PREDICTION SYSTEM OF RICE CONSUMPTION NEEDS USING WEIGHTED MOVING AVERAGE METHOD

Renisa  Maulidifa; Puspa Miladin Nuraida Safitri A.; Ririen Kusumawati

doi:10.52436/1.jutif.2024.5.4.1905

Renisa Maulidifa Informatics Engineering, Science and Technology Faculty, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia
Puspa Miladin Nuraida Safitri A. Informatics Engineering, Science and Technology Faculty, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia
Ririen Kusumawati Informatics Engineering, Science and Technology Faculty, Universitas Islam Negeri Maulana Malik Ibrahim Malang, Indonesia

DOI: https://doi.org/10.52436/1.jutif.2024.5.4.1905

Keywords: Forecasting, Prediction System, Rice Consumption Needs, Weighted Moving Average

Abstract

Most of Indonesia's population works in the agricultural sector. The main agricultural commodity is paddy which will be processed into rice. Despite being the fourth largest rice producer in the world, Indonesia continues to import rice. This is due to the rice deficit, declining rice field harvest areas, and the high consumption and demand for rice in the country. Malang Regency is one of the regions in Indonesia that faces challenges in fulfilling rice needs due to the increasing population and decreasing agricultural land due to land conversion. Therefore, this research aims to predict rice demand to ensure the availability of sufficient supply. This research implements the Weighted Moving Average (WMA) method to find the most optimal period and weight with the smallest MAPE value. The results show that WMA using a 3-month period and weights 0.1, 0.1, 0.8 is the best. From the test results, the rice demand obtained MAPE of 7.15% with the prediction results reaching 20,552.25 tons and the planting area obtained MAPE of 22.96% with the prediction results reaching 3842.70 ha for the next period. Further analysis was conducted to determine the efficiency of the available planting area whether it can sufficient the needs of rice. The results show that the expected rice production from the available planting area in Malang Regency can still sufficient the rice needs of the population. This research has also successfully implemented the method on a website-based system to facilitate data processing and prediction process with faster and more accurate results.

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