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PEMODELAN FAILURE TIME PADA MAHASISWA BERHENTI STUDI DI UNIVERSITAS JEMBER Hanifia, Fidiatma Foristy; Fatekurohman, M.; Anggraeni, Dian
Majalah Ilmiah Matematika dan Statistika Vol 20 No 1 (2020): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v20i1.17218

Abstract

Problems in higher education concerning students are always interesting objects studied from any side. One of the problems faced by universities and students is stopping study. Stopping the study of students became a problem in universities, including the University of Jember. One of the statistical methods used is Survival Analysis. In its development, survival analysis was carried out by combining the concepts of Geometric regression. Geometric is one of the non linear regression for discrete data. Geometric regression modeling cannot be done with ordinary linear modeling, but must be done using the Generalized Linear Model (GLMs) method. In this study the variables used were gender, GPA, faculty, age of entry and entry point. The results of the study students stopped studying in the first semester 140 students. Average GPA of 1.54. 62.85% male sex. Student faculty of education and teacher stopped most studies. The student entry pathway stopped the most SBMPTBR studies and 54.40% were 18 years old. Significant influential factors for stopping the study were GPA, gender and entry point. From the Geometric opportunity, it was found that female students were slower when they stopped studying than men. The faculty stops studying at the latest is the Faculty of Medicine. Keywords: Drop Out, Failure Time, Regrition Geometric Method
PERBANDINGAN MODEL ACCELERATED FAILURE TIME DAN MODEL COX PROPORTIONAL HAZARD PADA KASUS KARDIOVASKULAR Fatmala, Siti Febriana; Fatekurohman, Mohamat; Hadi, Alfian Futuhul
Majalah Ilmiah Matematika dan Statistika Vol 18 No 1 (2018): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v18i1.17244

Abstract

Cardiovascular disease is a disease that attacks the heart and blood vessels. Many types of cardiovascular diseases, but the most famous are coronary heart disease and stroke. Coronary heart disease is a disease that is the first cause of death that occurs in the world caused by risk factors and the length of time of survival of coronary heart disease patients, then using survival analysis with the Cox Proportional Hazard model and Accelerated Failure Time model. Comparison between Cox Proportional Hazard model and Accelerated Failure Time model expedited time can be determined by the survival time with a safe function, the hazard function and density function (comparison of income) of each questioned duration of time with the help of different AIC policies and the rate of deterioration. Estimation of the survival time of this cardiovascular case is determined from the Cox Proportional Hazard’s hazard ratio model and the Accelerated Failure Time’s time ratio model. The results showed that the Accelerated Failure Time model was better than the Cox Proportional Hazard model because the rate of deterioration and the AIC value was smaller than the other models and related to risk factors, namely the age and status of diabetes mellitus and the length of survival of the patient for 11 days obtained from the estimation of the survival time distribution between the Cox Proportional Hazard model and the Accelerated Failure Time model. Keywords: Coronary heart disease, survival analysis, Cox Proportional Hazard, Accelerated Failure Time
Estimating of Survival Function of Hepatitis Virus in Jember Mohamad Fatekurohman
Jurnal ILMU DASAR Vol 8 No 2 (2007)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (210.474 KB)

Abstract

Statistical method to analyse data of lifetime is called survival analysis. One problem in survival analysis is estimation of survival function. This function can be estimated by using nonparametric method. One problem in  medical is to study the lifetime of hepatitis virus. In this paper the lifetime of hepatitis viruses (A, B, C) are estimated using Nelson’s method. The results show that the three type of viruses have different lifetime and virus type A has the longest lifetime.
Analisis Hubungan Antara Financial Distress dan Keputusan Kebijakan Dividen Omisi Perusahaan Manufaktur Dwi Putri Antika; Mohamat Fatekurohman; Dian Anggraeni
Limits: Journal of Mathematics and Its Applications Vol 15, No 1 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (376.282 KB) | DOI: 10.12962/limits.v15i1.3390

Abstract

Financial distress adalah kondisi dimana perusahaan mengalami kerugian atau kehilangan, namun belum sampai dikatakan bangkrut. Kondisi yang paling mudah dilihat dari perusahaan yang mengalami financial distress adalah dari keputusan dividen omisi perusahaan. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh dari rasio keuangan seperti likuiditas, leverage, profitabilitas, free cash flow, dan size terhadap durasi waktu antara perusahaan mengalami financial distress dan kemunculan dividen omisi dengan model Cox extended yang diinteraksikan dengan fungsi waktu dan dungsi Heaviside dan untuk mengetahui keberlangsungan perusahaan untuk membagikan dividen. Pada penelitian ini data yang digunakan adalah data rasio keuangan perusahaan manufaktur periode 2016 yang terdaftar di BEI yang telah membagikan dividen selama minimal tiga tahun berturut-turut. Data yang diperoleh dianalisis dengan mendeskripsikan karakteristik setiap variabel, estimasi fungsi survival menggunakan plot Kaplan-Meier, uji perbedaan kurva survival dengan uji Log-Rank, pembentukan model Cox extended dengan fungsi waktu dan fungsi heaviside dan dipilih model terbaik dengan melihat nilai AIC. Hasil dari penelitian ini adalah diperoleh model terbaik Cox extended dengan fungsi heaviside. Variabel yang signifikan adalah profitabilitas (Return on Asset), dan perusahaan yang memiliki profitabilitas yang lebih besar dari 5,98% memiliki risiko mengalami omitted dividend 21% kali lebih kecil daripada perusahaan dengan profitabilitas rendah
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
PENENTUAN LOKASI STRATEGIS AUTOMATIC TELLER MACHINE PT. BANK SYARIAH INDONESIA TBK MENGGUNAKAN METODE DECISION TREE Masruroh Masruroh; Mohamat Fatekurohman; Dian Anggraeni
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 14 No 1 (2022): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2022.14.1.5653

Abstract

ABSTRAK. Lokasi Automatic Teller Machine Bank Syariah Indonesia Tbk (ATM BSI) dapat dianalisis dengan mengambil beberapa data sesuai dengan faktor pendukung yang akan digunakan. Faktor pendukung yang sesuai dianalisis dengan salah satu metode klasifikasi data mining yaitu Desicion Tree untuk menentukan lokasi strategis ATM BSI yang sudah didirikan. Desicion Tree adalah salah satu metode klasifikasi pada data mining berupa pohon keputusan untuk menyelesaikan permasalahan yang diperoleh dan menghasilkan aturan-aturan yang dapat dijadikan sebuah kesimpulan. Hasil perhitungan dengan metode Desicion Tree diperoleh akurasi sesuai dengan tabel confusion matrix untuk data training 100% dengan nilai AUC 1 dan data testing 100% dengan nilai AUC 1 dengan aturan pohon keputusan berdasarkan variabel jumlah penduduk dan jarak ATM ke SPBU. Hasil akurasi menunjukkan sangat baik dan akurat serta model Desicion Tree mampu memprediksi lokasi strategis dan tidak strategis berdasarkan data lokasi yang digunakan. Kata Kunci: Lokasi strategis, Automatic Teller Machine (ATM), Metode Desicion Tree.