Implementation of ARIMA with Min-Max Normalization for predicting the Price and Production Quantity of Red Chili Peppers in North Sumatra Province considering Rainfall and Sunlight Duration Factors
Received: 27 December 2024 | Revised: 25 January 2025 | Accepted: 11 February 2025 | Online: 3 April 2025
Corresponding author: Ifan Prihandi
Abstract
Red chili peppers are a vital agricultural commodity in the North Sumatra province, playing a significant role in Indonesia's economy. Fluctuations in chili prices affect farmers, consumers, and overall economic stability. This study leverages time series forecasting using the ARIMA model to predict red chili pepper prices and production, incorporating weather factors such as rainfall and sunlight duration. The dataset spans March 2021 to December 2023 and includes historical records of chili prices, production levels, and weather conditions. The analysis reveals a strong correlation between price fluctuations and production trends: Prices tend to rise when production declines and fall when yields increase. Additionally, production is influenced by weather conditions, where excessive rainfall damages crops and reduces yields, while balanced rainfall and sunlight duration support optimal growth. The ARIMA model demonstrates its effectiveness in capturing these patterns, providing actionable insights for farmers and policymakers to predict price changes and optimize production strategies. By integrating data-driven forecasting with weather analysis, this research contributes to more adaptive and informed decision-making in the agricultural sector.
Keywords:
time series prediction, machine learning, ARIMA, agricultural analytics, climate impact, data-driven decision-makingDownloads
References
H. Rana, M. U. Farooq, A. K. Kazi, M. A. Baig, and M. A. Akhtar, "Prediction of Agricultural Commodity Prices using Big Data Framework," Engineering, Technology & Applied Science Research, vol. 14, no. 1, pp. 12652–12658, Feb. 2024.
C. S. e Souza, S. A. Duah, A. Neményi, Z. Pék, and L. Helyes, "The impact of cultivar and irrigation on yield, leaf surface temperature and SPAD readings of chili pepper," Acta Agraria Debreceniensis, no. 2, pp. 103–108, Dec. 2020.
A. Lukas et al., "Fresh Chili Agribusiness: Opportunities and Problems in Indonesia," in Agricultural Economics and Agri-Food Business, IntechOpen, 2023.
R. Rahma, R. F. Sari, and S. Dur, "Multivariate Singular Spectrum Analysis Model in Forecasting Red Chili and Cayenne Pepper Prices," Al Ulum: Jurnal Sains Dan Teknologi, vol. 10, no. 1, pp. 14–22, Apr. 2024.
E. Mpaata, N. Koskei, and E. Saina, "Financial Literacy and Saving Behavior Among Micro and Small Enterprise Owners in Kampala, Uganda: the Moderating Role of Social Influence," Journal of Economics, Finance and Accounting Studies, vol. 2, no. 1, pp. 22–34, Jun. 2020.
D. Devianto, E. Wahyuni, M. Maiyastri, and M. Yollanda, "The seasonal model of chili price movement with the effect of long memory and exogenous variables for improving time series model accuracy," Frontiers in Applied Mathematics and Statistics, vol. 10, Jul. 2024.
H. Sasai, "The Effects of Rainfall Distribution and Intensity on Crop Production," Namimbia Economist. https://economist.com.na/57635/columns/the-effects-of-rainfall-distribution-and-intensity-on-crop-production/.
M. Kotz, A. Levermann, and L. Wenz, "The effect of rainfall changes on economic production," Nature, vol. 601, no. 7892, pp. 223–227, Jan. 2022.
S. M. Khasanah, M. Maksum, and E. Suwondo, "Trend Analysis of Red Chili Price-Formation Models," agriTECH, vol. 40, no. 1, pp. 57–63, Mar. 2020.
D. Novita, T. Supriana, Sirozujilam, and S. N. Lubis, "Strategy of Development of Sustainable Red Chili Agribusiness Areas in North Sumatra Province," Journal of Ecohumanism, vol. 3, no. 7, pp. 4983–4997, Nov. 2024.
S. Mardiyati and M. Natsir, "Fluctuations and trends in the prices of red chilies and cayenne peppers in the traditional markets of Makassar City," IOP Conference Series: Earth and Environmental Science, vol. 1302, no. 1, Oct. 2024, Art. no. 012124.
Y. D. S. Saragih, R. Pambudy, and T. G. Dewi, "Dampak Luas Lahan terhadap Kinerja Usahatani Cabai Merah (Kasus Provinsi Sumatera Utara)," JIA (Jurnal Ilmiah Agribisnis) : Jurnal Agribisnis dan Ilmu Sosial Ekonomi Pertanian, vol. 8, no. 6, pp. 486–496, Dec. 2023.
T. Surbakti, T. Supriana, and I. Iskandarini, "Asymmetric Price Transmission of Red Chili Market in North Sumatra Province, Indonesia," Agro Bali : Agricultural Journal, vol. 5, no. 1, pp. 156–165, Feb. 2022.
Y. Zhang, H. Yang, H. Cui, and Q. Chen, "Comparison of the Ability of ARIMA, WNN and SVM Models for Drought Forecasting in the Sanjiang Plain, China," Natural Resources Research, vol. 29, no. 2, pp. 1447–1464, Apr. 2020.
"Comparison of ARIMA, ANN and Hybrid ARIMA-ANN Models for Time Series Forecasting," Information Sciences Letters, vol. 12, no. 2, pp. 1003–1016, Feb. 2023.
L. M. Hamzah, S. U. Nabilah, E. Russel, M. Usman, E. Virginia, and Wamiliana, "Dynamic Modelling and Forecasting of Data Export of Agricultural Commodity by Vector Autoregressive Model," Journal of Southwest Jiaotong University, vol. 55, no. 3, 2020, Art. no. 41.
N. Nainggolan, H. A. H. Komalig, and T. Manurung, "Vector autoregressive time series model in predicting food prices in Manado city," AIP Conference Proceedings, vol. 2694, no. 1, Apr. 2023, Art. no. 050005.
Y. Peng, "Construction and Evaluation of Credit Risk Early Warning Indicator System of Internet Financial Enterprises Based On AI and Knowledge Graph Theory," Procedia Computer Science, vol. 243, pp. 918–927, 2024.
Y. S. Kim, M. K. Kim, N. Fu, J. Liu, J. Wang, and J. Srebric, "Investigating the impact of data normalization methods on predicting electricity consumption in a building using different artificial neural network models," Sustainable Cities and Society, vol. 118, Jan. 2025, Art. no. 105570.
H. Henderi, T. Wahyuningsih, and E. Rahwanto, "Comparison of Min-Max normalization and Z-Score Normalization in the K-nearest neighbor (kNN) Algorithm to Test the Accuracy of Types of Breast Cancer," International Journal of Informatics and Information Systems, vol. 4, no. 1, pp. 13–20, Mar. 2021.
I. D. Aulia and I. Pratama, "Analysis of Forecasting Methods on Rice Price Data at Milling Level According to Quality," Edu Komputika Journal, vol. 11, no. 1, pp. 1–10, Aug. 2024.
R. Konda, V. S. S. Kumar, R. C. Bagadi, and N. S. Kumar, "A Novel Ensemble Linear Regression Scheme Based on Incorporation of the Linear Model Strength Contributed by Each Data Point Co-ordinate Using a Special Weighted Error Metrics Ensembling Scheme Spanning Error Metric Types and Considered Linear Regression Models – An Example of Construction Accident (Fatal Falls) Prediction," Asian Research Journal of Current Science, pp. 84–106, Apr. 2023.
Y. Ledmaoui, A. El Maghraoui, M. El Aroussi, R. Saadane, A. Chebak, and A. Chehri, "Forecasting solar energy production: A comparative study of machine learning algorithms," Energy Reports, vol. 10, pp. 1004–1012, Nov. 2023.
D. F. McCaffrey, "Volume 14: Quantitative Research and Educational Measurement," in International Encyclopedia of Education, 4th ed., Elsevier, 2023, pp. xix–xxiv.
S. K. Filipova-Petrakieva and V. Dochev, "Short-Term Forecasting of Hourly Electricity Power Demand: Reggresion and Cluster Methods for Short-Term Prognosis," Engineering, Technology & Applied Science Research, vol. 12, no. 2, pp. 8374–8381, Apr. 2022.
R. Ospina, J. A. M. Gondim, V. Leiva, and C. Castro, "An Overview of Forecast Analysis with ARIMA Models during the COVID-19 Pandemic: Methodology and Case Study in Brazil," Mathematics, vol. 11, no. 14, Jul. 2023, Art. no. 3069.
C. Aliferis and G. Simon, "Overfitting, Underfitting and General Model Overconfidence and Under-Performance Pitfalls and Best Practices in Machine Learning and AI," in Artificial Intelligence and Machine Learning in Health Care and Medical Sciences: Best Practices and Pitfalls, G. J. Simon and C. Aliferis, Eds. Springer International Publishing, 2024, pp. 477–524.
F. Alshammari, N. Aljojo, A. Tashkandi, A. Alghoson, A. Banjar, and N. K. E. Abbadi, "A Hybrid Time-Series Prediction of the Greater Riyadh’s Metropolitan Area Expansion," Engineering, Technology & Applied Science Research, vol. 13, no. 5, pp. 11890–11897, Oct. 2023.
N. E. Samosir, N. Siagian, R. R. Nst, S. Frisnoiry, and K. Kunci, "The Effect of Demand And Supply On The Economy," Jurnal Ilmiah Multi Disiplin Indonesia, vol. 2, no. 8, pp. 1799–1805, Jun. 2023.
C. D. Lewis, Industrial and Business Forecasting Methods: A Practical Guide to Exponential Smoothing and Curve Fitting. Butterworth Scientific, 1982.
Downloads
How to Cite
License
Copyright (c) 2025 Ifan Prihandi, Sutarto Wijono, Irwan Sembiring, Evi Maria
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain the copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after its publication in ETASR with an acknowledgement of its initial publication in this journal.
