Faktor Status Bekerja di Kabupaten Karawang 2024 Menggunakan Regresi Logistik Biner Multilevel

Abstract. The multilevel binary logistic regression method is a statistical approach used to analyze the relationship between a binary dependent variable and several independent variables, particularly in datasets with a hierarchical structure, where observation units (such as individuals) are nested within higher-level units (such as regions). In this study, the method is applied to analyze the factors influencing the employment status of the working-age population in Karawang Regency, based on the 2024 National Labor Force Survey (SAKERNAS) data. The dependent variable is employment status, categorized into two groups: employed (1) and unemployed (0). The level-1 independent variables at the individual level include age, gender, highest educational attainment, marital status, and participation in special training. Meanwhile, regional characteristics (urban or rural) are modeled as a level-2 random effect. Parameter estimation is conducted using the Maximum Likelihood method with the Laplace Approximation approach. The analysis results indicate that age, gender, education level, and special training significantly influence employment status. Additionally, there is variation between regions that also affects an individual's likelihood of being employed. These findings highlight the importance of considering regional characteristics when analyzing labor force dynamics in Karawang. Abstrak. Metode regresi logistik biner multilevel merupakan pendekatan statistik yang digunakan untuk menganalisis hubungan antara variabel dependen biner dan sejumlah variabel independen. Dengan konteks data yang memiliki struktur hierarkis, di mana unit pengamatan (seperti individu) dikelompokkan ke dalam unit yang lebih tinggi (seperti wilayah). Dalam penelitian ini, metode tersebut diterapkan untuk menganalisis faktor-faktor yang memengaruhi status bekerja penduduk usia kerja di Kabupaten Karawang berdasarkan data SAKERNAS 2024. Variabel dependen yang diteliti adalah status bekerja dikategorikan menjadi dua: bekerja (1) dan tidak bekerja (0). Variabel independen tingkat individu (level 1) meliputi umur, jenis kelamin, pendidikan terakhir, status perkawinan, dan pelatihan khusus, sedangkan karakteristik wilayah (perkotaan dan perdesaan) dimodelkan sebagai efek acak pada level 2. Penaksiran parameter dilakukan menggunakan metode Maximum Likelihood dengan pendekatan Laplace Approximation. Hasil analisis menunjukkan bahwa umur, jenis kelamin, pendidikan terakhir, dan pelatihan khusus berpengaruh signifikan terhadap status bekerja. Selain itu, terdapat variasi antar wilayah yang turut memengaruhi kemungkinan seseorang bekerja. Temuan ini menegaskan pentingnya mempertimbangkan karakteristik wilayah dalam analisis ketenagakerjaan di Karawang.

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Journal
Bandung Conference Series Statistics
Published
2025-08-04
DOI
https://doi.org/10.29313/bcss.v5i2.20546
Primary Topic
Economic Growth and Fiscal Policies
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article
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article

Faktor Status Bekerja di Kabupaten Karawang 2024 Menggunakan Regresi Logistik Biner Multilevel

Afifa Ulya Rosyida, Nusar Hajarisman
Bandung Conference Series Statistics
Economic Growth and Fiscal Policies
article

Faktor Status Bekerja di Kabupaten Karawang 2024 Menggunakan Regresi Logistik Biner Multilevel

Afifa Ulya Rosyida, Nusar Hajarisman
article en

Abstract

Abstract. The multilevel binary logistic regression method is a statistical approach used to analyze the relationship between a binary dependent variable and several independent variables, particularly in datasets with a hierarchical structure, where observation units (such as individuals) are nested within higher-level units (such as regions). In this study, the method is applied to analyze the factors influencing the employment status of the working-age population in Karawang Regency, based on the 2024 National Labor Force Survey (SAKERNAS) data. The dependent variable is employment status, categorized into two groups: employed (1) and unemployed (0). The level-1 independent variables at the individual level include age, gender, highest educational attainment, marital status, and participation in special training. Meanwhile, regional characteristics (urban or rural) are modeled as a level-2 random effect. Parameter estimation is conducted using the Maximum Likelihood method with the Laplace Approximation approach. The analysis results indicate that age, gender, education level, and special training significantly influence employment status. Additionally, there is variation between regions that also affects an individual's likelihood of being employed. These findings highlight the importance of considering regional characteristics when analyzing labor force dynamics in Karawang. Abstrak. Metode regresi logistik biner multilevel merupakan pendekatan statistik yang digunakan untuk menganalisis hubungan antara variabel dependen biner dan sejumlah variabel independen. Dengan konteks data yang memiliki struktur hierarkis, di mana unit pengamatan (seperti individu) dikelompokkan ke dalam unit yang lebih tinggi (seperti wilayah). Dalam penelitian ini, metode tersebut diterapkan untuk menganalisis faktor-faktor yang memengaruhi status bekerja penduduk usia kerja di Kabupaten Karawang berdasarkan data SAKERNAS 2024. Variabel dependen yang diteliti adalah status bekerja dikategorikan menjadi dua: bekerja (1) dan tidak bekerja (0). Variabel independen tingkat individu (level 1) meliputi umur, jenis kelamin, pendidikan terakhir, status perkawinan, dan pelatihan khusus, sedangkan karakteristik wilayah (perkotaan dan perdesaan) dimodelkan sebagai efek acak pada level 2. Penaksiran parameter dilakukan menggunakan metode Maximum Likelihood dengan pendekatan Laplace Approximation. Hasil analisis menunjukkan bahwa umur, jenis kelamin, pendidikan terakhir, dan pelatihan khusus berpengaruh signifikan terhadap status bekerja. Selain itu, terdapat variasi antar wilayah yang turut memengaruhi kemungkinan seseorang bekerja. Temuan ini menegaskan pentingnya mempertimbangkan karakteristik wilayah dalam analisis ketenagakerjaan di Karawang.

Bandung Conference Series StatisticsVol. 5(2)
Bandung Islamic University (ID)
Openalex Percentile: Top 71%
Economic Growth and Fiscal Policies
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