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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Gaussian Indonesian Journal of Applied Statistics Desimal: Jurnal Matematika Syntax Literate: Jurnal Ilmiah Indonesia Journal of Data Analysis InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya Premium: Insurance Business Journal Jurnal Riset Statistika Pattimura Proceeding : Conference of Science and Technology Bandung Conference Series: Statistics
Aceng Komarudin Mutaqin
Program Studi Statistika Universitas Islam Bandung
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Pemodelan Besar Klaim Asuransi untuk Jaminan Third Party Liability Menggunakan Distribusi Campuran Rayleigh-Rayleigh Nur Rofiq Azijah; Aceng Komarudin Mutaqin
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36418/syntax-literate.v8i11.13895

Abstract

This paper will discuss the modeling claim severity of ThirdParty Liability insurance using a mixed Rayleigh-Rayleigh distribution. The mixed Rayleigh-Rayleigh distribution is a distribution built on the basis of an infinitely mixed distribution. The mixed Rayleigh-Rayleigh distribution is a continuous distribution with one parameter, namely α. Parameters in the mixed Rayleigh-Rayleigh distribution can be estimated using the maximum likelihood estimator method through the Newton-Raphson iteration numerical method. The distribution fit test was carried out using the Kolmogorov-Smirnov fit test. The data used is data on Third Party Liability insurance claims with comprehensive coverage at PT. X for the 2019 policy for category 2 in all regions. Based on the results of applying the mixed Rayleigh-Rayleigh distribution on the data claim severity of Third Party Liability insurance with comprehensive coverage at PT. X in 2019 category 2 using the Kolmogorov-Smirnov test it can be concluded that the claims severity in regions 1 and 3 come from populations with a mixed Rayleigh-Rayleigh distribution, while the claim severity claims in region 2 come from populations that don't have a mixed Rayleigh-Rayleigh distribution.
Deskripsi Data Korban Kecelakaan Berdasarkan Usia Korban di Provinsi Jawa Barat Tahun 2022-2023 Hendrik Wijayanto; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 4 No. 2 (2024): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v4i2.15107

Abstract

Abstract. Traffic accidents are one of the most serious problems to be addressed, with traffic accidents being the third biggest killer after HIV/AIDS and tuberculosis. In West Java Province, traffic accidents are increasing from year to year. This needs to be a special concern so that traffic accident victims do not get worse. Therefore, a study was conducted to visually determine the number of incidents and the percentage of age and position of accident victims in 2022 and 2023 using descriptive analysis, where the severity of accident victims is divided into two, namely death and injury. The highest age category is in the age range of 15-24 including the Youth group, where there are 586 victims in 2022-2023, while the age of 85-95 or the elderly is ranked the lowest with 52 accident victims, with these results the percentage of the number of accidents for children and adolescents has increased by 3.06% over the past 1 year. Abstrak. Kecelakaan lalu lintas merupakan salah satu masalah yang cukup serius untuk ditangani, terbukti bahwa kecelakaan lalu lintas merupaan pembunuh terbesar ketiga setelah HIV/AIDS dan TBC. Di Provinsi Jawa Barat kecelakaan lalu lintas meningkat dari tahun ke tahun. Hal ini perlu menjadi perhatian khusus agar korban kecelakaan lalu lintas tidak semakin parah. Oleh karena itu dilakukan penelitian untuk mengetahui secara visual terkait banyaknya kejadian dan persentase dari usia dan kedudukan korban kecelakaan pada tahun 2022 dan 2023 menggunakan analisis deskriptif, dimana tingkat keparahan korban kecelakaan dibagi menjadi dua yakni meninggal dunia dan luka-luka. Kategori usia yang paling tinggi berada pada rentang usia 15-24 termasuk kedalam kelompok Remaja, dimana terdapat 586 korban pada tahun 2022-2023, sedangkan usia 85-95 atau lansia berada di peringkat paling rendah dengan jumlah 52 korban kecelakaan, dengan hasil tersebut persentase jumlah kecelakaan untuk kelompok anak – anak dan remaja mengalami peningkatan sebesar 3.06% selama 1 tahun terakhir.
Deskripsi Data Korban Kecelakaan Berdasarkan Kedudukan Korban di Provinsi Jawa Barat Tahun 2022-2023 Muhammad Rifqi Hendriawan; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 4 No. 2 (2024): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v4i2.15372

Abstract

Abstract. Traffic accidents are a problem that is quite serious to deal with, it has been proven that traffic accidents are the third biggest killer after HIV/AIDS and TBC. This needs special attention so that traffic accident victims do not get worse. Traffic accident is a word that is often used to describe damage to one or more components of a journey that ends in death, injury or damage to objects. This research was conducted to describe data on traffic accident victims based on the position of victims in West Java province in 2022-2023. The results of the descriptive analysis show that the highest number of fatalities and injuries in 2022 and 2023 was in the category of 2-wheeled motor vehicle drivers, namely an increase of 5.52% for injured victims and a decrease of 5.52% for fatalities. On the other hand, non-motorized vehicle drivers are in the lowest ranking, namely 51 victims for 2022 and 54 victims for 2023. Abstrak. Kecelakaan lalu lintas merupakan salah satu masalah yang cukup serius untuk ditangani, terbukti bahwa kecelakaan lalu lintas merupaan pembunuh terbesar ketiga setelah HIV/AIDS dan TBC. Hal ini perlu menjadi perhatian khusus agar korban kecelakaan lalu lintas tidak semakin parah. Kecelakaan lalu lintas adalah kata yang sering digunakan untuk menggambarkan kerusakan dari satu atau lebih dari sebuah komponen perjalanaan yang berakhir pada kematian, luka–luka, ataupun kerusakan benda. Penelitian ini dilakukan untuk mendeskripsikan data korban kecelakaan lalu lintas berdasarkan kedudukan korban di provinsi Jawa Barat tahun 2022-2023. Hasil analisis deskriptif menunjukan bahwa jumlah korban meninggal dunia dan luka luka tertinggi pada tahun 2022 dan 2023 ialah pada kategori pengendara kendaraan bermotor roda 2, yaitu mengalami peningkatan sebesar 5.52% untuk korban luka-luka dan penurunan untuk korban meninggal dunia sebesar 5.52%. Di sisi lain pengendara kendaraan non-bermotor berada di peringkat paling rendah yakni sebanyak 51 korban untuk tahun 2022 dan 54 korban untuk tahun 2023.
PENGHITUNGAN PREMI UNTUK ASURANSI KENDARAAN BERMOTOR BERDASARKAN SEJARAH FREKUENSI KLAIM PEMEGANG POLIS MENGGUNAKAN ANALISIS BAYES Mutaqin, Aceng Komarudin; Komarudin, Komarudin
PYTHAGORAS Jurnal Matematika dan Pendidikan Matematika Vol. 4 No. 1: Juni 2008
Publisher : Department of Mathematics Education, Faculty of Mathematics and Natural Sciences, UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (215.459 KB) | DOI: 10.21831/pg.v4i1.686

Abstract

Makalah ini membahas masalah penghitungan premi untuk asuransi kendaraan bermotor berdasarkan sejarah frekuensi klaim pemegang polis menggunakan analisis Bayes. Dilihat dari sudut pandang pemegang polis, premi yang dihasilkan bersifat adil, karena premi yang harus dibayarkan pada saat perpanjangan polis proporsional dengan taksiran frekuensi klaimnya. Sementara itu, dilihat dari sudut pandang perusahaan asuransi, akan menghasilkan keseimbangan finansial. Sebagai bahan aplikasi digunakan data klaim pemegang polis asuransi kendaraan bermotor dari salah satu perusahaan asuransi yang berdomisili di Bandung.  Kata kunci : sistem bonus malus, analisis Bayes, asuransi kendaraan bermotor, frekuensi                       klaim  
PENERAPAN METODE MULTIVARIATE CREDIBILITY BONUS MALUS PREMIUM PADA DATA ASURANSI KENDARAAN BERMOTOR DI INDONESIA Sinta Asanah; Aceng Komarudin Mutaqin
Premium Insurance Business Journal Vol. 10 No. 2 (2023): PREMIUM INSURANCE BUSINESS JOURNAL
Publisher : P3M Trisakti School of Insurance (TSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35904/premium.v10i2.52

Abstract

Abstrak: Pada penelitian ini akan dibahas mengenai perhitungan premi berdasarkan sistem bonus malus dengan metode multivariate credibility bonus malus premium menggunakan model trivariat yang membedakan besar klaim menjadi tiga jenis klaim yaitu besar klaim yang tinggi, besar klaim yang sedang, dan besar klaim yang rendah. Parameter model trivariat ditaksir menggunakan metode penaksiran kemungkinan maksimum. Distribusi untuk frekuensi klaim adalah distribusi binomial negatif dengan distribusi dasarnya yaitu distribusi Poisson. Sedangkan, penjumlahan kategori besar klaim untuk satu polis dimodelkan oleh distribusi binomial. Berdasarkan metode penaksiran kemungkinan maksimum, diperoleh nilai taksiran distribusi trivariat yaitu a=1,6095, b=4,3985, a1=1,4614, b1=4,5272, a2=1,4998, dan b2=1,4253. Nilai taksiran parameter tersebut digunakan untuk menghitung premi dan diperoleh nilai premi yaitu semakin banyak jumlah klaim yang diajukan seorang pemegang polis, maka akan semakin besar premi yang harus dibayarkan oleh pemegang polis tersebut. Selain itu, semakin meningkat kategori besar klaimnya, maka premi yang harus dibayar pemegang polis akan semakin besar. Abstract: This study will discuss the premium calculation based on the bonus malus system using the multivariate credibility bonus malus premium method using the trivariate model which differentiates claim size into three types of claims, namely high claim size, moderate claim size, and low claim size. The parameters of the trivariate model were estimated using the maximum likelihood estimation method. The distribution for the frequency of claims is the negative binomial distribution with the basic distribution being the Poisson distribution. Meanwhile, the sum of major categories of claims for one policy is modeled by the binomial distribution. Based on the maximum likelihood estimation method, the estimated values of the trivariate distribution are a=1,6095, b=4,3985, a1=1,4614, b1=4,5272, a2=1,4998, and b2=1,4253. The estimated value of these parameters is used to calculate the premium and the premium value is obtained, namely the more the number of claims submitted by a policyholder, the greater the premium that must be paid by the policyholder. In addition, the greater the category of claims, the greater the premium to be paid by policyholders.
Uji Dua Rata-Rata Waktu Belajar Mandiri Antara Mahasiswa Laki-Laki dan Perempuan Khalis Syahril Suryana; Syahla Anisah; Aceng Komarudin Mutaqin
Jurnal Riset Statistika Volume 4, No. 2, Desember 2024, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jrs.v4i2.5002

Abstract

Abstract. In this report the author wants to discuss the two average tests regarding the length of independent study time (in hours) between male and female students of the 2019 Unisba statistics study program. To do this, a t test or independent sample t-test is needed. Because male and female students are independent sample group data. The conditions for being able to carry out a t test are that the data must be normally distributed and the two samples must have homogeneous variance. To be able to test whether the data is normally distributed or not, it is necessary to carry out a normality test using the Lilliefors test. And to test whether the two samples have homogeneous variances or not, a homogeneity of variance test was carried out using Fisher's test. After that, a t test can be carried out to find out whether the two averages are the same or different. Abstrak. Dalam laporan ini penulis ingin membahas tentang uji dua rata-rata mengenai lamanya waktu belajar mandiri (dalam jam) antara mahasiwa laki-laki dan perempuan prodi statstika 2019 Unisba. Untuk melakukan itu diperlukan uji t atau indpendent sample t-test. Karena mahasiswa laki-laki dan perempuan merupakan data kelompok sampel yang saling bebas. Syarat untuk dapat melakukan uji t yaitu data tersebut harus berdistribusi normal dan kedua sampel tersebut harus memiliki varians yang homogen. Untuk dapat menguji apakah data berdistribusi normal atau tidak, perlu dilakukan uji normalitas menggunakan uji Lilliefors. Dan untuk menguji apakah kedua sampel tersebut memiliki varians yang homogen atau tidak, dilakukan uji homogenitas varians dengan uji Fisher. Setelah itu, dapat dilakukan uji t untuk mengetahui apakah dua rata-rata tersebut sama atau berbeda.
Penerapan Distribusi Zero Inflated Lognormal Pada Data Besar Klaim Asuransi Gempa Bumi PT X Ikbar Farid Maulana; Aceng Komarudin Mutaqin
Premium Insurance Business Journal Vol. 11 No. 2 (2024): PREMIUM INSURANCE BUSINESS JOURNAL
Publisher : P3M Trisakti School of Insurance (TSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35904/premium.v11i2.61

Abstract

Abstrak Asuransi gempa bumi menjadi bagian penting dalam mitigasi risiko bencana alam. Data besar klaim asuransi gempa bumi seringkali mengandung nilai nol. Salah satu distribusi yang dapat digunakan untuk memodelkan data besar klaim asuransi gempa bumi yang mengandung nilai nol adalah distribusi zero inflated lognormal. Dalam penelitian ini distribusi zero inflated lognormal akan diterapkan untuk memodelkan data besar klaim asuransi gempa bumi PT X di Indonesia tahun 2019- 2023. Parameter dari distribusi zero inflated lognormal akan ditaksir menggunakan metode penaksir kemungkinan maksimum. Penelitian ini juga akan dihitung taksiran rata-rata besar klaim asuransi gempa bumi di PT X. Hasil penelitian menunjukkan bahwa distribusi zero inflated lognormal cocok untuk memodelkan data besar klaim asuransi gempa bumi PT X di Indonesia baik untuk tiap tahun dari tahun 2019-2023. Nilai taksiran rata-rata besar klaim asuransi gempa bumi sebesar Rp 1.983.096.412 untuk tahun 2019, Rp 5.052.882.209 untuk tahun 2020, Rp 7.937.183.066 untuk tahun 2021, Rp 2.960.961.523 untuk tahun 2022, dan Rp 15.642.984 untuk tahun 2023. Abstract Earthquake insurance plays a crucial role in disaster risk mitigation. Large datasets of earthquake insurance claims often contain zero values. One distribution that can be used to model large earthquake insurance claim datasets containing zero values is the zero-inflated lognormal distribution. In this study, the zero-inflated lognormal distribution will be applied to model the large earthquake insurance claim data of PT X in Indonesia for the years 2019-2023. The parameters of the zero-inflated lognormal distribution will be estimated using the maximum likelihood estimation method. This study will also calculate the estimated average earthquake insurance claims at PT X. The results of the study show that the zero-inflated lognormal distribution is suitable for modeling the large earthquake insurance claim data of PT X in Indonesia for each year from 2019 to 2023. The estimated average earthquake insurance claims are Rp 1,983,096,412 for 2019, Rp 5,052,882,209 for 2020, Rp 7,937,183,066 for 2021, Rp 2,960,961,523 for 2022, and Rp 15,642,984 for 2023.
MIXING DISTRIBUTION ANALYSIS OF MIXTURE POISSON DISTRIBUTION FOR THIRD PARTY LIABILITY INSURANCE CLAIM FREQUENCY DATA IN INDONESIA Aceng Komarudin Mutaqin; Syahla Anisah
Jurnal Statistika dan Aplikasinya Vol. 9 No. 1 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09101

Abstract

The Indonesian government plans to mandate Third Party Liability (TPL) insurance for all vehicle owners in 2025. However, statistical modeling of TPL claim frequency data in Indonesia has received limited attention in academic research. The mixture Poisson distribution can be considered as a distribution for Third Party Liability claim frequency data in Indonesia. This is because claim frequency data often experiences overdispersion. In this study, the mixing distribution of the mixture Poisson distribution for TPL claim frequency data in Indonesia will be analyzed using a bootstrap approach. The data used in this study is policyholder claim frequency data for comprehensive coverage of TPL for underwriting years 2015-2019 for vehicle categories 1, 2, 3 and 6 of PT. X in Indonesia. The results generally show that most distributions with more parameters have a larger p-value (more suitable for use as a mixing distribution for mixture Poisson distribution) than distributions with fewer parameters.
The determination of the aggregate loss distribution through the numerical inverse of the characteristic function using the trapezoidal quadrature rule Mutaqin, Aceng Komarudin; Sa'diah, Khalimatus
Desimal: Jurnal Matematika Vol. 4 No. 3 (2021): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v4i3.9434

Abstract

Aggregate loss is the total loss suffered by an insured in a certain period. The aggregate loss depends on the claim frequency and the amount of the claim each time the insured makes a claim. The distribution of aggregate losses must be known to calculate motor vehicle insurance premiums. In general, there are two methods that can be used in determining the distribution of aggregate losses, namely exact and numerical. When an exact solution is difficult to find, numerical methods such as Monte Carlo, Panjer Recursion, and Fast Fourier Transform can be used. This research will discuss the determination of the distribution of aggregate losses through the numerical inverse of the characteristic function using the trapezoidal quadrature rule, on the data of motor vehicle insurance category 7 in Indonesia. The estimated cumulative distribution function for the largest aggregate loss is 0.999993. When x=0, it means that if someone does not file a claim, the estimated value of the cumulative distribution function is 0.9293. This value is close to the percentage of the number of insured, which is 0.9241.
Modeling third-party liability insurance claims: An exponential mixture distribution and parametric bootstrap-based solution Ainani Tajriyan Muntaharridwan; Aceng Komarudin Mutaqin
Desimal: Jurnal Matematika Vol. 8 No. 2 (2025): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/qwpt6206

Abstract

This study aims to model large third-party liability insurance claim data using an exponential mixture distribution with a parametric bootstrap approach. The research seeks to identify a suitable exponential mixture distribution and determine its properties, such as the mean, standard deviation, and probability. The methodology involves modeling the large third-party liability insurance claim data using an exponential mixture distribution where the mixing distribution is determined through a parametric bootstrap approach. The parametric bootstrap is utilized to generate a mixing distribution, with inverse gamma and inverse exponential distributions considered as candidates. The selection of the mixing distribution is based on the p-value of the Kolmogorov-Smirnov test and the log-likelihood function value. The parameters of the chosen exponential mixture distribution are estimated using the maximum likelihood method via the Newton-Raphson iteration. The data used is from a comprehensive third-party liability extension for category 2 vehicles in DKI Jakarta, Jawa Barat, and Banten for the 2018 underwriting year. The results of the analysis indicate that the exponential-inverse gamma mixture distribution is suitable for modeling the large claim data. The estimated mean value is IDR 4,318,360, the estimated standard deviation is IDR 6,797,485, and the estimated probability is 0.6950.
Co-Authors Abdul Kudus Agung Muhammad Fikri Agus Yodi Gunawan Ainani Tajriyan Muntaharridwan Ajeng Mega Pratiwi Alfan Siam Nuri Andi Setia Nugraha Anggis Sagitarisman Anneke Iswani A. Anneke Iswani Ahmad Asep Syaifulhadi Aunuddin Aunuddin Avin Rahmadian Budi Susetyo Danang Setiawan Disa Fauzana Dumaria R. Tampubolon Dwi Sekar Kania Fachry Abda El Rahman Fakhriel Muhammad Hafizh Fauziah Rahmayanti Fauziah Rahmayanti Fera Shintarini Harmonia Kamil Hendrik Wijayanto Ikbar Farid Maulana Indah Permatasari Indah Permatasari Inne Marliani Khalimatus Sa'diah Khalis Syahril Suryana Kiki Yogaswara Komarudin Komarudin Lia Rahayu Linda Maliani Lisnur Wachidah Lukman Nul Hakim M Dziqri Nur Rohiim M Dziqri Nur Rohiim M. Wildan Bin H.M. Yahya Mardianto Karim Mardianto Karim Maulana Ilham Pratama Maya Dian Wati Mira Zakiah Rahmah Mohammand Sobri Muhammad Iqbal Fauzi Muhammad Rifqi Hendriawan Muhammad Rizq Nafisyah Alam Muhammad Rizq Nafisyah Alam Naufal Fajar Nina Fitriyati Nur Rofiq Azijah NURTITI SUNUSI Nusar Hajarisman Puput Aryanti Raisha Shahelia Nastiti Resyi Pandini Safitri Riki Kurniawan Rillifa Iris Adisti Roosdiana N.R. Sa'diah, Khalimatus Sabda Iman Dani Safira Pratiwi Sheli Andriani Sinta Asanah Siti Magfiratul Hasanah Sutawanir Darwis Suwanda Suwanda Syahla Anisah Tanti Susanti Wulan Jati Nuray Yayat Karyana Yhupi Praga Adri Yusuf Fahrizal