give birth for at least six months on fertility using the Japanese version of the Cardiff Fertility Knowledge Scale (CFKS-J). There are 44% of the sample from the study who managed to answer the items from the CFKS- J correctly. Based on the results of multivariate linear regression analysis, 65% of the sample who knows things about fertility get knowledge about it from the mass media or the internet. Based on theoretical reviews and empirical studies, the analytical framework in conducting the analysis of the internet and the ideal number of children according to women in Indonesia is as follows. Figure 2. Analytical Framework 3. RESEARCH METHODOLOGY This study aims to analyze the use of the internet and the ideal number of children according to women of childbearing age in Indonesia. This study uses secondary data obtained through the results of 2017 Indonesian Demographic and Health Survey (IDHS). The unit of analysis for this study is women aged 15-49 years or can be categorized as women of childbearing age. This category includes never-married women who are part of women of childbearing age. The samples from IDHS that will be used in this study are individual women from women of childbearing age aged 15-49 years. Internet usage Read about family planning from the internet Ideal number of children • Age • Residential area • Highest education level • Marriage status • Number of living children • Occupation • Wealth quintiles • Husband's desire to have children INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) 7 This study will use economic research methods to build research models and process the data. The main method of this research is quantitative research and will be supported by qualitative methods to support the findings and provide a broader perspective. This study focuses on cross-sectional data at the national level. The variables used in this study are presented in table 1. Table 1. Research Variables, Symbols, Operational Definitions, and Categorization Variables Operational Definitions Categorization Descriptive Inferential Dependent Variable Ideal number of children Number of children wanted 1. 0-2 children 2. 3-4 children 3. ≥5 children and non-numeric response Independent Variable Internet usage (internet) The length of internet usage in the last month before census 1. Everyday 0. Never use the internet * 1. Use the internet 2. Everyweek 3. Less than once a week 4. Never 5. No answer Read about family planning from the internet (fpinternet) Have or never have read about family planning information via the internet 0. No* 1. Yes Control Variable Age (age) Age of respondent during census 1. 15-24 years old* 2. 25-34 years old 3. 35-49 years old Residential area (location) The place where the respondent lived during the census 1. Urban 2. Rural* Highest education level (education) Highest education level of the respondent 1. Do not go to school 2. Primary school 3. Middle school 4. High school and above 1. Do not go to school and primary school* 2. Middle school 3. High school and above Marriage status (married) Respondents' marital status during the census 0. Not married* 1. Married Number of living children (children) The number of living children owned by the respondent 0. No living children* 1. 1 living children 2. 2 living children 3. 3 living children 4. 4 living children or more Occupation (occupation) Respondents' type of occupation 0. Not working 1. Agriculture* 2. Others AFEBI Economic and Finance Review (AEFR) Volume 6, No. 1 (2021) 8 Wealth quintiles (wealth) Household income quintile 1. Q1 (lowest)* 2. Q2 3. Q2 4. Q4 5. Q5 (highest) Husband's desire to have children (husband) The number of children the husband wants 1. Less 2. Equal 3. More 4. Do not know 5. Do not have a husband 0. Do not have a husband* 1. Equal 2. Others Note: * = reference category To support the findings and provide a broader perspective, this study will present the data or observations in a concise and clear manner. Descriptive analysis in this study is also important to see the significant relationship between variables. In addition to descriptive analysis, the authors used a multinomial logistic regression model. The multinomial logistic regression model is an analytical tool used to describe the relationship between the dependent variable in the form of multinomial data and the independent variables. The multinomial scale is a measurement that is divided into more than two categories. This study formed two separate models, namely a model of the entire sample of women of childbearing age and a model of women of childbearing age who is currently married. The female model aged 15-49 who is currently married is made to see the difference in the impact when a woman has a husband, who also has a voice in determining the number of children. This model will only look at the direct impact of internet use on the number of children desired by women of childbearing age. The method used to examine the effect of the internet on the ideal number of women in Indonesia in this study is logistic regression with a nominal scale dependent variable with the following three categories. • Y=1 ; wants 0-2 children • Y=2 ; wants 3-4 children • Y=3 ; wants ≥5 children and non-numeric response Next, the model can be described as follows. 1. Women of childbearing age 𝑔𝑗(𝑥) = 𝛽𝑗0 + 𝛽𝑗1𝐼𝑛𝑡𝑒𝑟𝑛𝑒𝑡 + 𝛽𝑗2𝑓𝑝𝑖𝑛𝑡𝑒𝑟𝑛𝑒𝑡 + 𝛽𝑗3𝑎𝑔𝑒 + 𝛽𝑗4𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛 + 𝛽𝑗5𝑒𝑑𝑢𝑐𝑎𝑡𝑖𝑜𝑛 + 𝛽𝑗6𝑚𝑎𝑟𝑟𝑖𝑒𝑑 + 𝛽𝑗7𝑐ℎ𝑖𝑙𝑑𝑟𝑒𝑛 + 𝛽𝑗8𝑜𝑐𝑐𝑢𝑝𝑎𝑡𝑖𝑜𝑛 + 𝛽𝑗9𝑤𝑒𝑎𝑙𝑡ℎ + 𝛽𝑗10ℎ𝑢𝑠𝑏𝑎𝑛𝑑 2. Women of childbearing age who is currently married 𝑔𝑗(𝑥) = 𝛽𝑗0 + 𝛽𝑗1𝐼𝑛𝑡𝑒𝑟𝑛𝑒𝑡 + 𝛽𝑗2𝑓𝑝𝑖𝑛𝑡𝑒𝑟𝑛𝑒𝑡 + 𝛽𝑗3𝑎𝑔𝑒 + 𝛽𝑗4𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛 + 𝛽𝑗5𝑒𝑑𝑢𝑐𝑎𝑡𝑖𝑜𝑛 + 𝛽𝑗6𝑐ℎ𝑖𝑙𝑑𝑟𝑒𝑛 + 𝛽𝑗7𝑜𝑐𝑐𝑢𝑝𝑎𝑡𝑖𝑜𝑛 + 𝛽𝑗8𝑤𝑒𝑎𝑙𝑡ℎ + 𝛽𝑗9ℎ𝑢𝑠𝑏𝑎𝑛𝑑 4. RESULT AND DISCUSSION 1) Difference in the ideal number of children Bivariate descriptive analysis is carried out to explain the sample description when viewed by the ideal number of children (the desired number of children). Table INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) 9 2 is a summary of the sample statistics when viewed by the ideal number of children (the desired number of children). Table 2. Summary of Descriptive Statistics for the Unit of Analysis by Ideal Number of Children Variable Ideal Number of Children (Number of Children Wanted) 0-2 3-4 ≥5 and non- numeric Total Internet Usage Everyday 10.013 5.461 1.469 16.943 59,10 32,23 8,67 100 Everyweek 2.574 1.484 474 4.532 56,80 32,74 10,46 100 Less than once a week 840 509 239 1.588 52,90 32,05 15,05 100 Never 11.083 8.842 5.019 24.944 44,43 35,45 20,12 100 No answer 15 10 2 27 55,56 37,04 7,41 100 Read about family planning from the internet Yes 6.228 3.742 838 10.808 57,62 34,62 7,75 100 No 18.279 12.534 6.350 37.163 49,19 33,73 17,09 100 Age 15-24 8.935 3.901 1.395 14.231 62,79 27,41 9,80 100 25-34 6.764 5.235 1.640 13.639 49,59 38,38 12,02 100 35-49 8.826 7.170 4.168 20.164 43,77 35,56 20,67 100 Residential Area Rural 13.963 8.469 3.088 25.520 54,71 33,19 12,10 100 Urban 10.562 7.837 4.115 22.514 46,91 34,81 18,28 100 Education Level Do not go to school 215 288 337 840 25,60 34,29 40,12 100 Primary school 4.934 4.233 2.679 11.846 41,65 35,73 22,62 100 Middle school 14.787 8.337 3.324 26.448 55,91 31,52 12,57 100 High school and above 4.589 3.448 863 8.900 51,56 38,74 9,70 100 Marriage status Married 15.744 12.385 5.437 33.566 46,90 36,90 16,20 100 Not married 8.781 3.921 1.766 14.468 60,69 27,1 12,21 100 Number of living children 0 8.744 3.949 1.582 14.275 61,25 27,66 11,08 100 1 5.245 2.692 737 8.674 60,47 31,04 8,50 100 2 6.879 4.037 1.313 12.229 AFEBI Economic and Finance Review (AEFR) Volume 6, No. 1 (2021) 10 56,25 33,01 10,74 100 3 2.436 3.488 1.387 7.311 33,32 47,71 18,97 100 ≥4 1.221 2.140 2.184 5.545 22,02 38,59 39,39 100 Occupation Not working 10.362 6.053 2.836 19.251 53,83 31,44 14,73 100 Agriculture 2.495 2.223 1.471 6.189 40,31 35,92 23,77 100 Others 11.655 8.013 2.892 22.560 51,66 35,52 12,82 100 Wealth quintiles 1 4.361 3.819 2.443 10.623 41,05 35,95 23,00 100 2 4.791 2.957 1.438 9.186 52,16 32,19 15,65 100 3 4.943 2.981 1.232 9.156 53,99 32,56 13,46 100 4 5.100 3.203 1.082 9.385 54,34 34,13 11,53 100 5 5.330 3.346 1.008 9.684 55,04 34,55 10,41 100 Husband's desire to have children Less 408 895 324 1.627 25,08 55,01 19,91 100 Equal 10.676 7.951 2.427 21.054 50,71 37,76 11,53 100 More 3.226 2.111 806 6.143 52,52 34,36 13,12 100 Do not know 858 884 1.576 3.318 25,86 26,64 47,50 100 Do not have a husband 9.357 4.465 2.070 15.892 58,88 28,10 13,03 100 Total 24.525 16.306 7.203 48.034 51,06 33,95 15,00 100 Note: Unit of measurement: women of childbearing age The internet is considered to be a source of information and can change the perspective of its users. This is because, on the internet, there is all information from many different points of view. In addition, the internet can also make life or daily activities easier. It can be seen from table 2, the fewer women use the internet, the percentage of both categories of the ideal number of children increases. The majority of women of childbearing age who use the internet every day want 0-2 children, which is 59.10% and 8.67% of them answered that they want five or more children or it's up to God (non-numeric). When women of childbearing age did not use the internet at all, the percentage who answered that they wanted to have five or more children or non-numeric became 20.12%. As is well known, the use of the internet can provide a variety of information, including information about family planning. Based on the results of the univariate analysis, only 22.45% of the total sample had read about family planning via the internet. Women who read information about family planning via the internet tend to prefer fewer children than those who do not. For those who read family planning via INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) 11 the internet, there is 7.75 percent of them wanted to have five or more children or non- numeric, while when women who did not read information about family planning via the internet, 17.09% of them wanted to have five or more children or non-numeric. In every relationship between partners, the desired number of children between wives and husbands is not always the same. Sometimes it is the difference in the ideal number of children between partners that makes a mismatch in fertility desires and the actual fertility. According to 2017 IDHS, in general, men want slightly more children than women. The cross table between the husband's desire to have children and the number of children desired by women of childbearing age gives quite an interesting result. It can be seen from table 2 that women whose husbands want fewer children actually have a greater percentage of wanting to have five or more children or non-numeric than women whose husbands want more and others. There were 19.91% of women whose husbands wanted fewer children who wanted to have five or more children or non-numeric and 13.12% of women whose husbands wanted more children. In other conditions, women who do not know what their husband wants are more likely to want to have five or more children or non-numeric, while those who do not have a husband tend to want 0-2 children. 2) Determinants of the Ideal Number of Children The result of multinomial logistic regression in this study showed that the overall model could well describe the influence between internet use and other observed factors on the number of children desired by the sample. Table 3 is a table of multinomial logistic regression results to determine the effect of internet use on the ideal number of children. Table 3. Multinomial Logistic Regression Results Based on Odds Ratio of Internet Use and Ideal Number of Children According to Childbearing-Aged Women in Indonesia Characteristics Ideal Number of Children (Number of Children Wanted) 0-2 3-4 0-2 to ≥5 or non-numeric to 3-4 β Odds Ratio β Odds Ratio β Odds Ratio Internet Usage 0,194 1,214 0,114 1,121 0,079 1,083 Read About Family Planning From The Internet 0,282 1,326 0,345 1,412 -0,063 0,939 Age 15-24 reference category 25-34 -0,303 0,739 -0,119 0,888 -0,184 0,832 35-49 -0,370 0,691 -0,465 0,628 0,095 1,100 Residential Area Urban 0,182 1,200 0,096 1,101 0,086 1,090 Rural reference category Education Level Do not go to school and primary school reference category Middle school 0,341 1,407 0,217 1,242 0,124 1,132 High school and above 0,124 1,132 0,421 1,523 -0,297 0,743 Marriage Status 0,299 1,349 0,371 1,450 -0,072** 0,931 Number of living children 0 reference category 1 0,474 1,606 0,332 1,394 0,142 1,152 AFEBI Economic and Finance Review (AEFR) Volume 6, No. 1 (2021) 12 2 0,303 1,354 0,335 1,398 -0,032** 0,968 3 -0,725 0,484 0,265 1,303 -0,990 0,372 ≥4 -1,695 0,184 -0,503 0,605 -1,192 0,304 Occupation Not working reference category Agriculture -0,037** 0,963 0,056** 1,057 -0,093 0,911 Others 0,107 1,113 0,208 1,232 -0,102 0,903 Wealth quintiles Q1 reference category Q2 0,371 1,449 0,102 1,107 0,269 1,308 Q3 0,425 1,530 0,161 1,175 0,264 1,302 Q4 0,484 1,623 0,267 1,306 0,218 1,243 Q5 0,485 1,624 0,225 1,252 0,260 1,297 Husband's desire to have children Do not have a husband reference category Equal 0,200 1,221 0,365 1,441 -0,166 0,847 Others -0,769 0,463 -0,470 0,625 -0,300 0,741 Constanta 0,822 2,231 0,173 1,189 0,629 1,876 Note *** p<0.01, ** p<0.05, * p<0.1 Table 4. Multinomial Logistic Regression Results Based on Odds Ratio of Internet Use and Ideal Number of Children According to Childbearing-Aged Women That Are Married in Indonesia Characteristics Ideal Number of Children (Number of Children Wanted) 0-2 3-4 0-2 to ≥5 or non-numeric to 3-4 β Odds Ratio β Odds Ratio β Odds Ratio Internet Usage 0,149 1,160 0,110 1,116 0,039** 1,039 Read About Family Planning From The Internet 0,197 1,218 0,213 1,237 -0,015** 0,985 Age 15-24 reference category 25-34 -0,137 0,872 -0,036** 0,965 -0,101 0,904 35-49 -0,186 0,831 -0,331 0,718 0,146 1,157 Residential Area Urban 0,187 1,206 0,082 1,085 0,105 1,111 Rural reference category Education Level Do not go to school and primary school reference category Middle school 0,354 1,425 0,247 1,280 0,107 1,113 High school and above -0,069 0,934 0,284 1,328 -0,353 0,703 Number of living children 0 reference category 1 0,678 1,971 0,402 1,494 0,277 1,319 2 0,405 1,500 0,323 1,382 0,082** 1,085 3 -0,644 0,525 0,205 1,228 -0,849 0,428 ≥4 -1,592 0,203 -0,556 0,574 -1,036 0,355 Occupation Not working reference category INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) 13 Agriculture -0,006** 0,994 -0,005** 0,995 -0,001** 0,999 Others 0,108 1,114 0,120 1,127 -0,012** 0,989 Wealth quintiles Q1 reference category Q2 0,412 1,509 0,117 1,124 0,294 1,342 Q3 0,479 1,614 0,157 1,170 0,322 1,380 Q4 0,568 1,764 0,293 1,340 0,275 1,316 Q5 0,572 1,771 0,270 1,310 0,302 1,352 Husband's desire to have children Do not have a husband reference category Equal 0,201 1,223 0,347 1,415 -0,146 0,864 Others -0,760 0,468 -0,479 0,619 -0,280 0,755 Constanta 0,810 2,248 0,531 1,700 0,279 1,322 Note *** p<0.01, ** p<0.05, *p<0.1 The internet has quickly become the main tool for finding health information (Rice and Katz, 2001; Webb et al., 2010), including fertility and family planning (Epstein and Rosenberg, 2005; Daniluk and Koert, 2013). With the use of the internet, various information and perspectives from all over the world can be accepted and implemented in a person so that they want to have a certain number of children. With this information, internet users will have more knowledge so that they can think or determine how many children they want or think are ideal, not just surrender everything to God. Based on the regression results in Tables 3 and 4, the entire sample model of women of childbearing age and the sub-sample of women of childbearing age who are currently married have similar results, those who have used the internet have a higher tendency to want to have fewer children than those who never used the internet. The internet has become more accessible over time, providing information to a large population. Governments around the world are taking advantage of the internet as a medium for disseminating information about family planning and contraceptive tools using websites. Research conducted by Nelson (2013) shows that Brazilians who have internet access are relatively more exposed to family planning, sexual health, and fertility knowledge than those without internet access. Community exposure to information related to family planning can then influence the desired number of children. The same thing happened to women in Pakistan. Based on the results of research conducted by Khan and Bari (2015), the media can change behavior by providing new information or choices and can form the identity of the audience who receives it. In addition, the internet also provides convenience in the form of reducing costs for finding information (for example: finding a partner, effective and inexpensive contraceptives, how to educate children, and the costs and benefits of having children) (Guldi et al., 2017). Based on the regression results, the use of the internet has an influence on a person's desire to have a certain number of children. Women who never accessed the internet tended to fall into the group who wanted more than five children and gave non-numerical responses. AFEBI Economic and Finance Review (AEFR) Volume 6, No. 1 (2021) 14 More evidence that Internet use can affect fertility was reported by Bocconi University in 2019. The Internet has been shown to increase the number of children born to highly educated women in Germany. The Internet also has a positive effect on overall satisfaction and time spent with children on weekdays. Since the internet expands and then increases economic activity, additional income (assuming children are a normal good) can increase the number of pregnancies that lead to births. At the same time, this can increase the opportunity cost of having a child and thus reduce the number of pregnancies that lead to birth. (Rindfuss et al., 1996; Martin 2000; Adsera 2004; Blossfeld et al., 2005; Kravdal and Rindfuss 2008; Pailhe´ and Solaz 2012). According to Becker (1960), when income increases with economic growth, the demand for quality children increases the shadow price of children and then reduces the number of children desired. Furthermore, women of childbearing age who have read information about family planning via the internet have a higher tendency to want to have fewer children than those who have never read information about family planning via the internet. Based on the regression results, the entire sample of women of childbearing age and the sub- sample of women of childbearing age who are currently married have similar results. These results are consistent with the government's goal in 2017, which is to reduce the total birth rate. Since 2016, The National Population and Family Planning Board (BKKBN) has targeted the poor, densely populated urban areas, fishing villages, slum areas, and other underdeveloped areas to have an awareness of the importance of the quality of children compared to the number of children. This is done to implement quality human development. The results obtained from this regression indicate that the internet has an important role in disseminating information, especially information about family planning. Women who read about family planning on the internet tended to want to have fewer children and did not give non-numerical responses. Webb et al. (2010) found that online interventions can positively influence a person's health behavior, this is also supported by the results of a study conducted by Wojcieszek and Thompson (2013) which found that there was a significant increase in knowledge about family planning after an online intervention. The provision of information about family planning online via the internet has been proven to affect the way of thinking and behavior of population fertility in several countries. Providing information via the internet is more effective in changing the way people think than the traditional way because of the convenience provided by the internet. The empirical evidence of this statement is proven by the research results of Daniluk and Koert (2015). After reading articles on fertility and family planning via the internet, the knowledge about fertility and beliefs about fertility that exist in Canadian communities can change. Based on recent research, low birth rates are thought to occur due to a lack of knowledge about fertility. Japanese citizens have lower knowledge of fertility compared to other developed countries, this could be one of the reasons why Japan has a low birth rate (Maeda et al., 2015). Interest in having children has a strong association with knowledge of fertility. Therefore, to prevent childlessness due to a lack of information on fertility, people who are not interested in having children need INTERNET USAGE AND IDEAL NUMBER OF CHILDREN IN INDONESIA (THE ANALYSIS OF THE 2017 IDHS) 15 to know the facts about fertility. There needs to be an increase in fertility education interventions from reliable sources that can be disseminated via the internet because often the information provided by the internet is inaccurate. 5. CONCLUSION The results of the inferential analysis show that internet use and socioeconomic characteristics influence the ideal number of children or the number of children desired by women of childbearing age. Some factors are not proven to be statistically significant in affecting the overall infertility of women of childbearing age, which is employment in agriculture. For the ideal number of children of women of childbearing age who are married, factors that are not proven to be statistically significant are the use of the internet and reading family planning information through the internet, employment in agriculture, and higher education. Women aged 15-49 who have used the internet are more likely to want to have fewer children and do not answer non-numerically than those who never use the internet. Those who have read information about family planning via the internet have a higher tendency to want to have fewer children and do not answer non-numerically than those who have never read information about family planning through the internet. The socioeconomic conditions that women have also cause them to be more likely to want to have fewer children and not answer non-numerically. 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