Implementasi Algoritma Linear Regression pada Framework Laravel untuk Prediksi Biaya Asuransi Kesehatan
DOI:
https://doi.org/10.76349/x2862183Kata Kunci:
biaya asuransi kesehatan, laravel, regresi linier berganda, php-ml, pembelajaran mesinAbstrak
Estimasi biaya medis yang akurat sangat krusial bagi perusahaan asuransi untuk memastikan penetapan premi yang presisi dan manajemen risiko yang efektif. Penelitian ini bertujuan untuk mengimplementasikan algoritma Multiple Linear Regression menggunakan pustaka php-ai/php-ml pada framework Laravel untuk memprediksi biaya asuransi kesehatan. Data yang digunakan adalah dataset sekunder Medical Insurance Cost yang terdiri dari 1.338 data historis pasien, dengan atribut meliputi usia, jenis kelamin, BMI, jumlah anak, dan status perokok. Metodologi penelitian mencakup pra-pemrosesan data melalui teknik encoding dan normalisasi, serta pembagian data dengan metode Hold-out Validation berasio 80:20. Hasil pengujian menunjukkan bahwa model menghasilkan nilai Mean Absolute Percentage Error (MAPE) sebesar 18,48% atau tingkat akurasi 81,52%. Kinerja ini mengindikasikan kemampuan prediksi kategori "Baik" (Good Forecasting), di mana model mampu mengikuti pola data aktual dengan presisi. Penelitian ini menyimpulkan bahwa integrasi regresi linear dengan pra-pemrosesan data yang tepat pada sistem berbasis web mampu memberikan estimasi biaya yang andal dan transparan.
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