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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Parameter: Jurnal Matematika, Statistika dan Terapannya
Sopaheluwakan, Marsa
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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ANALYZING THE LEVEL OF CREDIT FAILURE USING THE AUTOREGRESSIVE DISTRIBUTED LAG TO MAINTAIN STABILITY OF COMMERCIAL BANKS IN MALUKU PROVINCE Lewaherilla, Norisca; Sinay, Lexy Janzen; Damamain, Ferina Lestari; Sopaheluwakan, Marsa
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp843-860

Abstract

Commercial banks are banks that carry out business activities conventionally and or based on sharia principles, which in their activities provide services in payment traffic. The health level of a commercial bank is the result of an assessment of the bank's condition based on risk and bank performance. Commercial Bank performance assessment can use the proxy of asset ownership, namely Return on Assets (ROA). While the risk assessment of commercial banks can use the credit risk proxy used is the Non-Performing Loan (NPL) ratio. The purpose of this study is to examine the Health Level of Commercial Banks in Maluku Province using ROA and NPL based on bank internal factors (bank specific) and macro and micro economic conditions in Maluku Province. The data used is quarterly time series data, namely in the first quarter of 2014 - first quarter of 2022. The method used is multivariate time series data analysis, namely the Autoregressive Distributed Lag (ARDL) model. The results obtained are the Health Level of Commercial Banks in Maluku Province in the first quarter of 2014 - first quarter of 2022 is classified as healthy and stable, even though the Maluku economy is experiencing the impact of the COVID-19 Pandemic. Internal (specific) bank factors are very dominant in influencing the performance and risk of Commercial Banks in Maluku Province compared to macro and micro economic factors. This means that the policies and performance of all parties related to Maluku's economic conditions need to be improved in maintaining the stability and soundness of commercial banks. In general, the performance of all parties in maintaining the health level of Commercial Banks in Maluku Province is very good, especially during the COVID-19 Pandemic.
ORDINAL PROBIT REGRESSION MODELING ON THE HUMAN DEVELOPMENT INDEX MALUKU AND NORTH MALUKU PROVINCES Embuai, Emanuel Marthen; Salhuteru, Rosalina; Sopaheluwakan, Marsa; Djami, Ronald J.
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 4 No 1 (2025): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv4i1pp73-80

Abstract

This study examines the factors influencing Human Development Index (HDI) in Maluku and North Maluku Provinces using ordinal probit regression. Secondary data are employed to identify key socio-economic variables affecting HDI levels. Model selection is based on the Akaike Information Criterion (AIC), Schwarz Bayesian Information Criterion (SBIC), and R² values, while the Likelihood Ratio (LR) test is used to evaluate the significance of parameters. The findings reveal that expected years of schooling (X₂) is the most significant factor in determining HDI categories. The model that includes only this variable yields the lowest AIC and SBIC values and shows a significant LR test result. Furthermore, the negative regression coefficient indicates that an increase in expected years of schooling raises the probability of a region achieving a higher HDI category. These results underscore the crucial role of education policies in promoting human development. Future research is encouraged to incorporate economic, health, and infrastructure variables to provide a more comprehensive understanding of the factors influencing HDI.
Co-Authors Damamain, Ferina Lestari Djami, Ronald J. Embuai, Emanuel Marthen Lewaherilla, Norisca Lexy Janzen Sinay, Lexy Janzen Rosalina Salhuteru