Implementation of Least Square Method to Predict Crime in Indonesia Based on the Web

Nita Cahyani; Rahmat Irsyada; Diva Anggi

doi:10.47709/brilliance.v5i2.7424

Implementation of Least Square Method to Predict Crime in Indonesia Based on the Web

Authors

Nita Cahyani Universitas Padjadjaran, Indonesia
Rahmat Irsyada Politeknik Negeri Subang, Indonesia
Diva Anggi Universitas Nahdlatul Ulama Sunan Giri, Indonesia

DOI:

https://doi.org/10.47709/brilliance.v5i2.7424

Keywords:

Least Square, crime prediction, prediction accuracy, web

Abstract

This study was initiated by the need to apply the Least Square method to project the number of crimes in Indonesia using historical data from 2018 to 2022. Crime is a crucial issue in maintaining public security and supporting law enforcement, so accurate prediction results can assist the government in formulating public policies and optimizing resource use. The main problem of this study is how to apply the Least Square method to predict various categories of crimes in Indonesia, such as crimes against life, physical violence, morality, individual freedom, property rights with or without violence, and narcotics crimes. The purpose of this study is to develop a prediction model that can provide an accurate picture of future crime trends. The Least Square method was chosen because it can minimize prediction errors and process data with diverse variations, resulting in more stable and reliable estimates. The data used covers various types of crimes within the study period, with accuracy checked through the Mean Absolute Percentage Error (MAPE) value. The results show that the Least Square method is able to produce highly precise predictions with a MAPE value of 1.21%, thus proving effective in predicting crime rates in Indonesia with a very low error rate.

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Published

2025-12-29

How to Cite

Cahyani, N., Irsyada, R., & Anggi, D. (2025). Implementation of Least Square Method to Predict Crime in Indonesia Based on the Web. Brilliance: Research of Artificial Intelligence, 5(2), 1250–1257. https://doi.org/10.47709/brilliance.v5i2.7424