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All Journal Journal of Actuarial, Finance, and Risk Managment Indonesian Council of Premier Statistical Science
Syarifah Intan Nabilah
Study Program Of Actuarial Science, President University
Computer Science & IT Economics, Econometrics & Finance Mathematics Public Health Social Sciences

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Identifying Fraud in Automobile Insurance Using Naïve Bayes Classifier Dadang Amir Hamzah; Annisa Sentya Hermawan; Shintya Jasmine Pertiwi; Syarifah Intan Nabilah
Journal of Actuarial, Finance, and Risk Management Vol 1, No 2 (2022)
Publisher : Journal of Actuarial, Finance, and Risk Management

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33021/jafrm.v1i2.3971

Abstract

In this article, the Naïve Bayes Classifier is employed to detect fraud in automobile insurance. The Naïve Bayes classier is a simple probabilistic method based on the Bayes theorem. The data used in this article is determined from databricks.com which consists of 40 attributes and 1000 entries. The target attribute that will be predicted consists of two categories,” yes" or "no", which inform whether there is a fraud or not. The Data is split into training and testing with suitable proportions. Based on training data, the Naïve Bayes Classifier is applied to the testing data and returns the predictions data. Then, the prediction data is compared with the actual data to see the performance of the method. The result shows that the Naïve Bayes Classifier gives a good result to predict the insurance fraud with 78% accuracy, 67% precision, 3% of recall,  and  6% of F1 score  for “Yes”
Analisis Survival Terhadap Pasien Penderita Gagal Ginjal Menggunakan Metode Kaplan Meier Anisha Putri Ramadhani; Nafia Rahmi; Putri Nadira; Syarifah Hidayah; Teshi Amelia Hakilla Kisty
Indonesian Council of Premier Statistical Science Vol. 2 No. 1 (2023): February 2023
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/icopss.v2i1.25323

Abstract

Analisis ketahanan hidup adalah sebuah metode statistika yang digunakan untuk menganalisis data dimana variabel yang diperhatikan yaitu waktu sampai terjadinya suatu kejadian, kejadian yang dimaksud dapat berupa munculnya penyakit baru, penyakit berulang maupun kematian. Untuk menghitung peluang ketahanan hidup penderita gagal ginjal, akan digunakan metode Kaplan-meier. Objek yang dijadikan penelitian yaitu pasien penderita penyakit gagal ginjal pada Januari 2018 – November 2020 di RS Universitas Hasanuddin Kota Makassar Provinsi Sulawesi Selatan. Diperoleh hasil bahwa faktor kronik-akut, jenis kelamin, serta usia memiliki hubungan masing-masing saling bebas terhadap penderita gagal ginjal dan diperoleh penaksiran probabilitas ketahanan hidup sebesar 0.540 (54%).
Co-Authors Anisha Putri Ramadhani Annisa Sentya Hermawan Hamzah, Dadang Amir Nafia Rahmi Putri Nadira Shintya Jasmine Pertiwi Teshi Amelia Hakilla Kisty