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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan
Pelu, Shelma M
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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THE IMPACT OF BANK-SPECIFIC FACTORS ON NON-PERFORMING LOAN IN INDONESIA: EVIDENCE FROM ARDL MODEL APPROACH Sinay, Lexy Janzen; Latupeirissa, Sanlly J; Pelu, Shelma M; Tilukay, Meilin I
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 16 No 2 (2022): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.601 KB) | DOI: 10.30598/barekengvol16iss2pp675-686

Abstract

Non-performing Loan (NPL) is an indicator that is generally used to determine the ability of bank management to manage non-performing loans. This study aims to analyze the impact of bank-specific factors on NPL. The bank-specific factors are Capital Adequacy Ratio (CAR), Return on Assets (ROA), Operating Expenses on Operating Income (BOPO), and Loan to Deposit Ratio (LDR). The data used is monthly time series data, a case study on Commercial Banks in Indonesia from January 2015 to August 2020. The model used to analyze these problems is Autoregressive Distributed Lag (ARDL). The results obtained are ARDL(1,6,0,1,1) model is the best model. The model shows that bank-specific factors have a direct impact on NPL. Specifically, the ARDL bounds test offers the analysis results, which show that the ability of bank-specific factors to explain the NPL of commercial banks in Indonesia is 84%. At the same time, 16% are other factors outside the model. The analysis results show a long-run cointegration relationship between NPL and specific characteristics, CAR, ROA, and BOPO. Then, only CAR, BOPO, and LDR impact NPL in the short-run relationship. The equilibrium correction obtained is significant and confirms a long-run relationship. The equilibrium correction indicates a high velocity towards stability after a shock. It means that the performance of Commercial Banks in Indonesia is outstanding during the COVID-19 Pandemic because the ability to recover from shock is relatively faster
COMPARATIVE ANALYSIS OF TWO-STEP AND QUASI MAXIMUM LIKELIHOOD ESTIMATION IN THE DYNAMIC FACTOR MODEL FOR NOWCASTING GDP GROWTH IN INDONESIA Souisa, Gilbert Alvaro; Leiwakabessy, Reyner M.; Damayanti, Salma; Terim, Mohammad Zanuar F; Pelu, Shelma M
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 1 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss1pp655-664

Abstract

Economic activity data is needed quickly to make policy decisions, but this data suffers from publication delays. Gross Domestic Product (GDP) data is released within five weeks after the end of the quarter. An effort that can be made to provide such data is through nowcasting, which is forecasting in the current period using variables that have a higher frequency. This study aims at nowcasting GDP growth. The nowcasting method used is the Dynamic Factor Model (DFM) with Two Step (TS) and Quasi Maximum Likelihood (QML) estimation. The nowcasting results show that the DFM-TS model is better than the DFM-QML because it has a larger adjusted R-squared value and has the smallest RMSE value of 1.71035 compared to the DFM-QML value, which has an RMSE value of 1.71598.
Co-Authors Damayanti, Salma Latupeirissa, Sanlly J Leiwakabessy, Reyner M. Lexy Janzen Sinay, Lexy Janzen Meilin Imelda Tilukay Souisa, Gilbert Alvaro Terim, Mohammad Zanuar F