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Abstract. The background of this research is the rampant competition in the bus transportation business which is marked by the increasing number of bus transportation companies in several locations that are even close to each other, which results in customers being faced with a lot of choices. One of the famous transportation services in Blitar City is the Rosalia Indah bus. Ticket sales from PO Rosalia Indah are higher every day compared to other POs, such as PO Harapan Jaya. Therefore, transportation service companies compete with each other to attract consumers. This study aims to determine the effect of tariffs, accessibility, facilities and infrastructure on user interest. The population in this study were Rosalia Indah bus users, the sample of this study was 100 respondents. Sampling technique is nonprobability sampling  with the type of sampling, namely incidental sampling. The data analysis used in this study is descriptive analysis and quantitative analysis, the data were analyzed using multiple linear regression analysis with the help of  (software) Statistical Package For Social Science (SPSS) version 25. The results of the study by partially testing the t-test hypothesis showed that Rates, Accessibility, Facilities and Infrastructure have a positive and significant effect on increasing user interest.  Based on the research results, the regression equation model is Y = 1.821 + 0.424 + 0.263 + 0.178 + . the tariff variable with a regression coefficient of 0.424, the accessibility variable with a coefficient of 0.263, the variable of facilities and infrastructure with a regression coefficient of 0.178. From the regression equation, the tariff variable has the most dominant effect on increasing the number of users with an R2(R Square) test of 0.626 or 62.6% which means that user interest is influenced by tariff variables, accessibility, facilities and infrastructure, and other factors that influence Rosalia Indah bus user interest is 37.4% or 0.374.

This study aims to determine the effect of independent variables (Foreign Exchange Reserves, Foreign Direct Investment, Inflation Rate, and Interest Rate) on the dependent variable (Import Value) in Indonesia for the last five years. This study uses quantitative analysis with descriptive methods used to obtain empirical evidence of the effect of Foreign Exchange Reserves (X1), Foreign Direct Investment (X2), Inflation Rate (X3), Interest Rate (X4), and Import Value (Y). Panel data regression analysis was used with a significance level of 5%. The results showed that the variables of Foreign Exchange Reserves, Foreign Direct Investment, Inflation Rate, and Interest Rate had no significant effect on Import Value in Indonesia. Foreign Exchange Reserves, Foreign Direct Investment, Inflation Rate, and Interest Rate simultaneously have a significant effect on Import Value in Indonesia.

This research is motivated by a phenomenon. As this phenomenon and previous studies present different research gaps and have been conducted for quite some time, further studies are needed to test the consistency of the results of previous studies and also to revisit existing research gaps. is needed.The focus of my research in writing this journal is how monetary policy has a material impact on Indonesia's Islamic commercial bank lending products and how the inflation rate has a material impact on Indonesia's Islamic commercial bank lending products and the magnitude of the impact of monetary policy. Monetary Policy Politics and inflation rates in the Indonesian economy. The data used in this study are secondary data. Secondary data is research data obtained indirectly (acquired and recorded by others) through an intermediary medium. Secondary data for this study were obtained from the Indonesian Stock Exchange (IDX) Islamic Commercial Bank Listed Companies Annual Reports, OJK Shariah Bank Statistical Financial Statements (SPS), and financial statements issued by Bank Indonesia. The analysis method used in this study is multiple regression analysis. The purpose of this regression analysis is to obtain a comprehensive picture of the relationship between the independent and dependent variables of each company's performance. Before running multiple linear tests, this method requires a classical assumption test for best results. SPSS software version 23 is used to process the data.