Prediksi Kepadatan Sampah Menggunakan Metode Regresi Linear Berbasis Web - gulo, titusman; Kustiyono (Jurnal Algoritma, 2025)
The issue of household waste is a crucial issue that has a direct impact on environmental cleanliness and public health. This study aims to develop a web-based household waste density prediction system using the Laravel framework, employing linear regression to model the relationship between time and waste volume. The research data was obtained through a survey of a number of families who recorded their weekly waste volume in kilograms. This system is designed to provide estimates of waste volume for the following week based on historical data patterns, thereby helping the community and environmental managers at the neighborhood association (RT/RW) level to plan waste collection and transportation more efficiently. The linear regression method was chosen because it is simple yet effective in describing trends in waste volume changes over time. The implementation results show that the system is capable of producing predictions that are close to actual conditions, equipped with informative graphics and a user-friendly interface. With this system, household waste management can be carried out in a more planned, efficient, and data-driven manner.