Wijaya, Dimas Adi (2024) IMPLEMENTASI METODE RANDOM FOREST UNTUK MENENTUKAN PREDIKSI PUTUSAN PERCERAIAN DI KABUPATEN KUNINGAN (Studi Kasus : PKBH Universitas Kuningan). S1 / D3 thesis, Universitas Kuningan.

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Official URL: https://rama.uniku.ac.id

Abstract

Pernikahan dalam Islam dianggap sakral dan bertujuan untuk mencapai ketenangan serta kasih sayang antara pasangan. Namun, konflik dalam pernikahan seringkali menimbulkan perceraian yang meningkat signifikan di Indonesia, mencapai 516.334 kasus pada 2022. Penelitian ini bertujuan untuk menganalisis faktor-faktor perceraian di Kabupaten Kuningan menggunakan metode Data Mining, khususnya algoritma Random Forest. Data mining adalah proses menemukan pola dan informasi berguna dari kumpulan data besar menggunakan teknik statistik, matematika, dan kecerdasan buatan. Metode penelitian ini melibatkan analisis data perceraian dari Pengadilan Agama Kabupaten Kuningan (2019-2023). Atribut pada random forest usia pemohon, usia termohon, jumlah anak, indikator perceraian, lama nikah, dan Putusan. Hasil penelitian menunjukkan bahwa metode ini mampu memprediksi keputusan perceraian dengan akurasi 96,85%. Temuan ini diharapkan dapat membantu pihak-pihak terkait misalnya advokat dan pengadilan agama dalam mengidentifikasi kasus-kasus berisiko tinggi dan melakukan intervensi lebih awal untuk mengurangi angka perceraian.
Kata Kunci : Perceraian, Data Mining, Random Forest, Prediksi, Kabupaten Kuningan.

Marriage in Islam is considered sacred and aims to achieve tranquility and love between couples. However, conflicts in marriage often lead to divorce which has increased significantly in Indonesia, reaching 516,334 cases in 2022. This research aims to analyze the factors of divorce in Kuningan Regency using Data Mining method, especially Random Forest algorithm. Data mining is the process of finding patterns and useful information from large data sets using statistical, mathematical, and artificial intelligence techniques. Random forest is an ensemble algorithm consisting of a collection of decision trees. This research method involves analyzing divorce data from the Kuningan Regency Religious Court (2019-2023). The attributes in the random forest are applicant's age, respondent's age, number of children, divorce indicator, length of marriage, and verdict. The results showed that this method was able to predict divorce decisions with 96.85% accuracy. The findings are expected to help relevant parties such as advocates and religious courts in identifying high-risk cases and intervening early to reduce divorce rates.
Keywords : Divorce, Data Mining, Random Forest, Prediction, Kuningan Regency.

Item Type: Thesis (S1 / D3)
Uncontrolled Keywords: Perceraian, Data Mining, Random Forest, Prediksi, Kabupaten Kuningan. Divorce, Data Mining, Random Forest, Prediction, Kuningan Regency.
Subjects: L Education > L Education (General)
T Technology > T Technology (General)
Divisions: Fakultas Ilmu Komputer > S1 Sistem Informasi
Depositing User: S.Kom. Dimas Adi Wijaya
Date Deposited: 26 Nov 2024 06:29
Last Modified: 26 Nov 2024 06:29
URI: https://rama.uniku.ac.id/id/eprint/1992

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