The aim of this paper is to examine one of the most crucial factors in the “Technology Acceptance Model” proposed by Davis (perceived usefulness) in moderating the “DeLone and McLean” success model in the context of educational portal in Higher Education. Questionnaires were distributed online to 200 respondents and deserved to be analyzed. The respondents were regular students at the University of Bengkulu. Data analysis used Smart-PLS version 3.2.9. The research findings indicated an influence of “system quality, information quality, and service quality partially on user satisfaction” of the educational portal information systems. The result shows that perceived usefulness can strengthen the relationship between system quality, information quality, and service quality to the satisfaction of customer. This research contributes to the development of perceived usefulness variable as a moderating variable affecting the quality of a system, quality of information, and quality of service partially on user satisfaction and finding strategies needed by the University of Bengkulu effective and efficient information system.
This research is conducted to detect the health level of Bank listed in indonesian stock exchange using RGEC period 2014-2015. RGEC is the aspect that most influence on the financial condition of banks, which also affect the health of banks. By using the NPL, LDR, IRR, NPM, ROA, NIM and CAR. Population in this study are all companies of Bank listed on stock exchange totaling 42 companies. Based on sampling criteria finally obtained sample is 21 companies of bank publish financial reports continuously in the period 2014-2015. The results obtained that the NPL from overall of bank sampel in 2014-2015 categorized is healthy. The results obtained that the LDR from sampel there’s counted 6 healthy categorized company enough. Companies categorized as unhealthy counted 6 bank. The results obtained from IRR variable there’s counted 2 healthy expressed bank and there’s counted 9 bank categorized as unhealthy. NPM variable obtained get result counted 8 bank categorized as unhealthy, there’s counted 7 bank categorized very healthy and 2 bank categorized healthy. ROA variable there’s counted 2 bank categorized as unhealthy and 3 bank categorized very healthy. NIM variable there’s counted 4 bank categorized healthy and 17 bank categorized as very healthy. CAR variable there’s counted 1 company categorized healthy and 20 company categorized very healthy.
This study examines the effect of financial knowledge, financial behavior, and financial inclusion on financial well-being. The sampling method used in this study was purposive sampling with a total sample size of 509. We collected data using an online questionnaire distributed via social media in Sumatra, Indonesia. Data were examined using the Partial Least Square (PLS) technique. The results showed that financial knowledge, financial behavior, and financial inclusion had a positive effect on financial well-being. We also found that financial behavior and financial inclusion mediate the influence of financial knowledge on financial well-being.
This study aims to analyze the effect of individual dimensions of financial literacy on financial inclusion. This research design is a survey with an online questionnaire. The object of this research is the people in rural Bengkulu. The respondent in this study was 503 respondents. This study used convenience sampling with screening. This study reveals that knowledge, attitudes, and behaviors influence financial inclusion in rural Bengkulu. While skills do not affect financial inclusion in rural Bengkulu. This research also found that attitude is the variable that has the greatest influence on financial inclusion.
The purpose of this research was to determine whether there are significant differences in the (LDR, NPL, ROA, ROE, ROA, NIM and PDN) between government bank compared to private banks in Indonesia Stock Exchange (IDX) the period of 2008-2012. Method of sample selection was done by purposive sampling, the samples obtained from government banks such as BNI, BRI, BTN, and Mandiri bank, while from private banks such as BCA, BII, CIMB Niaga Bank and Panin Bank. Data analysis methods is hypothesis testing using two different test mean (pair sample t test). The results showed that the financial performance of the ratio for LDR, NPL, ROA, ROE, ROA and PDN there is no significant difference between the government banks and private banks. While the financial performance of the NIM ratio there are significant differences between the government banks and private banks.
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