Penerapan Smote Pada Data Tidak Seimbang Dalam Pemodelan Status NEET Penduduk Usia Muda di Provinsi Banten Tahun 2022
Abstract
In 2022, the percentage of NEET youth in Banten Province increased and occupied the second-highest position in Java and seventh-highest in Indonesia, at 27.29%. The imbalanced data have been identified compared to the percentage of non-NEET youth, which reached 72.71%. This study aims to apply the SMOTE Technique to handle this imbalanced data and determine the variables that influence the NEET status of youth. The method used in this study is binary logistic regression. The model evaluation results prove that the model with imbalanced data handling by SMOTE is better at modelling the NEET status of youth in Banten. Area of residence, household relationship status, marital status, age, education level, disability status, and training experience significantly influence the NEET status of youth. Thus, it is necessary to expand employment opportunities and provide easy access to training and skills development in rural areas, including for people with disabilities.
NEET (Not in Education, Employment or Training) pada penduduk usia muda telah menjadi isu internasional. Peningkatan jumlah penduduk usia muda NEET menggambarkan peningkatan potensi yang hilang bagi suatu wilayah serta kegagalan sistem pendidikan dan pasar kerja. Pada tahun 2022, persentase penduduk usia muda NEET Provinsi Banten mengalami kenaikan dan menempati posisi tertinggi kedua se-Pulau Jawa dan ketujuh se-Indonesia, yakni sebesar 27,29 persen. Dibandingkan dengan persentase penduduk usia muda bukan NEET yang mencapai 72,71 persen, telah teridentifikasi adanya data tidak seimbang. Penelitian ini bertujuan untuk menerapkan Synthetic Minority Oversampling Technique (SMOTE) untuk menangani data tidak seimbang dan mengetahui variabel yang memengaruhi status NEET penduduk usia muda di Provinsi Banten tahun 2022. Metode yang digunakan dalam penelitian ini adalah regresi logistik biner. Hasil evaluasi model membuktikan bahwa model yang disertai penanganan data tidak seimbang dengan SMOTE lebih baik dalam pemodelan status NEET penduduk usia muda di Provinsi Banten tahun 2022. Dari model terbaik, dapat disimpulkan bahwa wilayah tempat tinggal, status hubungan dalam rumah tangga, status perkawinan, umur, tingkat pendidikan, status disabilitas, dan pengalaman mengikuti pelatihan secara signifikan berpengaruh terhadap status NEET penduduk usia muda di Provinsi Banten tahun 2022. Oleh karena itu diperlukan upaya perluasan lapangan pekerjaan serta pemberian kemudahan akses pelatihan dan pengembangan keterampilan hingga ke wilayah perdesaan termasuk untuk penyandang disabilitas.
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