Influence Analysisloan Information on Interest Rate in Peer to Peer Lending


  • Evi Maria Diponegoro University
  • P. Basuki Hadiprajitno Diponegoro University



Age, Gender, Education, Marital Status, Credit Limit, Term Of The Loan, Platform Age, P2P, Interest Rates, Funders


Technology has developed rapidly and affected every community's life. This condition was also supported by the occurrence of a pandemic in early 2020 which resulted in restrictions on mobility between individuals and other humans to reduce the spread of the virus which resulted in a crisis. One of the technological developments in the financial sector is loan products through the Peer to Peer platform. Namely transactions that use an online platform that functions as an intermediary that connects borrowers and lenders to carry out lending and borrowing transactions without meeting physically. P2P transaction mechanisms that are carried out directly between borrowers and investors provide risk directly to investors for the success of their funding through the P2P platform. Therefore, in conducting a direct analysis of the loans to be financed, investors must have adequate information so that they can make the best analysis for the financing they are doing. This mechanism allows for information asymmetry on the part of borrowers and investors.

The level of trust from lenders is an important factor that will influence their decision as investors to provide funds to borrowers. This confidence can be obtained, among other things, by studying the various available information. In addition, there is the phenomenon of an increase in borrowers and lenders in P2P transactions in Indonesia. It is necessary to pay attention to whether this decision affects interest rates for lending through P2P platforms.


Al Arif, MNR (2012). Fundamentals of Marketing for Islamic Financial Institutions. Bandung: Alphabet.

Arinda, N. (2015). Analysis of the Influence of Age, Number of Dependents in the Family, Business Experience, Business Turnover and Number of Loans on the Rate of Return on Credit by MSMEs. Case Study: People's Credit Bank (BPR) Mount Ringgit Malang. Student Scientific Journal of the Faculty of Economics and Business: Brawijaya University, 3(2), 1–12.

Asih, Y. (2007). Nursing diagnoses. Jakarta: EGC.

Bachmann, A., Becker, A., Buerckner, D., Hilker, M., Kock, F., Lehmann, M., Tiburtius, P., & Funk, B. (2011). Online peer-to-peer lending - A literature review. Journal of Internet Banking and Commerce, 16(2).

BAPPENAS. (2021). Learning Study of Handling COVID-19 Indonesia (1st ed.). National Development Planning Agency (BAPPENAS).

Chen, D. (2012). Production and Operations Management Journal. International Journal of Physical Distribution and Logistics Management and Transportation Journal, 17(2), 2–15.

Chen, D., Lai, F., & Lin, Z. (2014). A trust model for online peer-to-peer lending: a lender's perspective. Information Technology and Management, 15(4), 239–254.

Chen, DTV, Wang, YM, & Lee, WC (2016). Challenges confronting beginning researchers in conducting literature reviews. Studies in Continuing Education, 38(1), 47–60.

Galloway, I. (2009). Peer-to-Peer Lending and Community Development Finance. Community Development Investment Center Working Paper, 21(3), 20.

Gavurova, B., Dujcak, M., Kovac, V., & Kotásková, A. (2018). Determinants of successful loan application at peer-to-peer lending market. Economics and Sociology, 11(1), 85–99.

Greiner, ME, & Wang, H. (2010). Building consumer-to-consumer trust in e-finance marketplaces: An empirical analysis. International journal of electronic commerce. United States: IGI Global.

Hafeez, A., Gujjar, AA, & Noreen, Z. (2014). Demanding need of growing technologies in distance learning systems. Turkish Online Journal of Distance Education, 15(4), 170–180.

Judisseno, RK (2005). Tax and Business Strategy. Main Library Gramedia.

Cashmere. (2016). Financial Statement Analysis. Jakarta: Rajawali Press.

Ketut Edy Wirawan, I Wayan Bagia, GPAJS (2016). The Influence of Education Level and Work Experience on Employee Performance. Journal of DotCom Dynamics, 7(2), 121–130.

Kosila, & Septian. (2020). Application of the Assure Type Cooperative Learning Model in Improving Student Learning Outcomes. Journal of Educational Innovation, 1(6), 1139–1148.

Lestari, RW (2011). The Influence of Wages, Level of Education and Technology on Labor Productivity in the Soy Sauce Industry in Pati District, Pati Regency. in Thesis. Department of Development Economics.

Lewis, A. (2012). Basics of Business Law: Introduction to Business Law. Nusamedia.

Lin, M. (2009). Peer-to-Peer Lending : An Empirical Study Peer-to-Peer Lending : An Empirical Study. Americas Conference on Information Systems.

Mahendra, AD (2014). Analysis of the Influence of Education, Wages, Gender, Age and Work Experience on Labor Productivity. Diponegoro Journal of Economics.

McMillan, JH, & Schumacher, S. (1984). Research in education: A conceptual introduction. Little, Brown.

Mishkin, FS (2008). Economics of Money, Banking and Financial Markets. UPT Library STIE LAMAPPAPOLEONRO SOPPENG.

Muhammad, EN (2008). Analysis of the factors that affect the rate of return on credit by MSMEs (Case study of Kupedes Customers of PT. Bank Rakyat Indonesia, Tbk (Persero) Cigudeg Unit, Bogor Branch). Faculty of Economics and Management, 49.

Nawai, N. (2010). Determinants of Repayment Performance in Microcredit Programs : A Review of Literature. International Journal of Business and Social Science, 1(2), 152–161.

Nugroho, A. (2012). Factors Influencing Intellectual Capital Disclosure (ICD). Accounting Analysis Journal. Semarang State University, 1(1), 378–386.

Poerwadarminanta, WJ. (2003). Indonesian General Dictionary. Library Hall.

Rahmawati. (2012). Financial Accounting Theory. Yogyakarta: Graha Science.

Rita, M., & Kusumawati, R. (2011). The Effect of Socio-Demographic Variables and Financial Characteristics on Attitudes, Subjective Norms and Behavioral Controls Using Credit Cards (Study on Employees at SWCU Salatiga). Journal of Management and Finance, 9(2), 109–128.

Rosalinda, L., Latipun, & Nurhamida, Y. (2013). Who Have Higher Psychological Well-Being? a Comparison Between Early Married and Adulthood Married Women. Journal of Educational, Health and Community Psychology, 2(2), 83–95.

Sanusi, A. (2011). Business Research Methodology. Jakarta: Salemba Empat.

Sevim, N., Temizel, F., & Sayilir, Ö. (2012). The effects of financial literacy on the borrowing behavior of Turkish financial consumers. International Journal of Consumer Studies, 36(5), 573–579.

Sudjana, N. (1988). Educational Research and Assessment. Bandung: New Light.

Supramono, & Damayanti, TW (2010). Indonesian Taxation. Yogyakarta: Andi Offset.

Susanti, BM (2000). Research on Women from an Androcentric View to a Gender Perspective”. Journal of ISI Yogyakarta.

Triwibowo, D. (2009). Factors Affecting Return of Troubled Loans by Customers in the Agribusiness Trade Sector (Case on BPR Rama Ganda Bogor). Economics and Management.

Varma, P., Nijjer, S., Sood, K., Grima, S., & Rupeika-Apoga, R. (2022). Thematic Analysis of Financial Technology (Fintech) Influence on the Banking Industry. Risks, 10(10), 1–17.

Widayanthi, LI (2012). The Influence of the Characteristics of MSME Debtors on the Rate of Return on Pundi Bali Dwipa Credit (Case Study of Customers of PT. Bali Regional Development Bank, Singaraja Branch Office). Student Scientific Journal of the Faculty of Economics and Business, 1(2), 1–15.

Wirdiyanti, R., Yusgiantoro, I., Sugiarto, A., Harjanti, AD, Mambea, IY, Soekarno, S., & Damayanti, SM (2022). How does e-commerce adoption impact micro, small, and medium enterprises' performance and financial inclusion? Evidence from Indonesia. Electronic Commerce Research.

Yoko, B. (2016). Analysis of Islamic Agricultural Financing Demand for Rice Farming in Central Lampung Regency. Journal of Farming Business.