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http://repository.ipb.ac.id/handle/123456789/114125
Title: | Identifikasi Faktor yang Memengaruhi Anak Putus Sekolah di Provinsi Daerah Istimewa Yogyakarta Menggunakan Regresi Logistik Biner |
Authors: | Anisa, Rahma Alamudi, Aam Hasanah, Malikhatul |
Issue Date: | 2022 |
Publisher: | IPB University |
Abstract: | Anak putus sekolah merupakan anak yang tidak mampu menyelesaikan
pendidikannya dan berhenti sekolah sebelum masa belajarnya berakhir sehingga
belum memiliki tanda tamat belajar atau ijazah pada jenjang pendidikan tersebut.
Provinsi DIY merupakan salah satu provinsi yang memiliki kasus putus sekolah
dan mengalami peningkatan dari tahun 2018 sampai 2020. Untuk itu, penelitian ini
bertujuan memodelkan kejadian anak putus sekolah di Provinsi DIY menggunakan
regresi logistik biner dengan menerapkan metode SMOTE untuk menangani
ketidakseimbangan data sehingga diketahui faktor-faktor yang memengaruhinya.
Regresi logistik biner digunakan karena peubah respon bersifat biner (Y = 1 jika
putus sekolah dan Y = 0 jika masih aktif bersekolah). Data penelitian menggunakan
data sekunder hasil Survei Sosisal Ekonomi Nasional 2021 yang dilakukan oleh
Badan Pusat Statistik wilayah Provinsi DIY. Hasil penelitian menunjukkan faktor
yang berpengaruh, yaitu pendidikan kepala rumah tangga, rata-rata pengeluaran
rumah tangga perkapita, status bekerja anak, dan status penerima PIP dengan
ketepatan klasifikasi model berikut : akurasi 79,16%, F1-score 17,19%, dan AUC
83,22%. Dropout schools are children who are unable to complete their education and leave school before the end of their study period so that they do not obtain certificate from school or a diploma at that level of education. DIY Province is one of the provinces that has dropout cases increasing from 2018 to 2020. For this reason, this study aims to model the incidence of school dropouts in DIY Province using binary logistic regression by applying the SMOTE method to handle data imbalances so that the factors that influence it are known. Binary logistic regression was used because the response variables were binary (Y = 1 if they dropped out of school and Y = 0 if they were still in school). This research used secondary data from the 2021 National Socio-Economic Survey conducted by the Central Statistics Agency for the DIY Province. The results showed that the influencing factors were the education of the head of the household, the average household expenditure per capita, the child’s working status, and the status of PIP recipients with 79,16% accuracy, 17,19% F1-score, and 83,22% AUC. |
URI: | http://repository.ipb.ac.id/handle/123456789/114125 |
Appears in Collections: | UT - Statistics and Data Sciences |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Cover.pdf Restricted Access | Cover | 206.75 kB | Adobe PDF | View/Open |
G14180018_Malikhatul Hasanah.pdf Restricted Access | Fullteks | 2.19 MB | Adobe PDF | View/Open |
Lampiran.pdf Restricted Access | Lampiran | 765.79 kB | Adobe PDF | View/Open |
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