PREDIKSI PREMI ASURANSI KESEHATAN MENGGUNAKAN MACHINE LEARNING: PENDEKATAN ARTIFICIAL NEURAL NETWORK

Rifqi Fauzi(1), Annisa Cipta Nabila(2), Valentina Febri Krisnawati(3), Achmad Pratama Rifai(4*)

(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(4) Universitas Gadjah Mada
(*) Corresponding Author

Sari


Studi ini berfokus pada pengembangan model prediktif premi asuransi kesehatan dengan mengintegrasikan berbagai variabel, termasuk umur, jenis kelamin (sex), indeks massa tubuh (BMI), jumlah langkah harian (steps), jumlah anak (children), status perokok (smoker), wilayah geografis (region), dan klaim asuransi. Variabel-variabel tersebut diidentifikasi sebagai faktor-faktor kunci yang dapat mempengaruhi premi asuransi kesehatan. Pendekatan machine learning digunakan, khususnya model Artificial Neural Network (ANN), digunakan untuk memprediksi premi. Analisis perbandingan antara model ANN dan Multiple Linear Regression dilakukan untuk mengevaluasi keakuratan dan kinerja relatif keduanya. Prediksi yang dilakukan menggunakan metode ANN dan Multiple Linear Regression memberikan hasil yang cukup signifikan dimana secara berurutan nilai mean absolute error sebesar 1.242,59 dan 3.769,42, nilai mean squared error sebesar 15.713.857 dan 29.803.154. Hasil eksperimen menunjukkan bahwa model ANN memiliki kemampuan prediksi premi yang lebih baik dibandingkan dengan model Multiple Linear Regression, terutama dalam menangani pola kompleks dan interaksi non-linear antar variabel.

Kata Kunci:  Asuransi Kesehatan, Premi Asuransi, Prediction, ANN, Multiple Linear Regression. 


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DOI: http://dx.doi.org/10.31602/jieom.v7i1.13802

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