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All Journal Information System Analysis, Design and Development
Budi Al Amin
Information Systems Study Program, Surakarta Campus, Faculty of Engineering and Informatics, UBSI, Jakarta

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Hybrid DTW-ARIMA Model for Rice Price Forecasting: An Indonesian Case Study Maria Sunarti Ekowati Ekowati; Nurul Hidayat; Ahmad Fauzi; Kristyana Dananti; Budi Al Amin; Rina Oktiyani; Rousyati Rousyati; Puji Widodo
Information System Analysis, Design and Development Vol. 1 No. 4 (2026): October: Information System Analysis, Design and Development
Publisher : Asosiasi Pengelola Jurnal Informatika dan Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66472/isadd.v1i4.355

Abstract

Rice, as a strategic commodity in Indonesia, experiences significant fluctuations that affect economic stability and public welfare. This raises challenges in food policy planning, particularly in achieving accurate price forecasting. The research problem addressed is how to improve rice price forecasting accuracy using time series clustering capable of capturing complex interregional patterns. The study is limited to monthly rice price data over the past five years. To solve this problem, a hybrid model integrating Dynamic Time Warping (DTW) and Autoregressive Integrated Moving Average (ARIMA) is proposed. DTW measures similarity among time series patterns, while ARIMA constructs predictive models based on historical data. The objective is to produce more accurate and stable forecasts compared to single-method approaches. The urgency lies in its contribution to national food policy and food security. The novelty compared to previous studies is the integration of DTW-ARIMA within a time series clustering framework, rarely applied to food commodities in Indonesia. Experimental results indicate that the hybrid DTW-ARIMA model achieves lower mean absolute percentage error (MAPE) than conventional methods. The expected output is a predictive model that can be implemented as a data-driven decision support system for national food policy.
Co-Authors Ahmad Fauzi Kristyana Dananti Maria Sunarti Ekowati Ekowati Nurul Hidayat Puji Widodo Rina Oktiyani Rousyati Rousyati