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        <dc:title>OPTIMISASI ANALISIS REGRESI LOGISTIK LASSO MENGGUNAKAN BAYESIAN INFORMATION CRITERION (BIC) (STUDI KASUS : FAKTOR PENYEBAB PERCERAIAN DI INDONESIA TAHUN 2024)</dc:title>
        <dc:creator>Mutiara Nur Amalina, NIM.: 22106010089</dc:creator>
        <dc:subject>515.6 Metode Analitik - Matematika</dc:subject>
        <dc:description>Divorce is a social issue influenced by various contributing factors and shows&#13;
different patterns across provinces. This study aims to classify divorce levels in Indonesia&#13;
in 2024 using LASSO logistic regression with optimal parameter selection&#13;
based on the Bayesian Information Criterion (BIC). The data used in this study are&#13;
secondary data from the Statistics Indonesia (BPS), covering 34 provinces in Indonesia.&#13;
The response variable was categorized into two groups, namely low and&#13;
high divorce levels, based on the divorce rate per 1,000 population. Meanwhile, the&#13;
predictor variables consisted of 13 factors causing divorce. The analysis began with&#13;
the development of an initial logistic regression model, followed by multicollinearity&#13;
testing, variable standardization, the application of the LASSO method, and the&#13;
selection of the optimal λ value using BIC. The results showed that the initial logistic&#13;
regression model experienced multicollinearity, as all variables had VIF values&#13;
greater than 10. Through the LASSO-BIC method, the optimal value obtained was&#13;
λBIC = 0.003914, with a minimum BIC value of 26.77. The final model retained&#13;
six variables, namely gambling, abandonment by one spouse, imprisonment of one&#13;
spouse, polygamy, physical disability/illness, and continuous disputes or conflicts.&#13;
Compared with the initial model, LASSO-BIC produced a simpler model, reducing&#13;
the number of parameters from 14 to 7 and decreasing the BIC value from 66.055&#13;
to 26.770.</dc:description>
        <dc:date>2026-05-20</dc:date>
        <dc:type>Thesis</dc:type>
        <dc:type>NonPeerReviewed</dc:type>
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        <dc:identifier>https://digilib.uin-suka.ac.id/id/eprint/76851/1/22106010089_BAB-I_IV-atau-V_DAFTAR-PUSTAKA.pdf</dc:identifier>
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        <dc:identifier>https://digilib.uin-suka.ac.id/id/eprint/76851/2/22106010089_BAB-II_sampai_SEBELUM-BAB-TERAKHIR.pdf</dc:identifier>
        <dc:identifier>  Mutiara Nur Amalina, NIM.: 22106010089  (2026) OPTIMISASI ANALISIS REGRESI LOGISTIK LASSO MENGGUNAKAN BAYESIAN INFORMATION CRITERION (BIC) (STUDI KASUS : FAKTOR PENYEBAB PERCERAIAN DI INDONESIA TAHUN 2024).  Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.   </dc:identifier></oai_dc:dc>
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