Prediction of Red Chili Prices at Musi Market Using  Android-Based Linear Regression Algorithm

Muhammad Syaiful Iskandar; Rita Wahyuni Arifin

doi:10.59934/jaiea.v4i3.1138

Authors

Muhammad Syaiful Iskandar Universitas Bina Insani, Indonesia
Rita Wahyuni Arifin Universitas Bina Insani, Indonesia

DOI:

https://doi.org/10.59934/jaiea.v4i3.1138

Keywords:

android, Linear Regression, Prediction, Red Chili

Abstract

The prices of nine essential goods (sembako) often experience fluctuations, which can affect people's purchasing power and economic stability. One commodity that frequently undergoes price changes is red bird's eye chili. One of the factors causing the instability of red chili pepper prices is extreme weather changes, such as heavy rainfall or droughts, which directly impact harvest yields and the availability of supplies in the market. This research aims to predict the price of red bird's eye chili in Musi Market using the Linear Regression algorithm. Furthermore, the study also develops an Android-based application to provide users with real-time and predictive price information for red bird's eye chili. This predictive information will be displayed through the Android-based application, making it easily accessible to users and helping them obtain price data quickly and accurately. This system integrates price data, weather, and seasonal events to predict price fluctuations. Evaluation results show that Linear Regression is the best model, with an MAE of 14,380.53 and an R² of 0.686, indicating the model's ability to explain 68.6% of the data variation, providing an efficient solution for price monitoring at Pasar Musi.

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