Jurnal Akuntansi ISSN 2303-0356 Vol. 12, No.1, February 2022 Hal. 23-36 23 SI APIK Application User Satisfaction with The TAM and Delone and Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh Yulia Rahmana1, Mirna Indriani2 Faculty of Economics and Business, Syiah Kuala University, INDONESIA1,2 ARTICLE INFO ABSTRACT Article history: Received: Dec 13,2021 Revised: Feb 11, 2022 Accepted: Feb 21, 2022 The research objective was to see the effect of the information system quality, information quality, perceived usefulness, and perceived ease of use on user satisfaction of the SI APIK application. The study population was Micro, Small, and Medium Enterprise (MSME) that had attended training on compiling Android-based financial reports. The study sample that included 32 respondents were determined using the census method. The sample collection was carried out by means of a questionnaire to the respondents. The results showed that quality of information systems has no significant effect on user satisfaction of SI APIK application, quality information has no significant effect on user satisfaction of SI APIK application, perceived usefulness is significant on user satisfaction of SI APIK application, perceived ease of use has no significant effect on user satisfaction of SI APIK application, quality of information systems, quality information, perceived usefulness, and perceived ease of use simultaneously affect user satisfaction of SI APIK application. Keywords: Quality of Information Systems; Quality Information; Perceived Usefulness; Perceived Ease of Use; User Satisfaction Correspondence: Mirna Indriani mirna_indriani@unsyiah.ac.id How to cite (APA Style): Rahmana, Y., Indriani, M. (2022). SI APIK Application User Satisfaction with The TAM and Delone and Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh. Jurnal Akuntansi, 12(1), 23-36 https://doi.org/10.33369/j.akuntansi.12.1.23-36 INTRODUCTION In Indonesia, Micro, Small, and Medium Enterprises (MSME) are the biggest contributor to the country's economy. MSME reached 64.2 million, contributing 61.07% of Indonesia's gross domestic product (GDP). MSMEs are called the pillars of the community's economy because they can absorb 96.92% of the total workforce (Jayani, 2021). The historical record of MSME has proven that MSME is powerful in dealing with various threats of economic shocks that previously occurred. At the end of 2019, MSME was again shaken by the 2019 Covid pandemic. This shock made MSME helpless. The results of a survey conducted by Bank Indonesia informed that around 87.5 percent of MSME were affected by the Covid-19 pandemic, and about 93.2% of MSME sales were disrupted and had a negative impact on MSME stability. This phenomenon is due to the limitation of physical distance among people, resulting in a decrease in purchasing power. MSMEs that utilize digital technology can save themselves from the impact of the pandemic. Technology can penetrate the distance that has been an obstacle. MSMEs that adapt to conditions by providing the products and services needed during the pandemic will survive by innovating. The innovation process for MSME is possible because MSME has the convenience of adopting innovations in the field of technology. Technology adoption is carried out to increase business growth because MSME does not have difficult bureaucracy and complicated systems. Smaller MSME has a smaller business scope so that MSME have an advantage in the relationship between employees. Then MSME also has high flexibility in adapting their business to very dynamic market conditions. The very flexible nature of MSME causes MSME to have advantages such as speed of innovation, low-cost structure, and the ability to focus on specific sectors (Stefanovic et al., 2010). Besides benefits, MSME also has a weak side due to limited time in completing needs, control over budget and financing, and mailto:mirna_indriani@unsyiah.ac.id https://doi.org/10.33369/j.akuntansi.12.1.23-36 SI APIK Application User Satisfaction With The Tam and Delone & Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh Yulia Rahmana and Mirna Indriani 24 lack of human and social capital (Ogunsade and Obembe 2016). Realizing that MSME is a buffer for the national economy, MSME needs special attention because maintaining the sustainability means maintaining the nation's stability. Several policies continue to be disbursed for MSME to grow and develop. For example, since 2016, Bank Indonesia has helped MSME apply technology for MSME financial management by providing MSME applications called SI APIK (information system for recording financial information applications). SI APIK is an application that MSME can use for free. This application is designed to make it easier for MSME to prepare accounting records and financial reports. This application is designed to be used by Android and IOS users. The application's design is done simply so that MSME can easily use it. SI APIK presents the menus needed by SMEs. SI APIK is expected to positively impact business actors' business activities because it is user- friendly (Anjilni, 2020). After the application was launched, it was recorded that more than 50,000 users had installed it on their smartphones. This data is obtained based on the Google Play application. This number is still low compared to the number of MSMEs in Indonesia today, almost 64.2 million. Based on this data, it gives rise to a question of why there are still many MSMEs that have not used the application, while the application is provided free of charge and provided by Bank Indonesia. How is the acceptance of SMEs to the application? In academic studies, one of the main factors affecting user acceptance of any application, including the SI APIK, can be seen from the Theory Acceptance Model (TAM). This theory is a theory that is commonly used in analyzing the reasons why someone accepts or rejects an information technology. This theory was proposed by Davis (1989), which is used to measure the level of acceptance and understanding of users in a newly launched service. Researchers try to generalize by comparing, extending, and integrating models (Hess et al., 2010, 2014; Venkatesh et al., 2003; Venkatesh & Davis, 2000). Two main factors in this theory are perceived ease of use and perceived usefulness. These two factors concern researchers to see the user's intention to use Information Systems (IS). According to this model, the use of SI is influenced by these two factors (Buana & Wirawati, 2018). In addition to the TAM model, the acceptance model of the system was also proposed by Delone & McLean (2003). This model uses a measurement of user satisfaction which can cause an SI to be used by the user. User satisfaction is generally determined by three elements, namely: system quality, information quality, and service quality (Delone & Mclean, 2003), but Simon Nisja Putra Zai (2014) research found the opposite. The IS success model proposed by (Delone & Mclean, 2003) is a popular model used by researchers to test system success (Purwati et al., 2021; Tahu & Yuesti, 2021). This study will examine two components of TAM, namely perceived ease of use and perceived usefulness and the two components of the system success model proposed by DeLone & McLean (2003), namely the quality of the system and the quality of information that is used as a predictor of user satisfaction with the SI APIK application testing the two components of each concept given that the SI APIK application is only used for MSME businesses. The SI APIK system is a simple system intended for Msme's business criteria. Testing the TAM model and the success of the DeLone & McLean (2003) system tested for the success of SI APIK is still rarely done; therefore, this study was conducted to investigate whether the generalization of the integration of the two theories can be proven by using environmental settings in MSME. The research results are expected to be used as the basis for fostering MSME, especially in providing a system that helps entities manage MSME bookkeeping/accounting administration. Financial Information Recording Application Information System (SI APIK)) The Financial Information Recording Application Information System (SI APIK) is facilitated by Bank Indonesia (BI). This application provides simple, fast, and accessible Jurnal Akuntansi ISSN 2303-0356 Vol. 12, No.1, February 2022 Hal. 23-36 25 financial accounting records based on android. Accounting records in this application follow the usual accounting cycle, starting from recording general ledger and financial reports. Financial reports that have never been made using this application can be generated. Entrepreneurs will get information about accounts receivable, payable, and separate between business and personal assets. This application has a recording standard that refers to the accounting standards compiled by the Indonesian Institute of Accountants (IAI), namely SAK EMKM. The recording application feature uses debit and credit mutations (double entry) through single entry on transactions, the accounts available are straightforward. SI APIK can be used for two business models: individual businesses and businesses that do not have a legal entity with the type of business in agriculture, services, trade, manufacturing, fisheries, cultivation, and animal husbandry. The objectives of establishing SI APIK) are among others: MSME have neatness in recording financial transactions and can assist business actors in obtaining bank financing. Theoretical Framework and Hypothesis Development Theory Acceptance Model (TAM) The Theory Acceptance Model is well known as the TAM theory, a theory of user acceptance or acceptance of information technology. The theory was first coined by Davis (1989) by adopting the Theory of Reasoned Action (TRA) proposed by Fishbein et al. (1980). Researchers use TAM to measure a new service level that users can accept and understand. Researchers often use this model in researching information systems because the model is simpler and easier to implement. The basic assumption in this theory is that a person's perception of something can determine a person's attitude and behavior. Thus it can be analogized that a person's attitude in accepting technology is very dependent on the user's perception and reaction to information technology (Adhiputra, 2015). Through TAM, user acceptance of certain information technologies can be estimated, such as applications that have been widely circulated. According to Davis et al. (1989) (figure 1), user behavior is generally based on the perceived ease of using a technology that will affect the perception of its usefulness. Someone believes that technology has uses that will influence an individual to have the intention to use information technology and thus ultimately use information technology. The dynamics of this perception are also largely determined by beliefs, attitudes, intentions, and user behavior relationships (Dimoka & Davis, 2008; Hendra, 2016). McLean Model (MD) is a model that is used to measure the success or failure of an information system according to the user's view. DeLone & McLean, developed this model in 1992. This model is regarded as the successful model of information system (figure 2). This model reveals that there are six dimensions of measuring the success of information systems : system quality, information quality, usage, and user satisfaction, which impact individuals and organizations. The relationship between variables can be seen in Figure 2. Percieved Usefulness Percieved Ease of Use Percieved Usefulness Actual System Use Figure 1. Technology Aceptence Model (TAM) (Davis et.al 1989) SI APIK Application User Satisfaction With The Tam and Delone & Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh Yulia Rahmana and Mirna Indriani 26 The early MD model (1992) defined system success as having six dimensions, namely Information Quality (KI), System Quality (KS), User Satisfaction (KP), System Use (PS), Individual Impact (DI), and Organizational Impact (DO). In the 1992 MD model, there are nine relationships that occur to determine the success of the system. The nine relationships, four of them relate system quality and information quality to user use and satisfaction. Two reciprocal relationships between users and system satisfaction, two relationships between users and system satisfaction on individual impacts and finally one relationship between individual impacts on organizations. DeLone & McLean (2003) updated the previously proposed model ten years later. In the new model, it is added that service quality is an important component that significantly determines the system's success. This justified model combines personal and organizational impact into one, which is called net benefit. This model has been tested in various contexts to assess the success of technologies such as expert systems (Yoon et al., 1995), knowledge management systems (Kulkarni et al., 2006), and enterprises (Maas et al., 2013) in work settings, and online shopping (Chiu et al., 2009), B2C e-commerce (Liu & Lai, 2014) in non- work settings with various respondents such as students (Teo et al., 2008), consumers (Chiu et al., 2009). System quality System quality is a measure of the system itself and reflects the system's interaction with users. There are several indicators used to determine a quality system as stated by Nelson et al. (2005:206), namely 1) reliability of the system that is operated to meet the user needs, 2) system flexibility, a flexible system can meet the needs of various users and accommodate special conditions, 3) Integration, a system becomes more useful for users if it can combine data between one part and another to support decision making, 4) Accessibility, a quality system must have the ability to be easily accessible in various situations, 5) response time, a system must be able to respond to user needs as soon as possible so that it can help users to make decisions. Information Quality The quality of information shows the quality of the output of a system (Rukmiyati & Budiartha, 2016). Quality information will provide value to its users with the characteristics of the information in accordance with user needs. The quality of the data produced by a system is good, the better the decisions made by users will be. To state that the information produced by a quality system must have specific characteristics. According to Mc Leod (2010), the characteristics of quality information are; accurate, relevant, timely, and complete. Figure 2 Information Systems Success Model (DeLone & McLean 1992) Jurnal Akuntansi ISSN 2303-0356 Vol. 12, No.1, February 2022 Hal. 23-36 27 If one of these characteristics is not met, then the quality of the information produced by the system is not good enough. User Satisfaction Responses and feedback given by users after using the information system indicate the level of satisfaction with that information system. User satisfaction has very subjective criteria because it shows how much users like the system used. User satisfaction also appears based on the level of a user's feelings based on the results of a comparison between user expectations for the product. Furthermore, according to Livary (2005), user satisfaction is also determined by the system's success in meeting users' needs. If user needs are met, user satisfaction will increase and vice versa. User satisfaction can also be seen from the increasing trend of SI users. Therefore, it can be concluded that systems will not occur if (Isnaeningsih et al., 2021). User satisfaction reflects how users perceive the actual system, not the technical quality of the system (Guimaraes et al., 2003). Therefore, user satisfaction is generally used to measure the effectiveness of information systems (Melone, 1990). Several factors cause user satisfaction, such as the technical ability of users, acceptance of information systems by users, and the usefulness of the information system itself (Lee & Kim, 1992). Information system user satisfaction factors can be measured through user perceptions of completeness of functions/features, stability/reliability, user-friendliness, innovation, security, and flexibility (Supriatna & Jin, 2006). Relationship between System Quality, Information Quality, and User Satisfaction with the SI APIK Application Consider designing or choosing a system to always look at the user aspect. Therefore the quality indicator of a system is always seen from the user's perspective. User reactions, especially user satisfaction, are the main indicators of system acceptance. The more satisfied users are with a system, it shows that the system has quality following user expectations. SI APIK is designed to meet the needs of MSME with the hope that SI APIK can help MSME run their business for the better therefore the satisfaction of SI APIK users will be a proxy for the quality of the SI APIK system. The use of the application is felt to be useful if it is felt that it is not difficult to operate so that users will improve their performances. Increasing the trust of application users is expected to improve their performance. Empirical results that report that system quality affects user satisfaction have been carried out such as Nugraheni (2016); Rukmiyati & Budiartha (2016); Isnaeningsih, Fitriati, Pujiharto, & Astuti (2021). Therefore, the hypothesis proposed in this study is: H1: The quality of the information system affects the satisfaction of the SI APIK application users The quality of information shows the quality of an output from the information system. The quality of data offers the system to process data into more useful information Bodnar & Hopwood (2006:15). Data quality can be reflected if the information is accurate, relevant, timely, and complete (Mc Leod, 2010). Users will be satisfied if the information produced by a system has a quality that is useful for users for the decision-making process. Several studies have proven that the quality of information produced by information systems has benefits for users so that users are satisfied with the information, such as research by Laumer, Maier & Weitzel (2017); Ong et al. (2009). Therefore, the hypothesis proposed in this study is: H2: Information Quality affects user satisfaction of the APIK SI Application SI APIK Application User Satisfaction With The Tam and Delone & Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh Yulia Rahmana and Mirna Indriani 28 Relationship of Perceived Usefulness, Perceived Ease of Use to User Satisfaction of the SI APIK Application Perceived usefulness is a person's belief that an increase in performance will occur when using certain technologies. If a person believes that the system is proper, he will use it. Conversely, if you feel that the information system is less useful, then the system will not be used (Jogiyanto, 2007). The research results by Amalia & Pratomo (2016); Rukmiyati & Budiartha (2016) showed proven results that the quality of information systems had a positive effect on the satisfaction of accounting software end-users. Therefore, the research hypothesis proposed is: H3: Perceived usefulness affects user satisfaction of the APIK SI application In addition to perceived usefulness, perceived ease of use also greatly determines application user satisfaction (Buana & Wirawati, 2018). The ease of describing the user does not require excessive effort in using it, or the user is free from difficulties (Davis, 1989). Therefore, the research hypothesis proposed is: H4: Perceived Ease of Use affects user satisfaction of the SI APIK Application Based on the framework described, the proposed conceptual chart can be seen in Figure 3 RESEARCH METHODS Samples and Data Collection Techniques The sample used is MSME entrepreneurs who have received training from Bank Indonesia (BI). Of the 150 MSMEs that received training, 32 (21.3%) respondents filled out the questionnaire. Questionnaires were distributed through Google Forms, and some were delivered directly with prior agreement. The questionnaire was sent several times to remind MSME that the distribution was 12 weeks. When it was confirmed that the respondents did not fill out the questionnaire, they generally did not fill it out because they no longer used SI APIK in their business. Therefore, data processing was only carried out on 32 participants who attended the SI APIK training conducted by Bank Indonesia. Variable Measurement The dependent variable used is the user satisfaction of the SI APIK application. The variable of user satisfaction is measured by a special design by Doll & Torkzadeh (1998), which consists of five dimensions, namely content, accuracy, format, ease of use, and timeliness. ). The instrument consists of 5 question items. Respondents were asked to rate the users' satisfaction using a Likert scale with strongly disagree to strongly agree on a scale of 1 User Satisfaction (US) System Quality (SQ) Information Quality (IQ) Perceived Usefulness (PU) Perceived Ease of Use (PEU) Figure 3. Conceptual Framework Jurnal Akuntansi ISSN 2303-0356 Vol. 12, No.1, February 2022 Hal. 23-36 29 to 5 on each question item for each instrument. The instrument used in measuring the information system quality variable is the instrument developed by Bailey & Pearson (1983). This instrument consists of access convenience, system flexibility, system integrit y, and response time. The instrument consists of 8 question items and uses a Likert scale of 1 to 5. The instrument used to measure the information quality variable is developed by Mc Leod & Schell (2013:38), which includes accuracy, relevance, and accuracy. time (timeliness), and complete (complete). The instrument consists of 10 question items. Perceived usefulness describes the level of belief that a person believes that his work performance will increase by using a certain subject (Davis, 1989). The instrument developed by Davis (1989) was used to measure the perceived usefulness variable. This instrument consists of four measurements: speeding up work (work more quickly), improving performance, increasing productivity, and making work more accessible. RESULTS AND DISCUSSION Data Description The characteristics of research respondents can be seen in the table below. MSME users are dominated by women and have an undergraduate education (table 1). Generally, respondents who fill out the questionnaire are the owner or business owner, Table 1. Characteristics of Research Respondents No Characteristics of Respondents Total Frequency 1. Sex 1.1 Male 13 40,6 1.2 Female 19 59,4 Total 32 100 2. Age 2.1 20 - 25 7 21,7 2.2 25 – 35 15 46,9 2.3 35 – 45 6 18,8 2.4 45 - 50 2 6,3 2.5 >50 years 2 6,3 Total 32 100 3. Last Education 3.1 D3 5 15,6 3.2 S1 19 59,4 3.3 S2 1 3,1 3.4 Others 7 21,9 Total 32 100 4. Position 4.1 CEO 1 3,1 4.2 Owner 25 78,2 4.3 Director 3 9,4 4.4 Operational manager 1 3,1 4.5 Accounting Staff 1 3,1 4.6 Operator 1 3,1 Total 32 100 Descriptive Research Variables The frequency of respondents' answers to research variables can be seen in table 2. The average answers are between 3 and 4 or between neutral and agree. It means that respondents do not consider the quality of SI APIK to be good, and the information produced has benefits for users. The highest score is only in the perception that SI APIK has usefulness, but the score for the ease of use of SI APIK is also still low at 3.28, and the level of user satisfaction with SI APIK is only 3.34. SI APIK Application User Satisfaction With The Tam and Delone & Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh Yulia Rahmana and Mirna Indriani 30 Tabel 2. Frequency Distribution of Respondents' Answer No. Item STS TS N S SS Average (KI) Fr % Fr % Fr % Fr % Fr % System Quality (SQ) 3.33 1 SQ1 1 3.1 1 3.1 11 34.5 19 59.3 0 0 3.59 2 SQ2 0 0 3 9.4 14 43.8 14 43.8 1 3.1 3.41 3 SQ3 0 0 1 3.4 16 50.0 12 37,5 3 9.4 3.53 4 SQ4 0 0 6 18.8 13 40.6 11 34.4 2 6.3 3.28 5 SQ5 1 3.1 5 15.6 15 46.9 8 25.0 3 9.4 3.22 6 SQ6 0 0 2 6.3 20 62.5 9 28.1 1 3.1 3.28 7 SQ7 1 3.1 3 9.4 17 53.1 10 34.5 1 3.4 3.22 8 SQ8 1 3.4 4 12.5 14 43.8 12 37.5 1 3.1 3.25 Information Quality 1 QI1 2 6.3 3 9.4 11 34.4 16 50.0 0 0 3.28 3.28 2 QI2 1 3.1 2 9.4 11 34.4 13 40.6 4 12.5 3.50 3 QI3 1 3.1 3 10.3 12 37.5 11 34.4 5 15.6 3.50 4 QI4 1 3.1 3 9.4 13 40.6 12 37.5 3 9.4 3.11 5 QI5 1 3.1 5 15.6 15 46.9 10 31.3 1 3.1 3.16 6 QI6 0 0 5 15.6 15 46.9 7 24.1 2 6.9 3.19 7 QI7 2 6.3 3 9.4 15 46.9 12 37.5 1 3.1 3.16 8 QI8 2 6.3 0 0 15 46.9 14 43.8 1 3.1 3.38 9 QI9 1 3.1 2 6.3 16 50 11 34.4 1 3.1 3.31 Perceived Usefulness 1 PU1 1 3.1 4 12.5 12 37.5 12 37.5 1 3.1 3.38 3.4 2 PU2 1 3.1 6 18.8 8 25 16 50.0 1 3.1 3.31 3 PU3 1 3.1 2 6.9 13 40.6 12 37.5 4 12.5 3.50 4 PU4 1 3.1 2 6.9 12 37.9 17 53.1 0 0 3.41 Perceived Ease of Use 1 PE1 3 9.4 4 12.5 13 40.6 11 34.4 1 3.1 3.09 3.25 2 PE2 1 3.1 5 15.6 15 46.9 10 31.3 1 3.1 3.16 3 PE3 1 3.1 4 12.5 13 40.6 12 37.5 2 6.3 3.31 4 PE4 1 3.1 4 12.5 14 43.8 12 37.5 1 3.1 3.25 5 PE5 0 0 3 9.4 11 34.4 16 50.0 2 6.3 3.63 6 PE6 0 0 3 9.4 13 40.6 14 43.8 2 6.3 3.47 User Satisfaction (US) 1 US1 2 6.3 3 6.3 15 46.9 11 34.4 1 3.1 3.19 3.34 2 US2 2 6.3 3 9.4 11 34.4 16 50.0 0 0 3.28 3 US3 1 3.1 2 6.3 13 40.6 15 46.9 1 3.1 3.41 4 US4 1 3.1 2 6.3 14 43.8 12 37.5 3 9.4 3.44 5 US5 1 3.1 2 6.3 15 46.9 11 34.4 3 9.4 3.31 Test Results and Discussion Validity testing is carried out by testing the product-moment correlation coefficient with a significance value of 0.05. The test results of all question items (table 3) have a significant value because the correlation coefficient is more than the R-table (N32=0,349). It can be stated that the research instrument is valid. The result of the reliability test of each variable can be seen in table 4. are 0.912 for system quality. Of 0.917, for the perceived usefulness of 0.897 for perceived ease of use of 0.90 and user satisfaction of 0.896. The reliability value will be fulfilled if the Cronbach alpha value > 0.7 (Ghazali, 2018). In this study, all variables meet the reliability requirements Jurnal Akuntansi ISSN 2303-0356 Vol. 12, No.1, February 2022 Hal. 23-36 31 Table 3. Validity Test Results Variable Item The correlation Coefficient (r) Description System Quality (SQ) SQ1 0,711 Valid SQ2 0,736 Valid SQ3 0,848 Valid SQ4 0,773 Valid SQ5 0,781 Valid SQ6 0,785 Valid SQ7 0,791 Valid SQ8 0,775 Valid Informaton Quality (IQ) IQ1 0,852 Valid IQ2 0,883 Valid IQ3 0,894 Valid IQ4 0,820 Valid IQ5 0,869 Valid IQ6 0,842 Valid IQ7 0,865 Valid IQ8 0,906 Valid IQ9 0,871 Valid IQ10 0,741 Valid Perceived Usefulnes (PU) PU1 0,919 Valid PU2 0,925 Valid PU3 0,916 Valid PU4 0,843 Valid Perceived Ease of Use (PEU) PEU1 0,892 Valid PEU2 0,806 Valid PUE3 0,901 Valid PUE4 0,907 Valid PUE5 0,743 Valid PEU6 0,799 Valid User Satisfaction (US) US1 0,875 Valid US2 0,903 Valid US3 0,939 Valid US4 0,840 Valid US5 0,887 Valid Source: Data processed (2021) Tabel 4. The Reliability Test Result Variabel Jumlah Item Pertanyaan Cronbach Alpha Description Sistem Quality (SQ) 8 0,914 Reliable Information Quality (IQ) 10 0,923 Reliable Perceived Usefulnes (PU) 4 0,899 Reliable Perceived Ease Of Use (PUE) 6 0,903 Reliable User satisfaction (US) 5 0,896 Reliable Source: Data processed 2021 The results of testing the hypothesis (H1), which tested the relationship between information system quality and user satisfaction, showed that information system quality (KSI) did not affect user satisfaction. It is shown from the probability value of 0.746, which is greater than the level of significance used, which is 0.05 (see table 2), therefore the research hypothesis that KSI affects job satisfaction cannot be accepted. The results of this study contradict the results of research by Buana & Wirawati (2018); Nugraheni S (2016); SI APIK Application User Satisfaction With The Tam and Delone & Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh Yulia Rahmana and Mirna Indriani 32 Rukmiyati & Budiartha (2016) but supports research by Simon Nisja Putra Zai (2014); Tulodo & Solichin (2019), which shows that system quality does not affect user satisfaction. The results of testing the second hypothesis (H2), which sees the relationship between information quality and user satisfaction, indicate that information quality does not affect user satisfaction because the probability value of 0.150 is greater or >0.05, thus the second hypothesis cannot be accepted. The results of this study cannot support previous research which states that the quality of information affects user satisfaction. This result is also supported by previous research, namely Amalia & Pratomo (2016), which shows that the quality of information does not affect users' satisfaction with accounting information systems. Table 5. Hypothesis Testing Results Model Standardized Coefficients T Sig Conclusion System Quality -0.04 -0.327 0.746 Rejected Information quality 0.341 1.482 0.150 Rejected Perceived Usefulnes 0.649 2.656 0.013 Accepted Perceived Ease of Use -0.039 -0.279 0.782 Rejected R2 = 0.84; Sig 0.00 F = 48,593; Sig 0.00 The study results (table 5) to examine the effect of perceived usefulness on user satisfaction indicate that perceived usefulness has a significant positive impact on user satisfaction because the probability value of 0.013 is smaller than the 5% significance level. Thus, it can be said that perceived usefulness affects user satisfaction of the SI APIK application on MSME in Banda Aceh, and this is under the hypothesis that has been formulated previously where perceived usefulness has a positive effect on user satisfaction. The testing results on the perceived ease of use variable show a probability value of 0.782, greater than the significance level of 0.05, thus perceived does not affect user satisfaction of the APIK SI application on MSME in Banda Aceh. It is not following the hypothesis that has been formulated previously where perceived ease of use has a positive effect on user satisfaction. The reason for rejecting the proposed hypothesis is that there is a possibility that users are not entirely satisfied with the SI APIK application. This can be seen from the average satisfaction level of only 3.34. The descriptive statistics also show that the quality of the SI APIK seen from comfort, flexibility, integrity, and response time is perceived by users in the normal category. Users do not thoroughly think that SI APIK quality is good enough and the information produced by SI APIK. Users do not feel that the data produced is accurate, relevant, timely, and complete. It can be understood because the form of MSME business is individual, there is no party to be held accountable for requiring information from SI APIK, even though they realize that SI APIK has benefits for them with an average score of 3.4. Users also think that SI APIK is not easy to use; this can be seen from the average score of 3.25. The designers of SI APIK tried their best to make this application easy to use, but users don't think so. This situation may occur because the user does not have free time to use the application. Entrepreneurs are usually busy running a business, so they ignore the administrative affairs of the entity, and there is no obligation to account for the business. So that the user's response stating "not easy to use" is questioned considering the level of education of the users is relatively high. Another possibility is that the owners do not delegate administrative matters to other parties or workers, so SI APIK has not been used maximally. Jurnal Akuntansi ISSN 2303-0356 Vol. 12, No.1, February 2022 Hal. 23-36 33 CONCLUSIONS AND SUGGESTION The study results indicate that the quality of information systems, information quality, and perceived ease of use does not affect user satisfaction. At the same time, the perceived usefulness variable has a significant positive effect on user satisfaction. The user's perception of each variable is also still relatively low, so user satisfaction with the APIK SI application is also still down. This study has some limitations. First, the researcher did not ask about the number of assets and turnover or employees, so business identification could not be made. Second, The researcher did not ask when the application was used, whether it was every transaction or not; this could affect the respondents' answers. Third, in the questions asked, the researchers also did not ask whether MSME had hardware facilities, which could affect respondents' responses to the SI APIK application. Suggestions are given for further research so that all the limitations of this research can be accommodated and observe firsthand how the MSME responds to the products provided by Indonesian Bank so that the entire purpose of launching this application can be best utilized for MSME. Requiring MSME to use specific applications to facilitate supervision can be carried out if there is a policy as a sufficient condition for MSME to obtain certain facilities from the government, such as working capital assistance and others. REFERENCES Adhiputra, M. W. (2015). Aplikasi Technology Acceptance Model terhadap pengguna layanan internet banking. Jurnal Bisnis Dan Komunikasi, 2(1), 52–63. Amalia, S. M., & Pratomo, D. (2016). Pengaruh Kualitas Sistem Informasi, Kualitas Informasi, Dan Perceived Usefulness Terhadap Kepuasan Pengguna Sistem Informasi Akuntansi (Studi Pada Pengguna Sistem Informasi Akuntansi Di Rumah Sakit Mata Cicendo Bandung). EProceedings of Management, 3(2). DOI: http://journal.unj.ac.id/unj/index.php/jrmsi/article/view/9183 Anjilni, R. Q. (2020). Membumikan SAK-EMKM Lewat SI APIK BI. Kompasiana.Com. Bailey, J. E., & Pearson, S. w. (1983). Development of a Tool for Measuring and AnalizingComputer User Satisfaction. Management Science, 29(5), 530–545. DOI: https://doi.org/10.1287/mnsc.29.5.530 Bodnar, G. H., & Hopwood, W. S. (2006). Sistem informasi akuntansi. Jakarta: Salemba Empat. Buana, I., & Wirawati, N. G. P. (2018). Pengaruh kualitas sistem informasi, kualitas informasi, dan perceived usefulness pada kepuasan pengguna sistem informasi akuntansi. E-Jurnal Akuntansi Universitas Udayana, 22(1), 683–713. DOI:https://doi.org/10.24843/EJA.2018.v22.i01.p26 Chiu, C., Chang, C., Cheng, H., & Fang, Y. (2009). Determinants of customer repurchase intention in online shopping. Online Information Review. Davis, F. D. (1989). Perceived Usefulness, Perceived Ese of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.5962/bhl.title.33621 Delone, W., & Mclean, E. (2003). The DeLone and McLean model of information systems SI APIK Application User Satisfaction With The Tam and Delone & Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh Yulia Rahmana and Mirna Indriani 34 Success : A ten-year update. Journal of Management Information Systems, 19(4), 9–30. https://doi.org/10.1080/07421222.2003.11045748 Dimoka, A., & Davis, F. D. (2008). Where does TAM reside in the brain? The neural mechanisms underlying technology adoption. ICIS 2008 Proceedings, 169. http://aiset.aisnet.org/icis2008 Doll, W. J., & Torkzadeh, G. (1998). Developing a multidimensional measure of system-use in an organizational context. Information & Management, 33(4), 171– 185.DOI:10.1016/0378-7206(98)00028-7 Fishbein, M., Jaccard, J., Davidson, A. R., Ajzen, I., & Loken, B. (1980). Predicting and understanding family planning behaviors. In Understanding attitudes and predicting social behavior. Prentice Hall. Guimaraes, T., Staples, & Mckeen. (2003). Empirically Testing Some main User-Related Factors for System Development Quality. Quality Management Journal, 10(4), 39–54. DOI:https://doi.org/10.1080/10686967.2003.11919083 Hendra, J. (2016). Aplikasi model TAM terhadap pengguna layanan internet banking di kantor Bank Jatim cabang Situbondo. Jurnal Ilmiah Ecobuss, 4(1), 40–48. Hess, T. J., Joshi, K., & McNab, A. L. (2010). An alternative lens for understanding technology acceptance: An equity comparison perspective. Journal of Organizational Computing and Electronic Commerce, 20(2), 123–154. https://doi.org/10.1080/10919391003712447 Hess, T. J., McNab, A. L., & Basoglu, K. A. (2014). Reliability generalization of perceived ease of use, perceived usefulness, and behavioral intentions. Mis Quarterly, 38(1), 1–28. DOI:10.25300/MISQ/2014/38.1.01 Isnaeningsih, H. N., Fitriati, A., Pujiharto, P., & Astuti, H. J. (2021). The influence Quality of information, Sistem Quality and Service Quality on Satisfaction and User Performace. Jurnal Manajemen Bisnis, 12(2), Layouting. https://doi.org/10.18196/mb.v12i2.11185 Jayani, D. H. (2021). 96,92% Tenaga Kerja Berasal dari UMKM. Databoks.Katadata.Co.Id. Jogiyanto, H. M. (2007). Sistem informasi keperilakuan. Yogyakarta: Andi Offset. Kulkarni, U. R., Ravindran, S., & Freeze, R. (2006). A knowledge management success model: Theoretical development and empirical validation. Journal of Management Information Systems, 23(3), 309–347. DOI:https://doi.org/10.2753/MIS0742- 1222230311 Laumer S, Christian Maier & Tim Weitzel (2017) Information quality, user satisfaction, and the manifestation of workarounds: a qualitative and quantitative study of enterprise content management system users, European Journal of Information Systems, 26:4, 333- 360, DOI: 10.1057/s41303-016-0029-7 Lee, J., & Kim, S. (1992). The relationship between procedural formalization in MIS development and MIS success: A contingent analysis. Information & Management, 22(2), 89–111. DOI:https://doi.org/10.1016/0378-7206(92)90064-M Liu, Z., & Lai, M. (2014). Price Comparison, Product Differentiation and Tacit Collusion in B2C Market. Review of Industrial Economics. Livary, J. (2005). An Empirical Test of DeLoneand McLean Model of Information SystemSuccess: Database for Advance in InformationSystem (DFA. Proquest Company. Maas, A. L., Hannun, A. Y., & Ng, A. Y. (2013). Rectifier nonlinearities improve neural network acoustic models. Proc. Icml, 30(1), 3. Mc Leod, R. (2010). Sistem Informasi Manajemen. Jakarta: Salemba Empat. Mc Leod, R., & Schell, G. P. (2013). Management Information System. Jakarta: Salemba Empat. Melone, N. (1990). A Theoritical Assessment of The User Satisfaction Construct in https://doi.org/10.1057/s41303-016-0029-7 Jurnal Akuntansi ISSN 2303-0356 Vol. 12, No.1, February 2022 Hal. 23-36 35 Information System Research. Management Science, 12–19. https://doi.org/10.1287/mnsc.36.1.76 Nelson, R. R., Todd, P. A., & Wixom, B. H. (2005). Antecedents of information and system quality: an empirical examination within the context of data warehousing. Journal of Management Information Systems, 21(4), 199–235. https://doi.org/10.1080/07421222.2005.11045823 Nugraheni S, I. (2016). Pengaruh Kualitas Sistem Informasi Akuntansi Terhadap Kepuasan Pengguna Paket Program Aplikasi Sistem Informasi Akuntansi (Studi Empiris pada Bank Perkreditan Rakyat di Kota Boyolali). Universitas Muhammadiyah Surakarta. DOI: http://eprints.ums.ac.id/id/eprint/43245 Ogunsade & Obembe, D. (2016) The influence of informal institutions on informal sector entrepreneurship: a study of Nigeria's hand-woven textile industry, Journal of Small Business & Entrepreneurship, 28:6, 413-429, DOI: 10.1080/08276331.2016.1202093 Ong, C.-S., Day, M.-Y., & Hsu, W.-L. (2009). The measurement of user satisfaction with question answering systems. Information & Management, 46(7), 397–403. DOI:10.1016/j.im.2009.07.004 Purwati, A. A., Mustafa, Z., & Deli, M. M. (2021). Management Information System in Evaluation of BCA Mobile Banking Using DeLone and McLean Model. Journal of Applied Engineering and Technological Science (JAETS), 2(2), 70–77. DOI:https://doi.org/10.37385/jaets.v2i2.217 Rukmiyati, N. M. S., & Budiartha, I. K. (2016). Pengaruh kualitas sistem informasi, kualitas informasi dan perceived usefulness pada kepuasan pengguna akhir software akuntansi (studi empiris pada hotel berbintang di provinsi bali). E-Jurnal Ekonomi Dan Bisnis Universitas Udayana, 5(1), 115–142. http://ojs.unud.ac.id/index.php/EEB/article/view Simon Nisja Putra Zai, A. F. D. (2014). Pengaruh Pentingnya Sistem, Kualitas Sistem& Kualitas Informasi Terhadap Kegunaan& Kepuasan Pengguna Dalam Pengembangan Sistem Informasi Akuntansi (Studi Kasus di RSUP Dr.Soeradji Tirtonegoro Klaten). Yogyakarta, Unversitas Negeri Yogyakarta, 1992. Stefanovic, I., Prokic, S., & Rankovic, L. (2010). Motivational and success factors of entrepreneurs: the evidence from a developing country. Zbornik Radova Ekonomskog Fakulteta u Rijeci: Časopis Za Ekonomsku Teoriju i Praksu, 28(2), 251–269. Supriatna, D., & Jin, T. F. (2006). Analisis pengaruh kepuasan pengguna public computer terhadap efisiensi dan efektifitas mahasiswa Trisakti School of Management. Jurnal Bisnis Dan Akuntansi, 8(2), 111–134. DOI:https://doi.org/10.34208/jba.v8i2.154 Tahu, G. P., & Yuesti, A. (2021). Academic Information System In Higher Education: Applicating Delone and Mclean Model. Journal of Contemporary Issues in Business and Government, 27(1), 2844–2853. Teo, T. S. H., Srivastava, S. C., & Jiang, L. I. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99– 132. https://doi.org/10.2753/MIS0742-1222250303 Tulodo, B. A. R., & Solichin, A. (2019). Analisis Pengaruh Kualitas Sistem, Kualitas Informasi dan Perceived Usefulness terhadap Kepuasan Pengguna Aplikasi Care dalam Upaya Peningkatan Kinerja Karyawan. JRMSI-Jurnal Riset Manajemen Sains Indonesia, 10(1), 25–43. Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2). DOI:10.1287/mnsc.46.2.186.11926 Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425. https://doi.org/10.2307/30036540 https://doi.org/10.1080/08276331.2016.1202093 http://dx.doi.org/10.1287/mnsc.46.2.186.11926 SI APIK Application User Satisfaction With The Tam and Delone & Mclean Approach: An Empirical Study on Micro, Small and Medium Enterprises (MSME) in Banda Aceh Yulia Rahmana and Mirna Indriani 36 Yoon, Y., Guimaraes, T., & O’Neal, Q. (1995). Exploring the factors associated with expert systems success. MIS Quarterly, 83–106. DOI: 10.2307/249712 Yuliani, A. (2017). Kemenkop UKM: 3,79 Juta UMKM Sudah Go Online. Www.Kominfo.Go.Id. http://dx.doi.org/10.2307/249712