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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 RAGAM: Journal of Statistics and Its Application
Aceng Komarudin Mutaqin
Program Studi Statistika Universitas Islam Bandung
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PEMODELAN DATA FREKUENSI KLAIM ASURANSI KENDARAAN BERMOTOR UNTUK CAKUPAN THIRD PARTY LIABILITY MENGGUNAKAN DISTRIBUSI POISSON-ARADHANA M Dziqri Nur Rohiim; Aceng Komarudin Mutaqin
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 4 No. 2 (2023): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v4i2.414

Abstract

The presence of insurance can provide coverage for all risks that occur for owners or motorists. Insurance will provide various forms of coverage in accordance with their respective products, so that vehicle owners or drivers will get protection, benefits or compensation for losses from various risks that occur above by buying an insurance policy of course. In Indonesia, motor vehicle insurance is included in the group of liability insurance. One of these insurance coverages is third-party legal liability. This is a protection against liability or third party legal responsibility or Third Party Liability, because the benefits provide protection against claims and losses experienced by third parties, in this case victims involved in accidents. Insurance premiums that can be provided by insurance companies to policyholders can be calculated based on the distribution model of claim frequency and claim size. Claim frequency is the number of insurance claims that occur in one period. Claim frequency data is often overdispersed. Poisson mixture distribution is often used as an alternative method for modeling claim frequency data when overdispersion occurs. This thesis will discuss the Poisson-Aradhana distribution modeling of motor vehicle insurance claim frequency data in Indonesia in 2019. The maximum likelihood estimation method is used to estimate the parameters of the Poisson-Aradhana distribution. The fit test used in this study is the Chi-Square test. The research material used is secondary data on the frequency of motor vehicle insurance claims recorded by PT. X from 8 categories and 3 regions in 2019. The results of the application of the Poisson-Aradhana mixed distribution on the frequency data of motor vehicle insurance claims for TPL coverage with comprehensive coverage at PT. X in 2019, most of the claim frequency data comes from a population with a Poison-Aradhana mixed distribution except for claim frequency data in category 1 region 3 and category 4 region 2
Penerapan Distribusi Lindley pada Data Besar Klaim Asuransi Kendaraan Bermotor di Indonesia Puput Aryanti; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 3 No. 2 (2023): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v3i2.8202

Abstract

Abstrak. Asuransi kendaraan bermotor adalah polis asuransi standar yang digunakan di Indonesia yang mencakup pertanggungan gabungan yaitu pertanggungan atas kendaraan bermotor itu sendiri dan pertanggungan tanggung jawab hukum kepada pihak ketiga. Salah satu hal yang perlu diperhatikan perusahaan asuransi sebagai lembaga penerima risiko adalah memodelkan data besar klaim. Distribusi yang cocok untuk memodelkan data besar klaim adalah distribusi kontinu yang non negatif, memiliki kemiringan yang positif, dan memiliki ekor yang tebal. Distribusi Lindley merupakan distribusi eksponensial campuran dan memiliki kriteria yang sesuai untuk pemodelan data besar klaim. Parameter yang ada ditaksir menggunakan metode kemungkinan maksimum. Pengujian kecocokan distribusi menggunakan uji Kolmogorov-Smirnov. Data yang digunakan merupakan data sekunder PT. X tahun 2019 yang terdiri dari data besar klaim pemegang polis asuransi kendaraan bermotor kategori 7 wilayah 2. Berdasarkan hasil penerapan distribusi Lindley untuk memodelkan data besar klaim asuransi kendaraan bermotor PT. X tahun 2019 dengan menggunakan uji Kolmogorov-Smirnov, dapat disimpulkan bahwa data besar klaim asuransi kendaraan bermotor PT. X tahun 2019 berasal dari populasi yang berdistribusi Lindley dengan nilai taksiran parameter distribusi Lindley sebesar θ=0,0000002995. Abstract. Motor vehicle insurance is a standard insurance policy used in Indonesia that includes combined coverage, namely coverage of the motor vehicle itself and legal liability coverage to third parties. One of the things that insurance companies need to pay attention to as risk-receiving institution is modeling the amount of the claim. A suitable distribution for modeling the amount of the claim is a continuous distribution that is non-negative, has a positive skew, and has a heavy tail. The Lindley distribution is a mixed exponential distribution and has criteria suitable for modeling the amount of the claim. The parameters were estimated using the maximum likelihood method. Testing the suitability of the distribution using the Kolmogorov-Smirnov test. The data used is secondary data of PT. X in 2019 which consists of data on large claims of motor vehicle insurance policyholders in category 7 region 2. Based on the results of the application of the Lindley distribution to model the 2019 PT. X motor vehicle insurance claim data using the Kolmogorov-Smirnov test, it can be concluded that the 2019 PT. X motor vehicle insurance claim data comes from a Lindley-distributed population with an estimated value of the Lindley distribution parameter of θ = 0.0000002995.
Analisis Pengaruh Bullying terhadap Kepercayaan Diri Mahasiswa Fakultas Mipa Universitas Islam Bandung Angkatan 2019 Avin Rahmadian; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 3 No. 2 (2023): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v3i2.8204

Abstract

Abstract. Bullying is an act of using power to hurt a person or group of people verbally, physically or psychologically so that the victim feels depressed, traumatized and helpless. In addition, bullying does affect an individual's self-confidence and interferes with the happiness of the subject or victim concerned. This study aims to determine whether there is an effect of bullying on the self-confidence of statistics students of the 2019 Islamic University of Bandung. The research method used is descriptive quantitative using a Likert scale and the number of samples taken is 100 respondents from Faculty of Mathematics and Natural Sciences Unisba class of 2019. The analysis technique used is regression analysis where the research results are significant regression coefficients or it can be said that bullying has a significant effect on Confidence of students of the Faculty of Mathematics and Natural Sciences, Bandung Islamic University class of 2019. Abstrak. Bullying adalah tindakan penggunaan kekuasaan untuk menyakiti seseorang atau sekelompok orang baik secara verbal, fisik maupun psikologis sehingga korban merasa tertekan, trauma dan tak berdaya. Selain itu bullying memang mempengaruhi kepercayaan diri seorang individu dan mengganggu kebahagiaan dari subjek atau korban yang bersangkutan. Penelitian ini bertujuan untuk mengetahui apakah terdapat pengaruh bullying terhadap kepercayaan diri mahasiswa statistika Angkatan 2019 Universitas Islam Bandung. Metode penelitian yang digunakan yaitu deskriptif kuantitatif dengan menggunakan skala likert dan jumlah sampel yang diambil yaitu sebanyak 100 responden dari Mahasiswa Fakultas FMIPA Unisba angkatan 2019. Teknis analisis yang digunakan yaitu analisis regresi dimana hasil penelitiannya yaitu koefisien regresi signifikan atau dapat dikatakan Bullying berpengaruh secara signifikan terhadap Kepercayaan diri Mahasiswa Fakultas MIPA Universitas Islam Bandung angkatan 2019.
Pengaruh Infrastruktur dan Inovasi Hybrid Learning terhadap Kepuasan Mahasiswa Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Islam Bandung Angkatan 2020-2021 M Dziqri Nur Rohiim; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 3 No. 2 (2023): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v3i2.8236

Abstract

Abstract. The COVID-19 pandemic has an impact on all aspects of the world, including education in Indonesia. The Indonesian government together with the Ministry of Education and Culture then decides to implement a limited Face-to-Face Learning, namely Hybrid Learning. This makes University of Islam Bandung carry out Limited Face-to-Face Learnig for the even semester of the 2021/2022 academic year, the learning applied is hybrid, online, and offline. This certainly affects the satisfaction of students who are taking Hybrid Learning for the first time. Therefore, the researcher wants to examine the “Effect of Hybrid Learning Infrastructure and Innovation on Student Satisfaction of the Faculity of Mathematics and Science University of Islam Bandung Class of 2020-2021”. The population of this research is FMIPA student class 2020-2021 with a sample of 100 students. The analysis technique in this study is Multiple Linear Regression Analysis by testing several classical intruments and assumptions. Based on the results of the study, it can be concluded that infrastructure has no significant effect on satisfaction, innovation does have a significant effect on satisfaction. Obtained a value of 14,1% diversity of satisfaction can be explained by infrastructure and innovation. Meanwhile (100% - 14,1% = 86,9%) the rest is explained by other reasons outside the model. Abstrak. Pandemi COVID-19 berdampak terhadap segala aspek di dunia, termasuk pada pendidikan di Indonesia. Pemerintah Indonesia bersama dengan Kementrian Pendidikan dan Kebudayaan kemudian memutuskan untuk menerapkan PTM terbatas, yaitu Hybrid Learning. Hal itu membuat Unversitas Islam Bandung melaksanakan Pembelajaran Tatap Muka Terbatas untuk semester genap tahun ajaran 2021/2022, pembelajaran yang diterapkan yaitu hybrid, daring, dan luring. Hal ini tentunya berpengaruh terhadap kepuasan mahasiswa yang baru pertama kali mengikuti Hybrid Learning. Maka dari itu, peneliti ingin meneliti mengenai “Pengaruh Infrastruktur dan Inovasi Hybrid Learning terhadap Kepuasan Mahasiswa Fakultas MIPA Unisba Angkatan 2020-2021”. Populasi penelitian ini adalah mahasiswa FMIPA angkatan 2020-2021 dengan sampel sebanyak 97 mahasiswa. Teknik analisis dalam penelitian ini adalah Analisis Regresi Linear Berganda dengan menguji beberapa uji Instrumen dan Asumsi Klasik. Berdasarkan hasil penelitian, dapat disimpulkan bahwa infrastruktur tidak berpengaruh secara signifikan terhadap kepuasan, inovasi benar-benar berpengaruh secara signifikan terhadap Kepuasan. Didapat nilai 14,1% keragaman kepuasan dapat dijelaskan oleh infrastruktur dan inovasi. Sedangkan (100% - 14,1% = 86,9%) sisanya dijelaskan oleh sebab-sebab lain di luar model.
Penerapan Analisis Konjoin untuk Mengukur Preferensi Wisatawan di Panti Tanjung Kerasak Kabupaten Bangka Sabda Iman Dani; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 3 No. 2 (2023): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v3i2.9398

Abstract

Abstract. Tourism activities have now become a necessity for people who are important to increase productivity in their daily lives. Bangka Belitung Province is an archipelago province that has a long coastline so that it has so many and varied beach tourism destinations. But it is very unfortunate that of the many beach tourism destinations owned in the South Bangka district, it is not maximized in the processing of beach tourism so that the attractiveness of visitors is less enthusiastic. It is important to know people's preferences for what kind of tourist destination they want, so that managers can maximize tourism management strategies that can attract many tourists. According to Ghozali (2011) in Saputra S (2020), conjoin analysis is used to determine how respondents perceive an object that has certain characteristics. In marketing research, conjoin analysis is used to determine how consumer preferences for various product designs. From the results of research with conjoin analysis, it shows that the stimuli that respondents are interested in are the existence of water tourism attractions, the existence of shelters and meeting points, good road networks, the existence of travel agents, the existence of community participation, and the existence of a security division, but from this the factor that has the highest utility value is the good road network factor followed in order by the community participation factor, the existence of a security division factor. Abstrak. Kegiatan pariwisata saat ini telah menjadi kebutuhan bagi masyarakat yang penting untuk meningkatkan produktifitas dalam kesehariannya. Provinsi Bangka Belitung merupakan provinsi kepulauan yang memiliki garis pantai yang panjang sehingga memiliki destinasi wiasata pantai yang begitu banyak dan beragam. Namun sangat disayangakan dari sekian banyak destinasi wisata pantai yang dimiliki di kabupaten Bangka Selatan tidak dimaksimalkan dalam pengolahan wisata pantai sehingga daya tarik pengunjung kurang antusias. Penting untuk mengetahui preferensi masyarakat terhadap destinasi wisata seperti apa yang diinginkan, sehingga pengelola dapat memaksimalkan strategi pengelolaan pariwisata yang dapat mengundang banyak wisatawan. Menurut Ghozali (2011) dalam Saputra S (2020), analisis konjoin digunakan untuk mengetahui bagaimana persepsi responden terhadap suatu objek yang memiliki karakteristik tertentu. Dalam riset pemasaran, analisis konjoin digunakan untuk mengetahui bagaimana preferensi konsumen terhadap berbagai desain produk. Dari hasil penelitian dengan analisis konjoin menunjukan stimuli yang diminati responden adalah adanya antraksi wisata air, adanya shelter dan meeting poin, jaringan jalan baik, adanya agen perjalanan wisata, adanya partisipasi masyarakat, dan adanya divisi ke amanan, namun dari hal tersebut faktor yang memiliki nilai kegunaan tertinggi adalah faktor jaringan jalan baik di ikuti secara berurutan adanya faktor partisipasi masyarakat, adanya faktor divisi keamanan, adanya faktor shelter dan meeting point, adanya faktor atraksi wisata air, dan adanya faktor agen perjalanan wisata
Penerapan Distribusi Inverse Gaussian pada Data Besar Klaim Asuransi Kendaraan Bermotor di Indonesia Fauziah Rahmayanti; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 3 No. 2 (2023): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v3i2.9456

Abstract

Abstract. Insurance is an agreement between the guaranteeing party and the guaranteed party where the guaranteeing party agrees with the guaranteed party to receive a premium as a replacement for losses, which will later be experienced due to events that have not yet occurred. Insurance is divided into two parts, namely general insurance and life insurance. One product of loss insurance is motor vehicle insurance. In several previous studies, there are many distributions that have been applied to insurance data (claims big data). Insurance and economic data are often positive and the distribution is usually skewed to the right. One of the most well-known parametric models with distributions that are usually skewed to the right is the inverse Gaussian which is a family of two-parameter distributions namely µ and λ. The material used in this thesis is big data on partial loss claims for motor vehicle insurance insurance company PT. ABC in 2019 Category 1 Region 2. The results of applying the inverse Gaussian distribution show that the large data for Category 1 motor vehicle insurance claims for Region 2 come from populations with an inverse Gaussian distribution. Abstrak. Asuransi merupakan persetujuan antara pihak yang menjamin dengan pihak yang dijamin di mana pihak yang menjamin bersepakat kepada pihak yang dijamin untuk menerima premi sebagai pengganti kerugian, yang nantinya akan dialami karena kejadian yang belum terjadi. Asuransi terbagi kedalam dua bagian yaitu asuransi kerugian (asuransi umum) dan asuransi jiwa. Salah satu produk dari asuransi kerugian adalah asuransi kendaraan bermotor. Pada beberapa penelitian terdahulu, terdapat banyak distribusi yang telah diterapkan pada data asuransi (data besar klaim) Data asuransi dan ekonomi seringkali positif dan distribusinya biasanya miring ke kanan. Salah satu model parametrik yang paling terkenal dengan distribusi yang biasanya miring ke kanan adalah inverse Gaussian yang merupakan keluarga distribusi dua parameter yakni dan . Bahan yang digunakan dalam skripsi ini adalah data besar klaim partial loss asuransi kendaraan bermotor perusahaan asuransi PT. ABC tahun 2019 Kategori 1 Wilayah 2. Hasil penerapan distribusi inverse Gaussian menunjukan data besar klaim asuransi kendaraan bermotor Kategori 1 untuk Wilayah 2 berasal dari populasi yang berdistribusi inverse Gaussian.
Penerapan Model Bivariat Menggunakan Copula Frank pada Jumlah Gol Hasil Pertandingan Liga 1 Indonesia 2019 Naufal Fajar; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 3 No. 2 (2023): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v3i2.9463

Abstract

Abstract. Indonesia is one of the countries that always organizes soccer competitions. Liga 1 is an Indonesian football league that brings together 18 of the best soccer teams from Indonesia. Each team played 34 times on a home-away system. The purpose of this thesis is to improve the quality of Indonesian football and mark the gradual league system of Indonesian football at a competitive level. Many studies have been conducted by researchers in various countries to process data on the number of goals scored in soccer matches for home and away teams from a soccer league. Joel Liden (2016) discusses the Copula Frank distribution followed by the marginal distribution, namely the Poisson distribution and the negative Binomial distribution, a distribution for data from discrete random variables. This thesis will discuss the application of the Copula Frank distribution to data on the number of goals for home and away teams from the highest caste Indonesian football league matches for 2018-2019 and to find out whether the Copula Frank distribution is a suitable opportunity distribution for modeling the case of the number of goals data. the. The distribution fit test used is the Chi-square test. As research material, secondary data from recording results obtained from PSSI.com will be used and presented as data on the results of the 2018-2019 Indonesian League 1 football match. The maximum likelihood estimator method is used to estimate the parameters of the discrete distribution. While the distribution fit test to be used is the chi-square test. As an application material, secondary data will be used as a result of recording obtained from rsssf.com and flashscore.com. The data that will be used contains information on the number of goals for the home team and the number of goals for the away team in the 2018-2019 Indonesian League 1 matches. The results of the application show that the bivariate Poisson distribution using Copula Frank is not suitable for modeling bivariate data on the number of goals for the home and away team in the Indonesian League 1 in 2018-2019. Abstrak. Indonesia merupakan salah satu negara yang selalu menyelenggarakan kompetisi sepak bola. Liga 1 merupakan liga sepak bola Indonesia yang mempertemukan 18 tim sepak bola terbaik dari Indonesia. Masing-masing tim bertanding sebanyak 34 kali dengan sistem kandang-tandang. Tujuan dibuat skripsi ini untuk meningkatkan kualitas sepak bola Indonesia dan menandai sistem liga bertahap sepak bola Indonesia di tingkat kompetitif. Sudah banyak penelitian yang dilakukan oleh para peneliti di berbagai negara untuk mengolah data jumlah gol hasil pertandingan sepak bola untuk tim kandang dan tim tandang dari suatu liga sepak bola. Joel Liden (2016) membahas distribusi Copula Frank diikuti oleh distribusi marjinal yaitu distribusi Poisson dan distribusi Binomial negatif, suatu distribusi untuk data dari peubah acak diskrit. Dalam Skripsi ini akan dibahas mengenai penerapan distribusi Copula Frank pada data jumlah gol tim kandang dan tim tandang hasil pertandingan Liga sepak bola Indonesia kasta tertinggi untuk tahun 2018-2019 dan untuk mengetahui apakah distribusi Copula Frank merupakan distribusi peluang yang cocok untuk memodelkan kasus data jumlah gol tersebut. Uji kecocokan distribusi yang digunakan adalah uji Chi-kuadrat. Sebagai bahan penelitian akan digunakan data sekunder hasil pencatatan yang diperoleh dari PSSI.com dan disajikan menjadi data hasil pertandingan sepakbola Liga 1 Indonesia tahun 2018-2019. Metode penaksir kemungkinan maksimum digunakan untuk menaksir parameter distribusi diskrit tersebut. Sedangkan uji kecocokan distribusi yang akan digunakan adalah uji chi-kuadrat. Sebagai bahan aplikasi akan digunakan data sekunder hasil pencatatan yang diperoleh dari yaitu rsssf.com dan flashscore.com. Data yang akan digunakan tersebut berisi informasi jumlah gol tim kandang dan jumlah gol tim tandang pertandingan Liga 1 Indonesia tahun 2018-2019. Hasil penerapan menunjukkan bahwa distribusi Poisson bivariat menggunakan Copula Frank tidak cocok untuk memodelkan data bivariat jumlah gol tim kandang dan tim tandang Liga 1 Indonesia tahun 2018-2019.
Penerapan Distribusi Zero Modified Poisson pada Data Jumlah Gol Tim Tandang Liga Sepak Bola Indonesia Maulana Ilham Pratama; Aceng Komarudin Mutaqin
Bandung Conference Series: Statistics Vol. 3 No. 2 (2023): Bandung Conference Series: Statistics
Publisher : UNISBA Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/bcss.v3i2.9477

Abstract

Abstract. The Indonesian League, which is currently known as the Indonesia Super League (ISL) or Liga 1, is the highest caste football competition between clubs in Indonesia. The Indonesian League was held for the first time in 1994 (the competition system was divided into 2 regions) which was a merger between the previous major competitions. Many researchers from various countries have carried out the application of distributions to football sports data cases to find out what odds distributions are suitable for modeling the number of goals scored in home and away games in a league. Distributions that can be used to model data on the number of goals scored in soccer matches include the Poisson distribution, negative binomial, Poisson-Lindley, and Zero-Inflated Poisson. In a football match, it is generally difficult for the away team to score goals. One of the discrete distributions for the case of the Poisson distribution when there are many zeros is the Zero-Modified Poisson distribution. In this thesis, the ZMP distribution will be applied to the data on the number of goals scored by the away team in the Indonesian Football League. The maximum likelihood estimator method is used to estimate the parameters of the discrete distribution. While the distribution fit test to be used is the chi-square test. As the application material, data on the results of the 2017-2018 Indonesian League football matches will be used. Based on the results of an analysis of the application of the Zero-Modified Poisson distribution to data on the number of goals scored by the Indonesian League 1 away team in 2017-2018, it can be concluded that the Zero-Modified Poisson distribution is suitable for modeling the frequency data of the number of goals scored by the Indonesian League 1 away team in 2017-2018. Abstrak. Liga Indonesia yang pada saat ini dikenal dengan Indonesia Super League (ISL) atau liga 1 adalah kompetisi sepak bola kasta tertinggi antar klub di Indonesia. Liga Indonesia diselenggarakan pertama kali pada tahun 1994 (sistem kompetisi dibagi 2 wilayah) yang merupakan penggabungan antara kompetisi besar sebelumnya. Penerapan distribusi pada kasus data olahraga sepak bola sudah banyak dilakukan oleh peneliti-peneliti dari berbagai negara untuk mengetahui distribusi peluang apa yang cocok untuk memodelkan jumlah gol dalam pertandingan kandang dan tandang dalam suatu Liga. Distribusi yang bisa digunakan untuk memodelkan data jumlah gol hasil pertandingan sepak bola diantaranya adalah distribusi Poisson, binomial negatif, Poisson-Lindley, dan Zero-Inflated Poisson. Dalam suatu pertandingan sepakbola, umumnya tim tandang selalu kesulitan untuk mencetak gol. Salah satu distribusi diskrit untuk kasus distribusi Poisson ketika nilai nol-nya banyak adalah distribusi Zero-Modified Poisson. Dalam skripsi ini akan diterapkan distribusi ZMP pada data jumlah gol tim tandang Liga sepak bola Indonesia. Metode penaksir kemungkinan maksimum digunakan untuk menaksir parameter pada distribusi diskrit tersebut. Sedangkan uji kecocokan distribusi yang akan digunakan adalah uji chi-kuadrat. Sebagai bahan aplikasi akan digunakan data hasil pertandingan sepak bola Liga Indonesia tahun 2017-2018. Berdasarkan hasil analisi penerapan distribusi Zero-Modified Poisson pada data jumlah gol tim tandang Liga 1 Indonesia tahun 2017-2018 dapat disimpulkan bahwa distribusi Zero-Modified Poisson cocok untuk memodelkan data frekuensi jumlah gol tim tandang Liga 1 Indonesia tahun 2017-2018.
Perhitungan Premi Risiko Asuransi Kendaraan Bermotor Berdasarkan Data Frekuensi dan Besar Klaim Dwi Sekar Kania; Aceng Komarudin Mutaqin
Jurnal Riset Statistika Volume 2, No. 2, Desember 2022, Jurnal Riset Statistika (JRS)
Publisher : UPT Publikasi Ilmiah Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jrs.v2i2.1295

Abstract

Abstract. Risk is an unpleasant result (harm) of an action or action. Life insurance is a risk transfer effort that bears financial losses from the risk of the death of the policyholder. General insurance is a risk transfer effort that insures property that may suffer losses. The product of general insurance is motor vehicle insurance. The number of motorized vehicles indicates how useful motorized vehicles are, which causes an increase in motorized vehicle ownership. In line with that, the incidence of road accidents is also increasing, but many of those who suffer losses from vehicle accidents do not receive the compensation that is the right of the vehicle owner. From the explanation of insurance, it is said to be able to control a risk, where in insurance we have to pay a certain amount of money to get the "protection". The amount paid is called the premium. Based on this phenomenon, the formulation of the problem in this study is How to apply the calculation of risk premiums based on claim frequency data and big data claims conducted by Ozgurel (2005) for each vehicle category and region at insurance company XYZ? Abstrak. Asuransi merupakan salah satu bentuk untuk mengendalikan suatu risiko dengan cara memindahkan risiko dari satu pihak ke pihak lain. Asuransi jiwa adalah suatu usaha pengalihan risiko yang menanggung kerugian finansial dari risiko kematian pemegang polis. Asuransi umum adalah suatu usaha pengalihan risiko yang menanggung harta benda yang mungkin mengalami kerugian. Produk dari asuransi umum adalah asuransi kendaraan bermotor. Banyaknya kendaraan bermotor tersebut menandakan betapa bergunanya kendaraan bermotor, yang menyebabkan meningkatnya kepemilikan kendaraan bermotor. Sejalan dengan itu, terjadi kecelakaan di jalan raya ikut meningkat, tetapi banyak dari mereka yang mengalami kerugian dari kecelakaan kendaraan tidak memperoleh santunan yang menjadi hak pemilik kendaraan. Dari penjelasan asuransi yang dikatakan dapat mengendalikan suatu risiko, di mana dalam asuransi kita harus membayar sejumlah uang untuk mendapatkan “perlindungan” tersebut. Sejumlah uang yang dibayarkan tersebut dinamakan dengan premi. Berdasarkan fenomena tersebut, maka rumusan masalah dalam penelitian ini yaitu Bagaimana menerapkan perhitungan premi risiko berdasarkan data frekuensi klaim dan data besar klaim yang dilakukan oleh Ozgurel (2005) untuk setiap kategori kendaraan dan wilayah pada perusahaan asuransi XYZ?
Ukuran-Ukuran Aktuaria untuk Data Besar Klaim Berdistribusi Inverse Gaussian Fauziah Rahmayanti; Aceng Komarudin Mutaqin
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 2 (2024): JANUARY 2024
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i2.30067

Abstract

An insurance company must be able to manage risks in the form of claims submitted by policyholders. There are several risk measures or actuarial measures that can be used to predict future risks and help companies prepare reserves. These actuarial measures are Value at Risk (VaR), Tail Value at Risk (TVaR), Tail Variance (TV), and Tail Variance Premium (TVP). In this article, we will discuss these actuarial measures for inverse Gaussian distributed claim severity. The Kolmogorov-Smirnov test is used to test the fit of the inverse Gaussian distribution. The maximum likelihood estimator is used as a method to estimate the parameters of the inverse Gaussian distribution. The data used in this article is data on partial loss claims for motor vehicle insurance insurance company PT. ABC in 2019 Category 1 in all regions. However, after testing the goodness of fit of the distribution using the Kolmogorov-Smirnov test for region 3, it did not come from a population with an inverse Gaussian distribution. So the data used to proceed to the actuarial measures estimation stage is only region 1 and region 2. Based on the results of calculating the actuarial measures for inverse Gaussian distributed claim severity, it can be concluded that the value of losses expected by a company can be calculated by taking into account the actuarial measures for claim severity on motor vehicle insurance in Indonesia.
Co-Authors Abdul Kudus Agung Muhammad Fikri Agus Yodi Gunawan Ainani Tajriyan Muntaharridwan Ajeng Mega Pratiwi Alfan Siam Nuri Aliya Maharani 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 Evania Putri 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