cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Advances
Contact Email
adshrjurnal@gmail.com
Phone
+6285174373232
Journal Mail Official
adshrjurnal@gmail.com
Editorial Address
Jl. Senopati No.113 Rt.1/Rw.2 Senayan Kebayoran Baru. Kota Jakarta Selatan, Jakarta Selatan, Provinsi DKI Jakarta, 12190
Location
Kota adm. jakarta selatan,
Dki jakarta
INDONESIA
Advances In Social Humanities Research
Published by Sahabat Publikasi
ISSN : 30323037     EISSN : 30315786     DOI : doi.org/10.46799/adv.v2i2.187
Core Subject : Humanities, Social, Engineering,
Humanities Engineering Law, Crime, Criminology & Criminal Justice Social Sciences
Advances In Social Humanities Research is a double blind peer-reviewed academic journal and open access to social and humanities fields. The journal is published monthly by Sahabat Publikasi Advances In Social Humanities Research provides a means for sustained discussion of relevant issues that fall within the focus and scopes of the journal which can be examined empirically. This journal publishes research articles covering social and humanities fields. Published articles are from critical and comprehensive research, studies or scientific studies on important and current issues or reviews of scientific books. This journal publishes research articles covering social and technology.
Arjuna Subject : Ilmu Sosial - Ilmu Sosial (Lain-Lain)
Articles 444 Documents
 41   42   43   44   45 
Strategies for Improving Loan Restructuring Success Based on Business Analytics and Machine Learning in Rural Bank (Case Study: PT BPR Jabar Perseroda) Aceng Rohmana; Cecep Taofiqurrochman; Samidi
Advances In Social Humanities Research Vol. 4 No. 9 (2026): Advances In Social Humanities Research
Publisher : Sahabat Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/adv.v4i9.629

Abstract

Credit restructuring remains essential to banking risk management because unsuccessful restructuring may lead to further deterioration in credit quality, particularly among rural banks with limited analytical capabilities. This study aimed to identify the factors associated with successful loan restructuring, develop a predictive model, and formulate data-driven strategies for PT BPR Jabar Perseroda. A quantitative business analytics approach was employed using the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. Historical data consisting of 1,200 loan restructuring observations from January to December 2025 were analyzed through descriptive, predictive, and prescriptive analytics using RapidMiner. Three classification algorithms—Random Forest, Gradient Boosted Tree, and Decision Stump—were evaluated based on accuracy, precision, recall, and F1-score. The findings showed that Random Forest achieved the best predictive performance, with an accuracy of 96.67%, precision of 98.65%, and recall of 96.05%. Initial collectibility status was the factor most strongly associated with restructuring success, followed by collateral type and the number of arrears, whereas the debt-to-income ratio and economic sector showed relatively weaker relationships. These findings supported the implementation of risk-based debtor segmentation, appropriate restructuring schemes, intensive post-restructuring monitoring, and the development of an early warning system. The study concluded that the integration of business analytics and machine learning could improve loan restructuring decision-making; however, predictive results should complement rather than replace professional judgment and prudent banking governance practices.
Business Analytics for Credit Risk Management in Rural Banks Using the CRISP-DM Methodology (Case Study: PT BPR Jabar Perseroda) Ayip Muhdiatullah; Samidi; Cecep Taofiqurrochman
Advances In Social Humanities Research Vol. 4 No. 9 (2026): Advances In Social Humanities Research
Publisher : Sahabat Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/adv.v4i9.630

Abstract

Credit risk remains a critical concern for rural banks because lending quality directly affects financial stability and institutional sustainability. Although banking databases contain valuable debtor information, credit assessments often continue to rely on administrative verification and subjective judgment. This study aimed to identify credit risk characteristics, compare the performance of Random Forest, Gradient Boosted Tree, and Random Tree algorithms, and formulate data-driven risk management strategies for PT BPR Jabar Perseroda. A quantitative descriptive research design was employed using the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, integrating descriptive, predictive, and prescriptive analytics. The sample consisted of 1,015 debtor records selected through stratified sampling from a population of 10,150 records. Model performance was evaluated using accuracy, precision, and recall metrics, while correlation analysis was conducted to identify variables associated with credit risk status. Payment delinquency history showed the strongest relationship with risk status (r = 0.653), whereas collateral demonstrated the weakest relationship (r = -0.047). The Random Forest algorithm achieved the best predictive performance, with 99.00% accuracy, 100.00% precision, and 97.83% recall. The findings indicated that repayment behavior provided more meaningful risk information than static administrative attributes. Therefore, integrating Random Forest-based predictions with the 5C credit assessment principles could strengthen objective credit evaluation, decision-support systems, early warning mechanisms, and proactive credit risk management.
Effect of Performing Loan, Intermediation Function, and Operational Efficiency on Banking Profitability (Case Study at PT Bank Pembangunan Daerah Jawa Barat & Banten, Tbk Period 2014–2024) Ade Muhammad Nur; Cecep Taofiqurrochman
Advances In Social Humanities Research Vol. 4 No. 9 (2026): Advances In Social Humanities Research
Publisher : Sahabat Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/adv.v4i9.631

Abstract

Banks’ profitability reflects their ability to perform financial intermediation, manage credit risk, and control operating costs. Bank bjb’s return on assets (ROA) declined during the 2014–2024 period, highlighting the need to identify its key financial determinants. This study aimed to examine the effects of non-performing loans (NPL), loan-to-deposit ratio (LDR), and operating expenses to operating income (BOPO) on return on assets (ROA). A quantitative descriptive and explanatory research design was employed using 44 quarterly observations derived from Bank bjb’s financial statements and annual reports, along with official publications from the Indonesia Stock Exchange and the Financial Services Authority. Saturated sampling was applied, and the data were analyzed using SPSS through descriptive statistics, classical assumption tests, multiple linear regression analysis, correlation analysis, coefficient of determination analysis, and hypothesis testing. The findings showed that NPL, LDR, and BOPO simultaneously had a significant effect on ROA (F = 5.186; p = 0.004). Partially, NPL had a significant negative effect on ROA (B = -0.155; p = 0.034), whereas LDR had a significant positive effect on ROA (B = 0.013; p = 0.030). BOPO had a negative but statistically insignificant effect on ROA (B = -0.011; p = 0.296). The model explained 22.6% of the variation in ROA. Therefore, profitability was strongly influenced by effective credit risk management and an optimal intermediation function, supported by continuous efficiency improvements and revenue diversification strategies.
Bridging the Agility Gap: A Strategic Framework for Commercial Banks to Enter the Un-Banked Lending Market Sintaully Anggia C; Jagat Prirayani
Advances In Social Humanities Research Vol. 4 No. 9 (2026): Advances In Social Humanities Research
Publisher : Sahabat Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/adv.v4i9.637

Abstract

Extending sustainable finance to Indonesia’s unbanked Micro, Small, and Medium Enterprise (MSME) sector presents a structural paradox. Traditional commercial banks possess a significant competitive advantage through access to low-cost capital, yet they are consistently disintermediated by fintech disruptors that offer faster services despite charging higher interest rates. This research investigates the root causes of this market displacement based on the theories of Information Asymmetry and Transaction Cost Economics (TCE). By integrating empirical data from a Principal Component Analysis (PCA) of MSME market demands and an Analytic Hierarchy Process (AHP) of banking executive priorities, this study identifies the specific areas where conventional banking models fail to meet market expectations. It develops a 12-cell Strategic Alignment Matrix that reveals a critical agility gap. To address this challenge, this paper proposes a paradigm shift toward an API-driven, B2B2C (Business-to-Business-to-Customer) Ecosystem Financing Model. This redesigned business process leverages open banking, smart contract automation, and closed-loop disbursement mechanisms to achieve fintech-level service speed. By systematically reducing operational costs through technology integration, banks can accommodate a realistic 4.5% Non-Performing Loan (NPL) rate while maintaining the risk tolerance required for sustainable and accelerated financial inclusion.

Page 45 of 45 | Total Record : 444

 41   42   43   44   45 

Filter by Year

2023 2026


Reset
Filter By Issues
All Issue Vol. 4 No. 9 (2026): Advances In Social Humanities Research Vol. 4 No. 8 (2026): Advances In Social Humanities Research Vol. 4 No. 7 (2026): Advances In Social Humanities Research Vol. 4 No. 6 (2026): Advances In Social Humanities Research Vol. 4 No. 5 (2026): Advances In Social Humanities Research Vol. 4 No. 4 (2026): Advances In Social Humanities Research Vol. 4 No. 3 (2026): Advances In Social Humanities Research Vol. 4 No. 2 (2026): Advances In Social Humanities Research Vol. 4 No. 1 (2026): Advances In Social Humanities Research Vol. 3 No. 12 (2025): Advances In Social Humanities Research Vol. 3 No. 11 (2025): Advances In Social Humanities Research Vol. 3 No. 10 (2025): Advances In Social Humanities Research Vol. 3 No. 9 (2025): Advances In Social Humanities Research Vol. 3 No. 8 (2025): Advances In Social Humanities Research Vol. 3 No. 7 (2025): Advances In Social Humanities Research Vol. 3 No. 6 (2025): Advances In Social Humanities Research Vol. 3 No. 5 (2025): Advances In Social Humanities Research Vol. 3 No. 4 (2025): Advances In Social Humanities Research Vol. 3 No. 3 (2025): Advances In Social Humanities Research Vol. 3 No. 2 (2025): Advances In Social Humanities Research Vol. 3 No. 1 (2025): Advances In Social Humanities Research Vol. 2 No. 12 (2024): Advances In Social Humanities Research Vol. 2 No. 11 (2024): Advances in Social Humanities Research Vol. 2 No. 10 (2024): Advances In Social Humanities Research Vol. 2 No. 9 (2024): Advances In Social Humanities Research Vol. 2 No. 8 (2024): Advances in Social Humanities Research Vol. 2 No. 7 (2024): Advances in Social Humanities Research Vol. 2 No. 6 (2024): Advances in Social Humanities Research Vol. 2 No. 5 (2024): Advances in Social Humanities Research Vol. 2 No. 4 (2024): Advances in Social Humanities Research Vol. 2 No. 3 (2024): Advances in Social Humanities Research Vol. 2 No. 2 (2024): Advances in Social Humanities Research Vol. 2 No. 1 (2024): Advances in Social Humanities Research Vol. 1 No. 12 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 11 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 10 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 9 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 8 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 7 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 6 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 5 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 4 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 3 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 2 (2023): ADVANCES in Social Humanities Research Vol. 1 No. 1 (2023): ADVANCES in Social Humanities Research More Issue