PEMODELAN REGRESI GAMMA MENGGUNAKAN METODE OPTIMASI BROYDEN-FLETCHER-GOLDFARB-SHANNO (BFGS) (Studi Kasus : Pencemaran Sungai di Kota Semarang) - Efifah Nur Safitri; Arief Rachman Hakim; Suparti Suparti (Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro, 2025)
Semarang City is one of the major industrial areas in Central Java and is located not far from residential areas. These large industries utilize a variety of chemicals to meet their needs, producing various wastes that are the main cause of high concentrations of Chemical Oxygen Demand (COD) in waters. Measurements on the COD value obtained are continuous data with Gamma distribution. In this study, Gamma regression is used to model the relationship between one or more predictor variables and a positive continuous response variable following a Gamma distribution. Parameter estimation in the Gamma regression model uses the Maximum Likelihood Estimation (MLE) method because it does not produce an analytical solution, an optimization method will be carried out with the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. This study aims to determine the Gamma regression model in the case of river pollution in Semarang City, determine the form of parameter estimation in the Gamma regression model and get what factors affect river pollution in Semarang City. Based on the value of 0.4431498 where the ability of the predictor variables to explain the response variable is 44.32%, the remaining 55.68% of the response variable is explained by other factors not contained in the model.