ANALYSIS OF THE INFLUENCE OF CONSUMER BEHAVIOR ON THE DECISION OF APPLYING MULTI-PURPOSE LOANS IN FINANCIAL TECHNOLOGY

: The purpose of this study is to analyze the effect of consumer behavior on the decision to submit a multipurpose loan for funds in the science and technology sector. The sample used in this study was 80 respondents. By using the accidental sampling method. The data used are primary data using questionnaires. The analysis technique used is multiple linear regression analysis. Based on the results of the analysis, it can be seen that there is a significant influence of cultural and social factors on the decision to submit a multipurpose fund loan to the science and technology department. While there is no significant effect of personal factors on the decision to apply for a multipurpose fund loan in fintek, while the adjusted R Square value obtained is 0.525. This shows that the amount of cultural, social and personal contribution simultaneously influences the decision to apply for a multipurpose fund loan in fintek is 52.5%, while the remaining 47.5% is influenced by factors outside cultural, social and personal.

According to data from the OJK, until January 2019, the distribution of fintech loans reached IDR 25.92 trillion. The number of distributions increased by 14.36% from the beginning of 2018 which was recorded at Rp. 22.67 trillion. This figure is still relatively small, because based on OJK research in 2016, there is a funding gap in Indonesia of Rp. 989 trillion per year. The gap is due to the need for funding of Rp. 1,649 trillion cannot be met by financial institutions which only have a total flow of funds of Rp. 660 trillion. Therefore, the fintech industry in Indonesia has enormous potential to develop again in the future considering that there are still many funding needs needed by the community that have not been met. To date, based on OJK statistical data as of February 1, 2019, there are 99 fintech lending companies that have been registered and licensed at the Financial Services Authority (OJK) and 54 payment system fintechs registered with Bank Indonesia (BI). There are still several more companies that are still in the licensing process, so the number of these fintech companies will also continue to grow.
Researcher on fintech was once conducted by Amalia (2018) who said that interest in using the Paytren application as a payment transaction tool was influenced by Perceived Usefulness and Attitude. Perceived Ease of Use (PEOU) has a positive and significant effect on the variable Perceived Benefits (PU), this indicates that the higher the public perception of the ease of application of Paytren, the higher the public perception of the usefulness of Paytren. positive and significant on the PU variable, this indicates that the higher the subjective norm for the application of Paytren, the higher the public perception of the usefulness of Paytren, it can be said that subjective norms, both interpersonal and environmental influences, or the opinions of certain figures will be able to form perceptions of the benefits of a program. product. Perception of Ease of Use (PEOU) has a significant positive effect on the consumer attitude variable in using Paytren (Attitude). Similarly, Perception of Benefits (PU) has a positive and significant effect on Attitude. Kurniawan et al. (2018), said that most of the respondents were very satisfied by 40%, and 40% felt very dissatisfied with the timeliness factor. This can be used as a recommendation for payment gateway service providers and the government as a regulator.
With the increasing number of fintech companies, it makes people interested in making loans to fintech companies. The decision to borrow becomes a very important thing because it can determine a person in achieving certain goals. Sumarwan (2014) define a decision as choosing an action from two or more possibilities. The decision to take credit is an act of choosing credit from two or more credit possibilities. This decision to take credit is the problem in this study because the number of customers who decide to take credit will have a significant influence on the income of fintech companies. If it is assumed that credit distribution is going well (smooth), the more customers who decide to take credit, the income of the fintech company will also increase. On the other hand, if credit distribution activities are not managed properly, it will certainly result in non-performing loans. In an effort to prevent, fintech companies need to know and understand customer behavior, especially those related to decisions in taking credit because it will be useful for determining strategies, policies and efforts to improve fintech companies in the future. Based on the above phenomenon, the purpose of this study is to determine consumer behavior towards the decision to apply for a multipurpose loan in fintech.
follow the choices that are considered right and reasonable by the community. Someone who decides to take a loan will make considerations based on the culture that develops in the community where he lives. The stronger the culture held by a person, the more difficult his decisions to change. In a sense, the greater the influence of culture on a person, the greater the decision to take a loan. H1 = Cultural factors can have a positive effect on the decision to apply for a multipurpose loan in fintech.

Social Factors Against Loan Application Decisions
Social interactions between people and other people can also determine a person's decisions. Factors such as family, reference group, as well as the role and status in the social factor component are included in a person's consideration in taking out a loan. The higher the intensity of a person's interaction with other people, it will encourage the borrower to make a decision. The greater the influence of the family and reference group, the higher the decision to take out a loan. So, if someone has good social interaction, then he will be motivated to decide to take a loan, so that social factors have a positive effect on the decision to take a loan. Conversely, if a person rarely engages in social interaction, the desire to take out a loan will also be low. H2 = Social factors can have a positive effect on the decision to apply for a multipurpose loan in fintech.

Personal Factors Against Loan Application Decisions
Personality is a collection of emotions, thoughts, and behaviors that are combined and consistent. If a behavior is carried out continuously to form values, a person will form a lifestyle, a self-concept that reflects a person is different or unique from others. With this, personality turns out to have an effect on a person's consideration in making a choice, including deciding to take credit. A person's personality is reflected in indicators of age and life cycle stage, occupation, economic situation, lifestyle, personality, and self-concept. It can be said that if a person is married, has a lower middle income and has a consumptive lifestyle, the more likely he is to take out a loan. However, if a person has the opposite condition, then it is unlikely that he will decide to take credit. H3 = Personal factors can have a positive effect on the decision to apply for a multipurpose loan in fintech.

Research Method
The type of research used in this research is explanatory (explanation) with a quantitative approach. The location of this research was carried out in Surabaya. The population in this study is an infinite population, namely the size of the population that is already so large that it cannot be counted (uncountable). Sampling according to Malhotra (2006) is mentioned in his marketing research book at least four or five times the number of question items. The sample in this study was 80 respondents (16 items question X5), with a sampling technique using simple random sampling, which is a sampling technique from members of the population that is carried out randomly without regard to the existing strata in the population Sugiyono (2017). The data taken in the study came from primary data, namely data obtained directly from respondents through questionnaires. The data testing technique used is multiple linear regression using the SPSS 21.00 program for windows.

Results and Discussion
In this study, the process of distributing questionnaires was addressed to 80 respondents, namely fintech customers in Surabaya. With the criteria that the customer has borrowed at least one loan. Respondents in this study consisted of 42 men and 38 women. Age 21 -30 years as many as 11 respondents, 31 -40 years as many as 38 respondents, 41 -50 years as many as 29, and > 50 years as many as 2 respondents. SMA/SMU education as many as 32 respondents, 41 respondents for S1, 7 respondents for S2, and 0 respondents for S3.

Validity Test
All question items (indicators) on all research variables produce corrected item total correlation values whose value is greater than r table so that it can be said that the question items that measure each research variable can be declared valid.

Reliability Test
It is known that the value of Cronbach's alpha in each research variable is greater than 0.60, thus the question items that measure the research variables are declared to meet the reliability or reliability requirements of the questionnaire.

Normality Test
The results of the normality test show that the residuals are normally distributed, this is evidenced by the shape of the pliers being symmetrical, not skewed to the right or to the left. Hypothesis test.

Multicollinearity Test
The test results show that all variables used as predictors of the regression model show a fairly small VIF value, where all of them are below 10 and the tolerance value is more than 0.1. This means that the independent variables used in the study do not show any symptoms of multicollinearity, which means that all of these variables can be used as mutually independent variables.

Heteroscedasticity Test
The results of the heteroscedasticity test show that there is no clear pattern from these points. This shows that the regression model does not have symptoms of heteroscedasticity, which means that there is no significant disturbance in this regression model.

F Test (Model Accuracy Test)
Based on the results of the regression analysis in the table above, the significant value obtained is 0.000 <0.05, so Ho is rejected, meaning that the model used to examine the influence of culture, social and personal on the decision to apply for a multipurpose loan in fintech can be said to be right.

Coefficient of Determination
The results of the regression analysis in the table above show that the adjusted R Square value obtained is 0.525. This shows that the amount of cultural, social and personal contributions simultaneously influences the decision to apply for a multipurpose loan at fintech is 52.5%, while the remaining 47.5% is influenced by factors outside of culture, social and personal.

Cultural Factors Against Loan Application Decisions
Culture has a significant effect on the decision to apply for a multipurpose loan in fintech. Culture has a significant effect on the decision to apply for a multipurpose loan at fintech, because the customer only considers or decides based on the individual concerned and certain people. When a customer decides to take a loan, the decision arises within himself or can also be influenced by certain people, not influenced by the habits of society in general. Moreover, fintech loans are only given to online customers. Which only relies on online data. Customers who do not have social networks cannot make these online fintech loans. In addition, it is suspected that this is because the culture of taking loans online is generally considered unnatural for some people. Therefore, cultural factors influence the decision to apply for a multipurpose loan at fintech. The results of this study are in line with Frangos et al. (2012), Ismunandar & Lestari (2019), Hudani (2020), who said that cultural factors can influence customers to borrow loans from banks.

Social Factors Against Loan Application Decisions
Social has a significant effect on the decision to apply for a multipurpose loan at fintech, because the decision to apply for a multipurpose loan at fintech in taking a loan is influenced by social factors. In other words, reference groups, family, roles and status influence customers in taking loans. One of the reasons is that in general, customers decide to take loans because they are based on meeting family needs. As is known, someone who is married has increasingly complex needs, so additional income is needed so that family needs can be met. Therefore, social factors influence customer decisions in taking loans to fintech. The results of this study are in line with Lu et al. (2012), Pratiwi & Mandala (2015), Hafidz (2018) who said that social factors greatly influence a customer's decision to borrow a loan at a bank.

Personal Factors Against Loan Application Decisions
Personal has no significant effect on the decision to apply for a multipurpose loan at fintech, because the decision to apply for a multipurpose loan at fintech in taking credit is influenced by personal factors. In other words, age and stage of life cycle, occupation and economic circumstances, personality and self-concept, lifestyle and values influence the decision of members to take out a loan. One of the reasons customers take loans in general is that they do not have additional income to deal with increasing age and life cycle stages. Customers only rely on income as employees. With age and stage of the life cycle, their needs will become more complex so they need to require additional income. However, if the customer can manage the money they have well, then the customer can be said not to make a loan. So that it can be said that personal factors do not affect customer decisions in taking loans to fintech. However, this study is not in line with Azam et al. (2012), Santoso & Purwanti (2013), Irwan (2019), who said that personal factors can influence customers to borrow loans from banks.

Conclusion
Based on the results of research on the analysis of the influence of consumer behavior on customer decisions in taking loans at fintech, the following results are obtained: a. Cultural factors influence the decision to apply for a multipurpose loan at fintech b. Social factors influence customer decisions in taking loans from fintech c. Personal factors do not affect customer decisions in taking loans from fintech