Pemodelan Regresi Cox Proportional Hazard Pada Data Perceraian - Haykal Abidin; Novita Eka Chandra; Mohammad Syaiful Pradana (Unisda Journal of Mathematics and Computer Science (UJMC), 2020)
The purpose of this research is modeling the Cox proportional hazard regression form on divorce data in Pelaihari sub-district, Tanah Laut district, South Kalimantan province. The source of the data comes from the Court Decision in Pelaihari District, Tanah Laut Regency, South Kalimantan. The data analysis technique uses software R with the steps, namely data description, Log-Rank test, checking proportional hazard assumptions, Cox regression model parameter estimation, backward selection with AIC, the best model parameter significance test, calculating Hazard ratio and interpretation of each predictor variable. Based on the results of the analysis and discussion, it was found that for the Log-Rank test, the variable survival time for domestic violence, forced marriage, lying and stories of disgrace differed significantly. While the model that meets the criteria after iteration up to 15 times is the 15th model with the smallest AIC value and p-value <0.05 with factors that significantly influence divorce in Pelaihari sub-district based on modeling results using Cox proportional Hazard regression. are the variables of cheating, gambling, domestic violence, forced marriage, lies, jealousy and disgrace story variables