Model Regresi Gamma untuk Menganalisis Indeks Pengeluaran Kabupaten/Kota di Pulau Sumatra

Gamma regression is part of Generalised Linear Models (GLMs) that can model data that is positive and asymmetric. The occurrence of data asymmetry is common in everyday life, for example in Human Development Index (HDI) data. The HDI has indicators called the Human Development Dimension Index, including the expenditure index, the education index and the life expectancy index. This study aims to model the expenditure index of districts/cities in Sumatra using Gamma regression because the expenditure index data is positive and non-symmetric. In modelling the Expenditure Index, the predictor variables used are the percentage of poor population, population density, percentage of population using their own toilet, and open unemployment rate in each district/city in Sumatra in 2023. The data used were obtained from the BPS website of the province corresponding to the regency/city in Sumatra. Based on the results of the analysis, all the predictor variables used had a significant effect on the expenditure index at the 1% and 5% significance levels, and the standard error value of each parameter estimate was small. In addition, the MSE of the model is also classified as small, which is 0.00163. This can prove that the model is supported by the data, although the coefficient of determination of the model ( ) in this study is only 47.59%.