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Journal : Indonesian Journal of Applied Statistics

Analisis Premi Asuransi Jiwa Menggunakan Model Cox Proportional Hazard Firda Anisa Fajarini; Mohamat Fatekurohman
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v1i2.25280

Abstract

Cox proportional hazard model is a regression model that is used to see the factors that cause an event. The survival analysis used in this research is the period of time the client is able to pay the life insurance premium using Cox proportional hazard model with Breslow method.The purpose of this research is to know how sex, age, insured money, job, method of payment of premium, premium, and type of product can influence the level of ability of client to make payment of life insurance premium based on customer data from PT. BRI Life Insurance Branch of Jember in 2007.The result of this research is the final model of Cox proportional hazard obtained from several variables which have significant influence with simultaneous and partial significance test is the variable of insured money (X3), variable of payment method of premium (X5), premium variable (X6) , and insurance product variable (X7) . The four variables are said to have a significant effect on the model, so that the final model of Cox proportional hazard is obtained that consists of the parameter estimation (β) value of each variable Keywords : survival analysis; cox proportional hazard model; breslow method; life insurance.
Aplikasi Model Cox Proportional Hazard pada Pasien Stroke RSD Balung Kabupaten Jember Tutik Qomaria; Mohamad Fatekurohman; Dian Anggraeni
Indonesian Journal of Applied Statistics Vol 2, No 2 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i2.34907

Abstract

According to the World Health Organization (WHO) cardiovascular disease is a disease caused by impaired heart and blood vessel function. There are many types of cardiovascular disease, but the most common and most well-known are coronary heart disease and stroke. Stroke is a syndrome characterized by symptoms and / or rapidly developing clinical signs in the form of focal and global brain functional disorders lasting more than 24 hours (unless there are surgical interventions or bringing death), which are not caused by other causes besides vascular causes. The number of stroke patients in Indonesia in 2013 based on the diagnosis of health personnel (Nakes) was 1.236.825 (7,0%), while based on the diagnosis of symptoms was 2.137.941 (12,1%). In this study the factors that can affect the survival of stroke sufferers were analyzed using the Cox proportional hazard regression model, the dependent variable was the length of time the patient was treated and the independent variables were gender, age, hypertension status, cholesterol status, Diabetes Militus (DM) status, stroke type, and Body Mass Index (BMI). The result showed that age, DM status, and type of stroke were the most influential factors on the survival of stroke patients at Balung Regional Hospital.Keywords : stroke disease, survival analysis, Cox proportional hazard model
Perbandingan Model Cox Proportional Hazard dan Regresi Weibull untuk Menganalisis Ketahanan Bank Syariah Yusrillah Ihza Zianita Afni; Mohamad Fatekurohman; Dian Anggraeni
Indonesian Journal of Applied Statistics Vol 2, No 2 (2019)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v2i2.33082

Abstract

On July 1, 2014 Financial Services Authority (OJK) issued a new regulation number 8/PJOK.13/2014 concerning the health of general sharia banks that can be valued from several aspects including credit risk, liquidity risk, Return on Asset (ROA), Net of Margin (NOM) and Capital Adequacy Ratio (CAR). The purpose of this study is to compare the models of Cox proportional hazard and Weibull regression for the resistance of sharia bank in 2017-2018 for 24 data. The data were analyzed by describing each variable and modeling in each method. Comparison result shows that Weibull regression model is better than the Cox proportional hazard model because it has smaller AIC and MSE.Keywords : Sharia Bank, Survival Analysis, AIC, MSE
Peramalan Arus Kas dengan Pendekatan Time Series Menggunakan Support Vector Machine Bella Audina; Mohamat Fatekurohman; Abduh Riski
Indonesian Journal of Applied Statistics Vol 4, No 1 (2021)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v4i1.47953

Abstract

Cash flow is a form of financial report that is used as a measure of the company success in the investment world. So that companies need to forecast the cash flow to manage their finances. Statistics can be applied for the forecasting of cash flow using the Support Vector Machine (SVM) method on the time series data. The aim of this research is to determine the optimal parameter pair model of the Radial Basic Function kernel and to obtain the forecasting results of cash flow using the SVM method on the time series data. The independent variable is needed the data on cash flow from operating income, expenditure and investment expenditure, sum of all cash flow. While the dependent variable is the financial condition based on the Free Cash Flow. The result of this research is a model with the best parameter pairs of the SVM tuning results with the greatest accuracy that is 75%, 82%, 88%, 64% and the forecasting financial condition of PT Cakrawala for the next 16 months.Keywords: cash flow, forecasting, time series, support vector machine.
Analisis Ketahanan Hidup Pasien Kanker Paru Menggunakan Regresi Weibull Arivatus Solehah; Mohamat Fatekurohman
Indonesian Journal of Applied Statistics Vol 1, No 2 (2018)
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13057/ijas.v1i2.25276

Abstract

Lung cancer is one of the diseases which difficult to detect because of uneasy symptoms detection till it develops being the risky one. But, if the disease has been found, it can spread fast and cause death. According to the data of WHO, the type of cancer which causes the most of death is lung cancer which reaches 1,3 milion death per year. Therefore, a survival analysis will be conducted to determine factors that affect the survival of lung cancer patient by using Weibull regression. The result shows some factors that significantly influence the survival of lung cancer patient are gender, erythrocyte, and general condition. Keywords : lung cancer; survival analysis; Weibull regression