Pemodelan Tingkat Kemiskinan di Papua Barat dengan Pendekatan Binary Logistic Regression - Aini, Anissa Nur; Octario Ashar, Andika Udistiyan; Lestari, Talia Indah; Nur, Indah Manfaati; Wasono, Rochdi (UIN Walisongo Semarang, 2023)
Binary logistic regression model is a regression model used to predict the probability of a specific event occurring or not occurring based on predictor variable. In this model, the response variable is binary, meaning it has only two possible categories: a “failure”category and a “success” category. West Papua is included in the list of seven provinces that are the main focus of efforts to combat extreme poverty. Therefore, it is necessary to monitor the factors that need to be considered in order to prevent an increase in the poverty rate. To identify the factors influencing the poverty rate in Papua Barat, the research method used is binary logistic regression modeling, which assesses the influence of independent variables on the poverty rate in West Papua. So the results obtained from this study are from three variables, namely the open unemployment rate, average per capita expenditure, and gross regional domestic product have a significant effect on the poverty rate in West Papua with a classification accuracy of 100%.