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All Journal Variance : Journal of Statistics and Its Applications
Norisca Lewaherilla
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Mathematics

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PERHITUNGAN PREMI DENGAN PENERAPAN DEDUCTIBLE PADA MODEL AKTUARIA UNTUK SICKNESS INSURANCE PERTANGGUNGAN SATU TAHUN Norisca Lewaherilla; Gabriella Haumahu
VARIANCE: Journal of Statistics and Its Applications Vol 1 No 1 (2019): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol1iss1page39-45

Abstract

Health insurance is an insurance product that provides benefits if the insured is exposed to the risk of an accident or illness and causes loss of income, thus requiring costs. The most important benefit in this study from sickness insurance is the reimbursement of medical expenses. The design of determining premiums by applying deductibles (flat deductibles) is seen as one of the insurance policy policies that meet the principles of determining premiums. The actuarial aspects considered in the health insurance model in this study for the calculation of premiums relating to the type of insurance benefits with expense reimbursement for a period of one year coverage, with due regard to the type of work. The purpose of this study is to see the applied of deductible to the premiums that must be paid to insurance companies that provide benefits for claims submitted. The policy of applying deductibles certainly makes the amount of reimbursement change.
IMPLEMENTASI DATA MINING UNTUK KLASIFIKASI PENYAKIT ASAM URAT MENGGUNAKAN ALGORITMA C4.5 Gianovita Talarima; Ferry Kondo Lembang; Norisca Lewaherilla; Johan Bruiyf Bension
VARIANCE: Journal of Statistics and Its Applications Vol 5 No 1 (2023): VARIANCE: Journal of Statistics and Its Applications
Publisher : Statistics Study Programme, Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/variancevol5iss1page25-36

Abstract

Penyakit asam urat merupakan masalah kesehatan diseluruh dunia khususnya Indonesia dengan prevelensi mencapai angka 11,9%. Angka tersebut akan semakin meningkat jika adanya ketidaktahuan masyarakat umum tentang faktor-faktor yang dapat memicu terkena penyakit asam urat. Pada penelitian ini menggunakan Data Screening Civitas Akademika UKIM yang dilakukan untuk membuat model klasifikasi menggunakan Data Mining Algoritma C4.5 yang menghasilkan sebuah pohon keputusan serta pengujian yang dilakukan dengan menggunakan program R. Dari seluruh data berjumlah 277 data dibagi menjadi 198 data training dan 79 data testing. Dalam penelitian ini terdapat beberapa atribut klasifikasi yaitu, jenis kelamin, konsumsi alkohol, konsumsi gula berlebihan, usia, nilai IMT, dan riwayat penyakit. Berdasarkan perhitungan didapatkan hasil akurasi setelah post-pruning adalah 78% untuk data training dan 70% untuk data testing.
Co-Authors Ferry Kondo Lembang Gabriella Haumahu Gianovita Talarima Johan Bruiyf Bension