Pemodelan regresi logistik Firth Penalized Maximum Likelihood Estimation pada kepemilikan tempat usaha

Eva Khoirun Nisa, Siti Maslihah

Abstract


Pada penelitian sosial sering memperoleh data kategorik dengan proporsi kategori yang diinginkan (sukses) jauh lebih sedikit dibandingkan dengan proporsi kategori yang tidak diinginkan (gagal). Data tersebut dikatakan sebagai separasi sempurna atau rare events. Data dengan rare events bila digunakan dalam regresi termasuk regresi logistik akan menghasilkan estimator parameter yang bias dalam proses Maximum Likelihood Estimation (MLE). Untuk mengatasi kebiasan karena data rare events atau separasi sempurna maka Firth menambahkan unsur penalti matriks informasi Fisher fungsi ln likelihood MLE. Metode tersebut dinamakan Firth Penalized Maximum Likelihood Estimation. Penelitian ini bertujuan untuk memodelkan regresi logistik dengan Firth Penalized Maximum Likelihood Estimation pada data kepemilikan tempat usaha. Model regresi logistik yang diperoleh sudah sesuai dengan data dan menghasilkan bahwa bidang usaha, umur usaha, skala UMKM, dan lokasi usaha berpengaruh terhadap kepemilikan tempat usaha. Dengan demikian, para pelaku UMKM perlu mempertimbangkan dengan bijak kepemilikan tempat usaha. 


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DOI: https://doi.org/10.26877/aks.v15i3.21088

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