INTRODUCTION

The Marketplace Marketplace is one of the digital advances experienced by society today. A marketplace is a place to make it easier for sellers and buyers to buy and sell online through internet media (Apriadi and Saputra, 2017). The existence of a marketplace can help business actors to sell their products to interested consumers. On the other hand, consumers can search for the goods they need with various product choices such as brands, colours, sizes, and others just by using cellphones and other internet tools. Marketplace in Indonesia is experiencing development from year to year. Shopping transactions through the Marketplace Marketplace have increased since 2019, which reached Rp. 265.07 trillion. Although 2020 decreased to Rp. 253 trillion, the transaction value increased by 33.2% to Rp. 337 trillion in 2021 (Aseng and Pandeirot, 2022).

According to data from DataIndonesia.id on September 22, 2022, transactions through the MarketplaceMarketplace in 2022 experienced a significant increase to Rp. 842.3 trillion. The findings from We are Social show that the ratio of marketplace users in Indonesia reached 88.1% and named Indonesia the country that uses the MarketplaceMarketplace the most (Artasya and Nuri, 2022). Marketplace has several advantages, so it is in great demand by online buying and selling actors. The advantages of marketplaces are that they are more effective in terms of time and more efficient in terms of cost (Kasmi and Candra, 2017). Marketplaces that have been present in Indonesia include Tokopedia, Shopee, Lazada, Bukalapak, Orami, Blibli, and others.

Blibli is one of Indonesia's growing marketplaces, based on data from the I-2022 quartile price. Co.id Blibli ranks sixth as the Marketplace Marketplace with the highest number of visitors in Indonesia. Blibli's monthly visitors reached 16.3 million in the I-2022 quartile. Based on sources from Tribunnewswiki.com on April 11, 2022, Blibli partners offer electronic products, fashion needs, home appliances, etc. The Blibli application not only sells products from cooperating partners, but Blibli also sells its products. In addition, the Blibli application also provides service features such as Blibli Mitra. This service feature is for micro-businesses that are running small businesses.

Furthermore, this feature makes Blibli Pay later easier for buyers and sellers because buyers can pay for goods based on a predetermined period. Blibli Express Service, this feature can be called Blibli's internal courier. Blibli Mart, this feature offers shopping categories and provides household products. Blibli also provides 24-Hour Customer Care services. Customer Care services to assist users in consulting about application products and services. Although Blibli has provided good and complete services to its consumers, consumers still feel many complaints. Based on sources from Mediakonsumen.com on December 23, 2022, Blibli Application user complaints such as unclear Blibli delivery and poor Customer Service service, orders cancelled for no apparent system reason, and the goods sent did not match those ordered.

System Quality is very important for User Satisfaction. According to Rakhmadian et al. (2017), if consumers feel that the system is easy to use and does not need much effort, it will impact User Satisfaction. System Quality can be measured from several aspects, namely ease of Use, access speed, and system security (Natalia and Br Ginting, 2018). According to Hernita et al. (2020), System Quality measurement focuses on the results of interactions between users and systems. In addition to System Quality, Information Quality significantly affects purchasing decisions. The information presented in the online shop includes information related to the products sold on the online shop. Reliable information is useful for assessing the quality and usefulness of the products sold. To satisfy customers in online shopping, product information must be up-to-date. This can help consumers purchase (Ayuningtiyas and Gunawan, 2018). Information Quality related to the products sold, such as size, colour, stock, and completeness of information in the product description, affects User Satisfaction (Romla and Ratnawati, 2018). On the other hand, if the information provided is not of high quality, it negatively affects User Satisfaction (Rakhmadian et al., 2017). Complete and honest information is the most important thing in online purchases because, in online shopping, consumers cannot see the product directly and only see through photos, so it is not easy to judge the quality of the goods (Wardoyo and Andini, 2017).

Another factor that affects User Satisfaction is Service Quality. Consumers will feel satisfied if the Service Quality provided is under what consumers expect (Iskandar and Nasution, 2019). Service Quality is something that every company pays attention to. Quality Service Quality will meet consumer expectations and impact User Satisfaction (Cesariana et al., 2022). If consumers receive appropriate service or exceed expectations, then consumers will feel satisfied (Sigit and Soliha, 2017). According to Herlistyani et al. (2012) in Armanto (2018), there are efforts to give and receive information from each other in the service process. If the information provided and received by consumers provides good benefits, then consumer User Satisfaction will increase. Services can be known by comparing consumer expectations with the services consumers receive. If the service received or felt by consumers follows expectations, then Service Quality can be called good and high-quality service. However, if the service consumers receive is not as expected, the service is referred to as poor and low-quality Service Quality. Service is essential to attract customer interest and will affect sales (Pane et al., 2018).

Purwati et al. (2021) found that System Quality positively affects User Satisfaction. This research was supported by Hidayatullah et al. (2020). This contradicts the research of Mangun Buana and Wirawati (2018), saying that System Quality does not affect User Satisfaction. Research conducted by Apsari and Astika (2020) and supported by Mofokeng research (2021) states that Information Quality influences User Satisfaction. This study's results differ from the research of Purwati et al. (2021), which states that Information Quality does not affect User Satisfaction. Next, according to the research of Widiani and Abdullah (2018) and supported by Muiz et al. (2019), Rahmadani et al. (2019) said that Service Quality has a positive effect on User Satisfaction. This contradicts research from Manik et al. (2017), saying that Service Quality does not affect User Satisfaction.

The existence of differences from the results of previous studies is interesting to study. This study used the same variables as the previous study: System Quality, Information Quality, Service Quality, User Satisfaction and Use. However, what distinguishes this study from previous studies is to modify the DeLone & McLean (2003) model by looking at indirect influences. This study aims to determine the direct influence of System Quality, Information Quality and Service Quality on Use, to find out the direct influence of System Quality, Information Quality, Service Quality, and Use on User Satisfaction and to find out the indirect influence of System Quality, Information Quality and Service Quality to User Satisfaction through Use on Blibli Marketplace. It is hoped that the results of this study can improve the information system of the Blibli application as a whole, including System Quality, Information Quality, and Service Quality, to provide satisfaction to Blibli application users.

RESEARCH METHODS

From the hypothesis above, the research model can be described as follows:

The research design used in this study is casual associative research which is useful for analyzing the relationships between one variable and another or how one variable affects another. This study aims to determine the direct influence of System Quality, Information Quality and Service Quality on Use, to find out the direct influence of System Quality, Information Quality, Service Quality, and Use on User Satisfaction and to find out the indirect influence of System Quality, Information Quality and Service Quality on User Satisfaction through Use on the Blibli Marketplace. The research shorthand used in this study is a quantitative shortcoming in this study using primary data. Primary data is data that has never been processed before by others. Data collection in this study used a survey with a questionnaire. The survey method is a way or method of collecting data by sharing questions with respondents by distributing questionnaires. The distribution of questionnaires using google forms through social media such as WhatsApp, Instagram, Facebook, and telegram.

In this study, to collect data, a questionnaire was carried out. In this study, the preparation of a questionnaire using a Likert scale. The Likert scale is a research scale used to measure attitudes and opinions. This study used four levels of the Likert scale, namely Strongly Disagree (STS), Disagree (TS), Agree (S), and Strongly Agree (SS). This study used five variables: System Quality, Information Quality, Service Quality, User Satisfaction and Use. System Quality is measured by reliability, East Of Use, Response Time, and Visual Display (DeLone and McLean, 2003). Information Quality variable measurement uses DeLone and McLean (2003) measures: Timeliness, Completeness, Accuracy, Consistency, and Relevance. Service Quality is measured using DeLone and McLean's (2003) Service Quality measures: Assurance, Responsiveness, and Empathy. Measurement of User Satisfaction variables using DeLone and McLean (2003) measures, Repurchase, No Complaints, Recommend To Others, and Experience In Online Shopping. Use variable measurements using DeLone and McLean's (2003) measures, namely Nature Of Use, Intention to Use, and Daily Use.

The population in this study were marketplace users who had used and shopped on the Blibli application. According to Hair et al. (2019), the number of samples must have five times the number of questions analyzed to get a tangible result. There were 38 questions in the questionnaire in this study, so the minimum number of samples required was 190 respondents. This research will use the purposive sampling method. According to Sugiyono (2018), purposive sampling aims to obtain samples that match the researchers' criteria. Criteria – predetermined criteria are. (1) have used and shopped on the Blibli application more than two times in the last year, (2) have been Active users of the Blibli application in the last year, and (3) are in the Jabodetabek area.

In the research conducted using the Smart PLS analysis tool wherein analyzing the data, there are several stages, namely, the first stage is the outer model where the validity test is carried out (1) Convergent Validity Test with a standard loading factor value of > 0.60 is the ideal size (Hair et al., 2019), Average Variance Extracted (AVE) with a Cut-off value of AVE > 0.50. continued (2) The Discriminant Validity Test, judging from the cross-loading value where a value in the standard relation of the construct with measurement items is greater than other construct sizes, can show the results of latent constructs predicting the size on the block better than other block sizes. Meanwhile, the reliability test will use Cronbach alpha and composite reliability measures, with a reliable value standard of > 0.70 (Ghozali, 2016). The next stage is the Inner model by determining the value of the R-square. If the value of the R-Square is at the value of 0.75, 0.50, 0.25, it can be concluded that the inner model is strong, moderate and weak. T-Statistics is a value that is useful to see at the significance level to hypothesis testing by looking for T-Statistics values through the bootstrapping procedure on Smart PLS. Hypothesis testing starts by calculating the path coefficient, then compared with the T-statistical value > T of the table. A hypothesis is acceptable if a statistic T value can be greater than the table T of 1.96 (α 5%) so that it can be interpreted that if a value of T statistic in each hypothesis can be greater than T, the table can show that the hypothesis is accepted or proven (Ghozali, 2016). There is a criterion of the t-statistical test (Ghozali, 2016), namely (1) if the value on the construct of the significance of the t-test is > 0.05, then Ho is accepted, and Ha is rejected so that it can be interpreted that there is no influence between variables, (2) If the constructed value of the significance of the t-test is < 0.05 then Ho is unacceptable, and Ha is acceptable so that it can be interpreted as an influence between variables.

RESULTS AND DISCUSSION

Characteristics of Respondents

Based on the results of the questionnaires distributed online using Google Forms, 190 respondents were collected. The respondents who use and shop the most through the Blibli application are women, with 147 people (77.4%) and the most aged 17 – 22 years, which is 157 people (82.6%). Furthermore, the most respondents with unmarried status were 170 (89.5%) and domiciled in the Tangerang area, which was 100 people (52.6%). Then, most respondents had the status of high school / vocational high school students, namely 157 people (82.6%) and working as students/students, which amounted to 147 people (77.4%). Moreover, most of them have used the Blibli application for > 1 year, which is 96 people (50.5%). Most respondents have shopped through the bible application 1 – 2 times a month, which 97 people (51.1%). Moreover, the most purchased products by respondents were accessories and fashion products, totalling 93 people (48.9%). Based on the results, it can be concluded that many respondents are women aged 17-22 years. They are generation Z who like online shopping, are always connected to the virtual world and can do everything using the sophistication of existing technology. (Results can be seen in Appendix 6).

Outer Model

Validity Test

This study tested a validity test that is useful for knowing a measurement of a statement against the questionnaire used in this study which aims to measure the indicators and variables studied. The statements that will be tested in this study are 38 statements. The validity test in this study is as follows:

Convergent Validity

Outer Loading (Loading Factor)

Of all the results that have been analyzed in the Loading Factor table, a questionnaire indicator totalling 38 statements, there are 30 valid indicators, and eight indicators declared invalid.

Table 4. Hypothesis Test1

	Original Sample (O)	Sample Mean (M)	Standard Deviation (STDEV)	T Statistics (\|O/STDEV\|)	P Values
Information Quality -> Use	0.303	0.301	0.095	3.194	0.001
Information Quality -> User Satisfaction	0.131	0.134	0.092	1.427	0.154
Service Quality -> Use	0.417	0.411	0.096	4.362	0.000
Service Quality -> User Satisfaction	0.391	0.373	0.112	3.510	0.000
System Quality -> Use	0.095	0.106	0.082	1.153	0.250
System Quality -> User Satisfaction	0.169	0.173	0.079	2.133	0.033
Use -> User Satisfaction	0.261	0.274	0.084	3.111	0.002

Source: Data processed by author, 2023

System Quality does not affect Use regarding the T value of 1.510 < 1.96 and the significant value ρ -Value 0.250 > 0.05. This shows that System Quality is not a variable that determines user activity (Use) on the Blibli application. However, Information Quality positively affects Use regarding the T value of 3.194 > 1.96 and the significant value ρ -Value 0.001< 0.05. This shows that the higher the Information Quality provided to Blibli application users, the higher the user activity (Use) on the Blibli application. The results further stated that Service Quality also positively affected Use regarding significant values of ρ -Value 0.000 < 0.05 and statistical T values of 4.362 > 1.96. This shows that the higher the Service Quality obtained by Blibli application users, the higher the user activity (Use) on the Blibli application.

System Quality positively affects User Satisfaction regarding the significant value of ρ -Value 0.033 < 0.05 and the T value of statistics 2.133 > 1.96. This shows that the higher the System Quality in the Blibli application, the more User Satisfaction will increase using the Blibli application. However, Information Quality does not affect User Satisfaction regarding significant values ρ -Value 0.154 > 0.05 T and statistical values of 1.427 < 1.96. This shows that Information Quality is not a variable that determines User Satisfaction when they use the Blibli application. In contrast, Service Quality has a positive effect on User Satisfaction seen from the significant value of ρ -Value 0.000 < 0.05 and T value of Statistics 3.510 > 1.96. This shows that the higher the System Quality in the Blibli application, the more User Satisfaction will increase using the Blibli application. The results further stated that Use positively affected User Satisfaction regarding the significant value of ρ -Value 0.002 < 0.05 and the statistical T value of 3.111 > 1.96. This shows that the higher the Use of the Blibli application, the more User Satisfaction will also increase in using the Blibli application. System Quality positively affects User Satisfaction regarding the significant value of ρ -Value 0.033 < 0.05 and the T value of statistics 2.133 > 1.96. This shows that the higher the System Quality in the Blibli application, the more User Satisfaction will increase using the Blibli application. However, Information Quality does not affect User Satisfaction regarding significant values ρ -Value 0.154 > 0.05 T and statistical values of 1.427 < 1.96. This shows that Information Quality is not a variable that determines User Satisfaction when they use the Blibli application. At the same time, Service Quality has a positive effect on User Satisfaction seen from the significant value of ρ -Value 0.000 < 0.05 and T value of Statistics 3.510 > 1.96. This shows that the higher the System Quality in the Blibli application, the more User Satisfaction will increase using the Blibli application. The results further stated that Use positively affected User Satisfaction regarding the significant value of ρ -Value 0.002 < 0.05 and the statistical T value of 3.111 > 1.96. This shows that the higher the Use of the Blibli application, the more User Satisfaction will also increase in using the Blibli application.

Table 5. Hypothesis Test Results2

Hypothesis	Hypothesis Statement	*P-Value*	T- Statistic	Information	Conclusion
H1	System Quality has a direct positive effect on the Use	0.250	1.153	The data do not support the hypothesis	H1 rejected
H2	Information Quality has a direct positive effect on the Use	0.001	3.194	Data support hypothesis	H2 accepted
H3	Service Quality has a direct positive effect on the Use	0.000	4.362	Data support hypothesis	H3 accepted
H4	System Quality has a direct positive effect on User Satisfaction	0.033	2.133	The data do not support the hypothesis	H4 accepted
H5	Information Quality has a direct positive effect on User Satisfaction	0.154	1.427	The data do not support the hypothesis	H5 rejected
H6	Service Quality has a direct positive effect on User Satisfaction	0.000	3.510	Data support hypothesis	H6 accepted
H7	Use as a direct positive effect on User Satisfaction	0.002	3.111	Data support hypothesis	H7 accepted

Source: Data processed by author, 2023

The test results of the indirect effect of the System Quality variable on User Satisfaction through Use after being tested as a whole obtained a T-statistical value of

1.040 < 1.96 and a value of ρ -Value 0.299 > 0.05. This shows no indirect influence of System Quality on User Satisfaction through Use. Based on the overall results

It is known that System Quality has a positive effect on User Satisfaction (H4), and it is known that there is no indirect influence of System Quality on User Satisfaction through Use (H8). Use does not act as a mediating variable (No Mediation) between System Quality and User Satisfaction. So, the user variable is not proven to be a mediation variable and can be interpreted that directly the Quality system can affect User Satisfaction.

The test results of the indirect effect of the Information Quality variable on User Satisfaction through Use after being tested as a whole obtained a T-statistical value of 2.211 > from 1.96 and a value of ρ -Value of 0.024 < of 0.05. This shows an indirect influence of Information Quality on User Satisfaction through Use. Based on the overall results, it is known that Information Quality does not positively affect User Satisfaction (H5), and it is known that there is an indirect influence of Information Quality on User Satisfaction through Use (H9). It can be interpreted that Use acts as a mediating variable (Full Mediation) between Information Quality and User Satisfaction. So it can be concluded that if the Information Quality is improved, it will increase Use and impact increasing User Satisfaction in the Blibli application.

The test results of the indirect effect of Service Quality variables on User Satisfaction through Use after being tested as a whole obtained a T-statistical value of 2.211 > from 1.96 and a value of ρ -Value of 0.028 < of 0.05. This shows an indirect influence of Service Quality on User Satisfaction through Use. Based on the overall results, it is known that Service Quality has a positive effect on User Satisfaction (H6), and it is known that there is an indirect influence of Service Quality on User Satisfaction through Use (H10). It can be concluded that Use acts as a mediating variable (Partial Mediation) between Service Quality and User Satisfaction, meaning that if there is or is no Use, consumers will still feel satisfied with the Service Quality of the Blibli application.

CONCLUSION

Based on the study's results, System Quality does not affect Use, which means that it can be said that System Quality is not a factor consumers consider when using the Blibli application. While Information Quality positively affects Use, the higher the Information Quality provided to users, the higher the user activity (Use) on the Blibli application. Service Quality positively affects Use. This shows that the higher the Service Quality obtained by Blibli application users, the higher the user activity (Use) on the Blibli application.

System Quality has a positive influence on User Satisfaction. This shows that the higher the System Quality in the Blibli application, the more User Satisfaction will increase using the Blibli application. However, Information Quality does not influence User Satisfaction, which shows that Information Quality is not a variable that determines User Satisfaction when using the Blibli application. Meanwhile, Service Quality has a positive influence on User Satisfaction. This shows that the higher the System Quality in the Blibli application, the more User Satisfaction will increase using the Blibli application. Furthermore, Use has a positive effect on User Satisfaction, which, if Use is increased, will also increase users' satisfaction with the Blibli application.

System Quality does not have an indirect influence on User Satisfaction through Use. Use cannot mediate the System Quality variable. Meanwhile, Information Quality and Service Quality indirectly influence User Satisfaction through Use. If Information Quality and Service Quality are improved, it will increase Use and impact increasing User Satisfaction.

This research does not prove the direct influence of System Quality on Use and Information Quality on User Satisfaction in the Blibli application. The results of this study also state that Service Quality has the most influence in increasing user activity (Use) and User Satisfaction, so that this can be said that Service Quality in the Blibli application must be further developed and improved in the future in order further to increase user activity (Use) and User Satisfaction.

BIBLIOGRAPHY

Apriadi, D., & Saputra, A. Y. (2017). E-Commerce Berbasis Marketplace Dalam Upaya Mempersingkat Distribusi Penjualan Hasil Pertanian. JURNAL RESTI (Rekayasa Sistem Dan Teknologi Informasi), 1(2), 131–136.

Apsari, I. A. P., & Astika, I. B. P. (2020). Pengaruh Kualitas Informasi, Kualitas Sistem Informasi, dan Perceived Usefulness pada Kepuasan Pengguna SIMDA. E-Jurnal Akuntansi, 30(3), 611–623.

Armanto, I. D. (2018). Pengaruh Dimensi Kualitas Layanan Terhadap Kepuasan Pelanggan Indihome Triple Play. E-Jurnal Manajemen Unud, 7(3), 1282–1309.

Artasya, Z. S., & Nuri. (2022). Pengaruh E-Commerce pada Perekonomian Indonesia Saat Pandemi Covid-19. AMRI (Analisa Metode Rekayasa Informatika), 1(1), 27–31.

Aseng, A. C., & Pandeirot, L. B. (2022). Marketplaces Attractiveness among Generation Z during COVID-19 Pandemic. Cogito Smart Journal, 8(1), 81–91.

Ayuningtiyas, K., & Gunawan, H. (2018). Pengaruh Kepercayaan, Kemudahan Dan Kualitas Informasi Terhadap Keputusan Pembelian Daring Di Aplikasi Bukalapak Pada Mahasiswa Politeknik Negeri Batam. Journal of Applied Business Administration, 2(1), 152–165.

Cesariana, C., Juliansyah, F., & Fitriyani, R. (2022). Model Keputusan Pembelian Melalui Kepuasan Konsumen Pada Marketplace : Kualitas Produk Dan Kualitas Pelayanan ( Literature Review Manajemen Pemasaran). Jurnal Manajemen Pendidikan Dan Ilmu Sosial, 3(1), 211–224. https://doi.org/https://doi.org/10.38035/jmpis.v3i1

DataIndonesia.id. (2022). META: Prospek E-Commerce Indonesia Masih Positif pada 2022. DataIndonesia.Id.

DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Herlistyani, L., Winoto, Y., & Rohman, A. S. (2012). Pengaruh Kualitas Jasa Pelayanan Informasi Telkom Terhadap Loyalitas Pelanggan Telkom Speedy Kepada PT. Telekomunikasi Indonesia Tbk. EJurnal Mahasiswa Universitas Padjadjaran, 1(1), 1–14.

Hernita, S. J., Sidik, W., & Sanjaya, V. F. (2020). Pengaruh E-Service dan Kualitas Sistem terhadap Kepuasan Pengguna Sistem E-Learning dengan Moderasi Perceived Value. Jurnal Manajemen Bisnis, 2(2), 257–264. https://doi.org/10.30812/target.v2i2.1001

Hidayatullah, S., Khouroh, U., Windhyastiti, I., Gerry, P. R., & Waris, A. (2020). Implementasi Model Kesuksesan Sistem Informasi DeLone And McLean Terhadap Sistem Pembelajaran Berbasis Aplikasi Zoom Di Saat Pandemi Covid-19. Jurnal Teknologi Dan Manajemen Informatika, 6(1), 44–52.

iprice.co.id. (n.d.). Peta E‑Commerce Indonesia. Iprice.Co.Id.

Iskandar, D., & Nasution, M. I. B. (2019). Analisis Pengaruh Kepercayaan, Keamanan dan Kualitas Pelayanan Terhadap Keputusan Pembelian pada Online Shop Lazada (Studi Kasus Pada Mahasiswa/i FEB UMSU). Jurnal Kewirausahaan, 1(1), 128–137. https://doi.org/https://doi.org/10.30596/snk.v1i1.3590

Kasmi, & Candra, A. nurudian. (2017). Penerapan E-Commerce Berbasis Business To Consumers Untuk Meningkatan Penjualan Produk Makanan Ringan Khas Pringsewu. Jurnal Aktual STIE Trisna Negara, 15(2), 109–116.

Mangun Buana, I. B. G. M., & Wirawati, N. G. P. (2018). Pengaruh Kualitas Sistem Informasi, Kualitas Informasi, dan Perceived Usefulness Pada Kepuasan Pengguna Sistem Informasi Akuntansi. E-Jurnal Akuntansi, 22(1), 683–713. https://doi.org/10.24843/eja.2018.v22.i01.p26

Manik, A., Salamah, I., & Susanti, E. (2017). Pengaruh Metode Webqual 4.0 Terhadap Kepuasan Pengguna Website Politeknik Negeri Sriwijaya. Jurnal Elektro Dan Telekomunikasi Terapan.

Mediakonsumen.com. (n.d.). Beli HP di Blibli, tapi yang Datang Mainan. Mediakonsumen.Com.

Mofokeng, T. E. (2021). The impact of online shopping attributes on customer satisfaction and loyalty: Moderating effects of e-commerce experience. Cogent Business and Management, 8, 1–33. https://doi.org/10.1080/23311975.2021.1968206

Muiz, M., Rachma, N., & Slamet, A. R. (2019). Pengaruh Sales Promotion dan Kualitas Pelayanan Terhadap Minat Pembelian Ulang di Mediasi Variabel Kepuasan Konsumen (Survei pada Konsumen GrabBike Online di Kota Malang). Jurnal Riset Manajemen.

Natalia, J., & Br Ginting, D. (2018). Analisis Pengaruh Kelengkapan Fitur, Persepsi Kemudahan Penggunaan, Kualitas Informasi, Kualitas Sistem, Persepsi Manfaat terhadap Kepuasan Penggunaan serta Dampaknya terhadap Loyalitas Pengguna Aplikasi Viu. Media Informatika, 17(3).

Pane, D. N., Fikri, M. El, & Muharran, R. H. (2018). Pengaruh Harga Dan Kualitas Pelayanan Terhadap Kepuasan Pelanggan Pada Rumah Makan Sidempuan Medan. Jurnal Manajemen Tools, 9(1), 1–11.

Purwati, A. A., Mustafa, Z., & Deli, M. M. (2021). Management Information System in Evaluating BCA Mobile Banking Using DeLone and McLean Model. Journal of Applied Engineering and Technological Science (JAETS), 2(2), 70–77.

Rahmadani, F., Suardana, I. M., & Samudra, H. (2019). Pengaruh Kualitas Pelayanan, Produk, Harga Dan Lokasi Terhadap Loyalitas Pelanggan Dengan Kepuasan Pelanggan Sebagai Variabel Intervening Pada Ud. Eva Group Mataram. Jurnal Ilmiah, 16(1), 123–135.

Rakhmadian, M., Hidayatullah, S., & Respati, H. (2017). Analisis Kualitas Sistem Dan Kualitas Informasi Terhadap Kepuasan Pemakai Sistem Informasi Akademik Dosen. Seminar Nasional Sistem Informasi, 14, 665–675.

Romla, S., & Ratnawati, A. (2018). Keputusan Pembelian E-Commerce Melalui Kemudahan Penggunaan, Kualitas Informasi Dan Kualitas Interaksi Layanan Web. Jurnal Ekonomi Dan Bisnis, 19(1), 59–70.

Sigit, K. N., & Soliha, E. (2017). Kualitas Produk Dan Kualitas Layanan Terhadap Kepuasan Dan Loyalitas Nasabah. Jurnal Keuangan Dan Perbankan, 21(1), 157–168.

Sugiyono, D. (2013). Metode penelitian pendidikan pendekatan kuantitatif, kualitatif dan R&D.

Tribunnewswiki.com. (n.d.). Blibli. Tribunnewswiki.Com.

Wardoyo, W., & Andini, I. (2017). Faktor-Faktor Yang Berpengaruh Terhadap Keputusan Pembelian Secara Online Pada Mahasiswa Universitas Gunadarma. Jurnal Ekonomi Manajemen Sumber Daya, 19(1), 12–26.

Widiani, Y. N., & Abdullah. (2018). Kualitas Pelayanan E-Government Melalui Aplikasi E-Filing Kantor Pelayanan Pajak Pratama Bandung Cibeunying Terhadap Kepuasan Pengguna Aplikasi. Jurnal Riset Bisnis Dan Manajemen, 11(2), 88–96.

	Average Variance Extracted (AVE)
Information Quality	0.525
Service Quality	0.540
System Quality	0.509
Use	0.527
User Satisfaction	0.501

	Cronbach's Alpha	Composite Reliability
Information Quality	0.818	0.869
Service Quality	0.829	0.875
System Quality	0.761	0.838
Use	0.775	0.847
User Satisfaction	0.858	0.889

	Saturated Model	Estimated Model
SUMMER	0.083	0.083
d_ULS	3.171	3.171
d_G	1.089	1.089
Chi-Square	1118.459	1118.459
NFI	0.661	0.661