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All Journal EKSAKTA: Journal of Sciences and Data Analysis Jambura Journal of Mathematics
Mujiati Dwi Kartikasari
Department Of Statistics, Universitas Islam Indonesia
Chemical Engineering, Chemistry & Bioengineering Chemistry Earth & Planetary Sciences Materials Science & Nanotechnology Mathematics

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Premium Pricing of Liability Insurance Using Random Sum Model Mujiati Dwi Kartikasari
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 17, ISSUE 1, February 2017
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/eksakta.vol17.iss1.art5

Abstract

Premium pricing is one of important activities in insurance. Nonlife insurance premium is calculated from expected value of historical data claims. The historical data claims are collected so that it forms a sum of independent random number which is called random sum. In premium pricing using random sum, claim frequency distribution and claim severity distribution are combined. The combination of these distributions is called compound distribution. By using liability claim insurance data, we analyze premium pricing using random sum model based on compound distribution
Prediction of Outstanding Claims Liability in Non-Life Insurance: An Application of Adaptive Grey Model Mujiati Dwi Kartikasari; Hani’atul Maghfuroh
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 2, ISSUE 2, August 2021
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol2.iss2.art4

Abstract

In order to assess the solvency of non-life insurance companies, the prediction of outstanding claims liability is very important. Prediction of outstanding claims liability is usually done by using a run-off triangle data scheme. However, if data are not available to form the scheme, the prediction of outstanding claims liability cannot be made. Another alternative for predicting of outstanding claims liability is to use time series analysis. This research uses an adaptive grey model that has the advantage of being free of assumptions of data patterns and a minimum amount of data used to predict is small (at least 4 data). To determine the accuracy of the adaptive grey model, we compare the prediction of outstanding claims liability using a grey model classic. Based on the analysis results, the adaptive grey model is better than the classic gray model in predicting outstanding claims liability.
Self-Organizing Map Menggunakan Davies-Bouldin Index dalam Pengelompokan Wilayah Indonesia Berdasarkan Konsumsi Pangan Mujiati Dwi Kartikasari
Jambura Journal of Mathematics Vol 3, No 2: July 2021
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (800.87 KB) | DOI: 10.34312/jjom.v3i2.10942

Abstract

ABSTRAKKecukupan konsumsi pangan merupakan salah satu penunjang terbentuknya sumber daya manusia unggul yang menjadi fokus kebijakan pembangunan di Indonesia. Agar konsumsi pangan terpenuhi, salah satu cara yang dapat dilakukan adalah melakukan pengelompokan wilayah berdasarkan konsumsi pangan. Penelitian ini bertujuan untuk mengelompokkan wilayah Indonesia berdasarkan konsumsi pangan berdasarkan data konsumsi kalori per kapita sehari dari berbagai komoditas pangan. Pengelompokan wilayah dilakukan dengan metode self-organizing map (SOM) dengan terlebih dahulu ditentukan jumlah cluster optimum menggunakan nilai Davies-Bouldin Index (DBI) terkecil. Hasil penelitian menunjukkan bahwa hasil cluster optimum yang terbentuk sejumlah 4 cluster dengan jumlah anggota untuk cluster 1 sebanyak 22 provinsi, cluster 2 sebanyak 10 provinsi, cluster 3 sebanyak 1 provinsi, dan cluster 4 sebanyak 1 provinsi.ABSTRACTAdequate food consumption is one of the supports for forming superior human resources, which is the focus of development policies in Indonesia. To fulfill food consumption, one way to be done is to group regions based on food consumption. This study aims to classify regions of Indonesia based on food consumption based on average daily per capita calorie consumption data from various food commodities. Regional grouping is done using the self-organizing map (SOM) method by first determining the optimum number of clusters using the smallest Davies-Bouldin Index (DBI) value. The results showed that the optimum cluster results were 4 clusters with the number of members for cluster 1 as many as 22 provinces, cluster 2 as many as 10 provinces, cluster 3 as many as 1 province, and cluster 4 as many as 1 province.
Implementasi Metode Perhitungan Aktuaria Program Dana Pensiun Menggunakan Flask Muthia Dishanur Izzati; Mujiati Dwi Kartikasari
Jambura Journal of Mathematics Vol 4, No 2: July 2022
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1656.682 KB) | DOI: 10.34312/jjom.v4i2.12954

Abstract

The pension fund program is a program that seeks future planning by providing pension benefits to participants. The vital thing that becomes a concern in the pension fund program is the actuarial cost method. There are two categories for actuarial cost methods, which are Accrued Benefit-Cost Method and Projected Benefit-Cost Method. The normal contribution characteristic of the Projected Benefit-Cost Method is more stable than the Accrued Benefit-Cost Method, so it is better to use it from the participants’ perspective. This study discusses the use of the Projected Benefit-Cost Method by calculating normal contributions and actuarial liabilities from the methods included in it, which are Attained Age Normal, Entry Age Normal, and Individual Level Premium. Based on the calculation results, the Entry Age Normal and Individual Level Premium methods have a smaller final value of normal contribution payments and have a larger actuarial liability than the Attained Age Normal. Thus, of the three methods included in the Projected Benefit-Cost Method, the Entry Age Normal and Individual Level Premium methods are better used from the perspective of participants. For the calculation of pension funding using the Attained Age Normal, Entry Age Normal, and Individual Level Premium methods to be widely implemented by the public, this study created an application website using flask, which can be accessed at https://perhitunganaktuariadapen.herokuapp.com/.
Co-Authors Hani’atul Maghfuroh Muthia Dishanur Izzati