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All Journal International Journal of Research in Community Services International Journal of Quantitative Research and Modeling
Rizki Apriva Hidayana
Department of Mathematics, Faculty of Mathematics and Natural Sciences, Universitas Kebangsaan Republik Indonesia, Bandung, Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Physics Social Sciences Other

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Comparison of LSTM and ARIMA-GARCH Models in Predicting Stock Price Volatility of Islamic Banking in Indonesia Alim Jaizul Wahid; Rizki Apriva Hidayana; Nestia Lianingsih
International Journal of Quantitative Research and Modeling Vol. 7 No. 2 (2026): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v7i2.1327

Abstract

Stock price volatility is one of the most critical investment risk indicators, particularly in Islamic banking stocks that face the dual challenges of conventional capital market dynamics and compliance with Islamic principles. This study compares the predictive performance of two modeling approaches: Long Short-Term Memory (LSTM), a deep learning architecture based on Recurrent Neural Networks, and the classical econometric ARIMA-GARCH model, in predicting stock price volatility of four Islamic banking issuers in Indonesia, namely BRIS (Bank Syariah Indonesia), BSIM (Bank Sinarmas Syariah), PNBS (Bank Panin Dubai Syariah), and BTPNS (Bank BTPN Syariah), for the period 2019–2024. Daily closing price data was obtained from the Indonesia Stock Exchange (IDX). The ARIMA-GARCH model was built through the stages of identification, estimation, and Box-Jenkins diagnostic testing, while the LSTM model was optimized through hyperparameter tuning with a 60-day rolling window. Predictive performance was evaluated using Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The results show that the LSTM model consistently produces lower MAPE values than ARIMA-GARCH for all issuers studied, especially during periods of high volatility such as the COVID-19 pandemic (2020) and global interest rate instability (2022–2023). However, the ARIMA-GARCH model provides better interpretability and is more stable under calm market conditions. This research contributes to the literature on Sharia-based quantitative finance in Indonesia and provides practical implications for investors and risk managers.
Strengthening Household Organic Waste Management through Community-Based Composting Training: An Integrated Behavioral and Circular-Economy Evaluation in Sukamaju Village, Ciamis Regency, West Java, Indonesia Siti Hadiaty Yuningsih; Alim Jaizul Wahid; Rizki Apriva Hidayana
International Journal of Research in Community Services Vol. 7 No. 3 (2026): International Journal of Research in Community Service (IJRCS)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v7i3.1356

Abstract

Household organic waste remains the largest single component of Indonesia's national waste stream, yet community service programs that teach composting rarely evaluate anything beyond participant satisfaction or simple pre-post knowledge scores. This article reports a community service program conducted with 30 housewife participants (members of the Family Welfare Movement, PKK) in Sukamaju Village, Ciamis Regency, West Java, that combined hands-on aerobic composting training with a structured evaluation grounded in the Theory of Planned Behavior (TPB) and a simple circular-economy cost estimation. The program was carried out in four stages: a preparatory needs assessment, socialization, hands-on training in EM4-assisted aerobic bin composting, and a four-week mentoring and monitoring period. Knowledge and the four TPB constructs (attitude, subjective norm, perceived behavioral control, and intention) were measured before and after the program, household organic waste was weighed before and after mentoring, and compost maturity was judged with a simple temperature, color, odor, and estimated carbon-to-nitrogen (C/N) checklist suited to a non-laboratory setting.The results, presented here as a reporting template, show a marked increase in composting knowledge and in all four TPB constructs, a reduction in the volume of organic waste delivered to the temporary disposal point, compost that met basic maturity criteria, and an estimated saving on household plant-nutrition expenditure. By jointly tracking behavioral, technical, and economic indicators, the program offers an evaluation design that has not been used together in the composting-focused community service literature reviewed here, and it is offered as a low-cost, replicable template for similar programs elsewhere in Indonesia.
Co-Authors Alim Jaizul Wahid Alim Jaizul Wahid Nestia Lianingsih Yuningsih, Siti Hadiaty