A Kernel Logistic Regression Approach to Understanding the â€œBanyak Anak Banyak Rezekiâ€ Stigma - Tjabbe. Suwardi, Assyifaâ€™ Nur Qalby. A.; Sanur, Muh. Alwi; Chaerunnisa, Nurul Mutmainnah; Maulina, Azzahra Dwi Nur; Poerwanto, Bobby (Jurnal Varian, 2024)
Indonesia, the worldâ€™s 4th largest country with a population of 270 million in 2020, faces many challenges due to rapid population growth, including biodiversity loss and increased consumption of naturalresources. One of the cultural factors underlying the high rate of population growth is the perception ofâ€œBanyak Anak Banyak Rezekiâ€œ that develops in the community. This study aims to identify and modelthe factors that influence the â€œBanyak Anak Banyak Rezekiâ€ stigma and find solutions to overcome thisproblem. The research method used was quantitative, with a sample of 384 people in South Sulawesi,consisting of Bugis, Makassar, Toraja, and Mandar tribes. The variables studied include religiosity,tradition, number of children, and cognitive dissonance. The analysis techniques used were logisticregression (LR) and kernel logistic regression (KLR). The results showed that religiosity, number ofchildren, and cognitive dissonance had a significant effect on the â€œBanyak Anak Banyak Rezekiâ€ stigma.The accuracy of the LR model reached 87.01% and increased to 93.51% after using KLR.