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Journal : Jurnal Matematika

Analisis Premi dari Asuransi Pengangguran I Nyoman Widana; Ketut Jayanegara
Jurnal Matematika Vol 9 No 1 (2019)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2019.v09.i01.p111

Abstract

Unemployment insurance is designed to overcome some of the financial problems faced by workers who have been involuntarily terminated from their jobs. The benefit insurance is financed based on the contributory from an employer, employee or government in recent times, some developing countries have been establishing unemployment insurance. This research aims to analyze the unemployment insurance products in Indonesia. Especially to analyze the financial viability of the product. The method used is the equivalence premium principle. Based on data sourced from BPJS Ketenagakerjaan and a claim rate of 10%, it is found that a premium rate of 5% of insured wages would support a benefit level of 50% of the wages for 43 weeks. This premium rate would also support 70% of the wages for 32 weeks. Meanwhile, the premium rate of 1% of the participant wages would guarantee a benefit level of 50% for 6 weeks.
Memodelkan Impor Beras Menggunakan Regresi Data Panel Eka N Kencana; Darma Arnawa; Ketut Jayanegara
Jurnal Matematika Vol 10 No 2 (2020)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2020.v10.i02.p130

Abstract

Abstract Rice is one of the world’s most important commodities. The Food and Agri-cultural Organizations estimates about 90 percent of the world’s rice is produced bycountries in the Asian continent with the rice production centers located in the ASEANregion. As an agricultural country, Indonesia is ranked third in the world rice producersafter China and India, and in the first rank of ASEAN rice producers. However, Indone-sia along with other producing countries in ASEAN also import rice. This article aimsto model rice imports from 5 ASEAN countries. Using data from FAO for the period2009–2018, 3 types of Panel Data Regression models were applied to model rice imports.The results of the analysis show Random Effect Model (REM) is the most appropriatemodel for rice imports in 5 ASEAN countries with the difference for two consecutiveyears import, consumption, and rice production was used as explanatory variables .Keywords: import, panel data, random effect, regression, rice.
Analisis Komponen Biaya Asuransi Jiwa Dwiguna (Endowment) Desak Nyoman Trisnawati; I Nyoman Widana; Ketut Jayanegara
Jurnal Matematika Vol 4 No 1 (2014)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2014.v04.i01.p41

Abstract

Asuransi adalah suatu istilah penyediaan jasa yang bergerak dalam bidang pertanggungan atau perlindungan. Seseorang yang telah mengasuransikan dirinya akan menyetujui kontrak yang disebut dengan polis. Di Indonesia terdapat beberapa jenis asuransi jiwa, salah satunya adalah asuransi jiwa dwiguna. Asuransi jiwa dwiguna adalah asuransi jiwa yang kepada tertanggung akan diberikan sejumlah uang pada akhir asuransi sesuai dengan polis. Jika tertanggung meninggal selama masa asuransi atau setelah akhir asuransi, kepada tertanggung akan diberikan uang sebesar uang pertanggungan. Untuk memenuhi pertanggungan, akan dibayarkan sejumlah uang yang disebut dengan premi. Premi terdiri dari premi netto dan premi bruto, premi netto adalah premi yang perhitungannya hanya berdasarkan faktor mortalita, sedangkan premi bruto adalah gabungan dari premi netto dengan faktor-faktor lain seperti faktor biaya. Penelitian ini membahas tentang analisis komponen biaya pada asuransi jiwa dwiguna. Komponen dari biaya asuransi jiwa dwiguna ini adalah biaya penutupan awal, biaya pengumpulan premi dan biaya pemeliharaan.Semua perhitungan aktuaria menggunakan tabel CSO 1980 dengan bunga 9%. Dengan menerapkan metode Eliminasi Gauss Jordan besarnya komponen biaya dari asuransi jiwa dwiguna masing-masing, biaya penutupan awal sebesar dan , biaya pengumpulan premi sebesar 0,075 dan biaya pemeliharaan sebesar 2.
EVALUASI KINERJA JARINGAN SYARAF TIRUAN PADA PERAMALAN KONSUMSI LISTRIK KELOMPOK TARIF RUMAH TANGGA I Putu Eka N. Kencana; Ketut Jayanegara
Jurnal Matematika Vol 2 No 1 (2012)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2012.v02.i01.p22

Abstract

Many methods have been applied in forecasting technics, varied fromStatistical Forecasting Methods (SFM) or Mathematical Modelling and ForecastingMethods (MMFM) to Artificial Neural Methods (ANM). This research aimedto implement and evaluate performance of Artificial Neural Network (ANN), onemethod in ANM group; for forecasting electricity consumption by household inProvince of Bali. This research used electricity consumption data from January2001 to December 2009 as basis for network’s training and validating its result.The actual data from January to December 2010 is used to evaluate the performanceof network prediction. Research shows the Mean Absolute Prediction Error(MAPE) of the ANN’s prediction is 7,56%.
Penerapan Metode K-means Pada Klasterisasi Provinsi di Indonesia Berdasarkan Indikator Indeks Kebahagiaan Damayanthi, Ni Wayan Rita; Suciptawati, Ni Luh Putu; Jayanegara, Ketut; Sukarsa, I Komang Gde; Kencana, Eka N.; Wijayakusuma, I Gusti Ngurah Lanang
Jurnal Matematika Vol 14 No 1 (2024)
Publisher : Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2024.v14.i01.p172

Abstract

The happiness index is a measure that reflects individual well-being, thus playing an important role in the development of a region. The level of happiness in Indonesia is still significantly lower compared to other ASEAN countries. In relation to efforts to improve the happiness index in Indonesia, this study applies the K-means method to cluster the 34 provinces of Indonesia based on the indicators of the happiness index for the year 2021. The data used is sourced from publications by the Indonesian Central Bureau of Statistics with seven happiness index indicators and employing the Minkowski distance. The clustering results of the 34 provinces using the K-means method obtained four clusters with a cluster accuracy value of 71 percent. Cluster 1 consists of seven provinces with a fairly high average of seven attributes, cluster 2 consists of seven provinces is a cluster with a low average level of internal and external satisfaction, cluster 3 consists of four provinces with a high average of seven attributes, and cluster 4 consists of 16 provinces is a cluster with provinces with a fairly high average level of external satisfaction, but a low level of internal satisfaction.