Big Data Analysis for Tin Production Prediction in Bangka Belitung Using Machine Learning Models

Abstract

 Tin mining is the main economic sector in Bangka Belitung. However, fluctuations in tin production due to environmental, technological, and policy factors pose challenges in planning and managing resources. This study aims to analyze tin production data using big data techniques and machine learning models to improve the accuracy of tin production predictions. The methods used include data collection from various sources, data processing, and the implementation of machine learning models such as linear regression, random forest, and neural network. The results show that machine learning models can provide more accurate predictions than conventional methods.