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Meiliyani Siringoringo
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Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman Jl. Barong Tongkok, Kampus Gunung Kelua Kota Samarinda, Provinsi Kalimantan Timur 75123
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INDONESIA
Eksponensial
Published by Universitas Mulawarman
ISSN : 20857829     EISSN : 27983455     DOI : https://doi.org/10.30872/
Core Subject : Economy, Science, Education,
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Other
Jurnal Eksponensial is a scientific journal that publishes articles of statistics and its application. This journal This journal is intended for researchers and readers who are interested of statistics and its applications.
Arjuna Subject : Matematika - Statistik dan Probabilitas
Articles 12 Documents
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Search results for , issue "Vol 8 No 2 (2017)" : 12 Documents clear
Perbandingan Kinerja Metode Klasifikasi Chi-square Automatic Interaction Detection (CHAID) dengan Metode Klasifikasi Algoritma C4.5 pada Studi Kasus : Penderita Diabetes Melitus Tipe 2 Di Samarinda Tahun 2015 Muhammad Faisal; Yuki Novia Nasution; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

C4.5 algorithm is tree classification where tree branches can be more than two. In C4.5 algorithm, the decision tree is based on entropy and gain criterias. Chi-Squared Automatic Interaction Detection (CHAID) classification method is a methods which is used to divide data to become a smaller groups based on categorical dependent and independent variables. The purpose of this research is to determine the classification process by C4.5 algorithm and CHAID method for DM type 2 patients. Risk factors for diabetes type 2 are Decline, Age, Gender, Status of Obesity, Diet, and Sports Activity based on the availability of source data from the Hospital of Abdul Wahab Sjahranie Samarinda. The results show that factors which significantly affect the DM type 2 patients are Obesity and Sport Activity. While by using CHAID, the factors which significantly affect the patients are Decline, Obesity, Diet and Sports Activity. The Classification result accuracy of the C4.5 algorithm is 90% and 94% for CHAID method.
Peramalan Harga Minyak Mentah Dunia (Crude Oil) Menggunakan Metode Radial Basis Function Neural Network (RBFNN) Ayu Wulandari; Sri Wahyuningsih; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Forecasting is a technique to estimate a value in the future with past data and current data. One of the forecasting method that includes neural network is Radial Basis Function Neural Network (RBFNN). In this research, RBFNN method is used to get the best model and to forecast world crude oil price (US$) data. World crude oil prices forecasting is very important for many stakeholder, both from the government sector, business entities and investors so that all activities can go according to plan. In the RBFNN method, the network input and the number of hidden layers is very influential to get the best model from RBFNN and also the forecasting. To get the best model by using network input determination by identifying the Partial Autocorrelation Function (PACF) lag, and to determine the number of hidden layers by the K-Means cluster method. Results of the research showed that from the training data, the best model of RBFNN is using 2 network inputs Xt−1 and Xt−2 and 3 hidden layers with Mean Absolute Percentage Error (MAPE) accuracy level is 6,8150%. With the model, for the next period from June 2017 to December 2017 the world crude oil price (US $) shows a downward trend.
Penerapan Metode Analisis Regresi Logistik Biner Dan Classification And Regression Tree (CART) Pada Faktor yang Mempengaruhi Lama Masa Studi Mahasiswa Chairunnisa Chairunnisa; Yuki Novia Nasution; Ika Purnamasari
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Binary Logistic Regression is one of the logistic regression analysis which is used to analyze the relationship between a dichotomous dependent variable with several independent variables. Classification and Regression Tree (CART) is one of the methods that developed to perform classification analysis on dependent variables either on nominal, ordinal, or continuous scale. In this research, Binary Logistic Regression method and Classification and Regression Tree (CART) applied to the data of the students at Faculty of Math and Natural Science Mulawarman University graduated in year 2016 to determine the characteristic of student which is classified according to two categories that is the study period less than or equal to 5 years and study period more than 5 Years, with five independent variables namely GPA Graduates (X1), Gender (X2), Type of Junior School (X3), Domicile (X4), and Major (X5). Factors that influence the study period of the students based on Binary Logistic Regression method are GPA, Gender, Secondary School Type and Major. The result of classification by using CART method is the student who have the study period less than or equal to 5 Years is a student from Chemistry major or have GPA between 3,51 and 4,00, while the study period more than 5 Year is the student who have GPA between 2,00 and 2,75; 2,76 and 3,50. In terms of classification accuracy, Binary Logistic Regression method was able to accurately predict the observation as much as 75.0%, while the CART method was able to accurately predict the observation as much as 77.27%.
Analisis Data Kejadian Berulang Tidak Identik Dengan Cox Gap TimeModel Andi Widya Rhezky Awalul Aziz; Yuki Novia Nasution; Sri Wahyuningsih
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

The gap time method is a method that can be used in recurrent event Time-based modelling. Gap analysis is often useful when events are relatively uncommon, when the object of the study is the prediction of time for the next event, or on the phenomenon of circulation.The analysis of model for non-identical recurrent events using survival time in the form of gap time is called Cox Gap Time Model. The purpose of this research is to know Cox Gap Time model for recurrent occurrence in DM type II disease and to know the factors that influence repetitive incident in DM type II disease in RSUD A. W. Sjahranie Samarinda. The variables in this research are age, treatment, status and relapse time (gap time). The study was conducted by using 263 medical records data of DM type II patients admitted to the hospital during observation period in January 2015 until December 2016. The results shows that age factor affects the first gap time and there are age, gap 1 covariate and gap 2 covariate that have significant effect aga inst to the third gap time variable, meanwhile there is no variable affects the second gap time.
Pemodelan Jumlah Kematian Bayi di Provinsi Nusa Tenggara Timur Tahun 2015 Dengan Regresi Poisson Pratama Yuly Nugraha; Memi Nor Hayati; Desi Yuniarti
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Poisson regression is one of the non-linear regression analysis whose response variable is modeled with Poisson distribution. The parameter estimation Poisson regression model using Maximum Likelihood Estimation (MLE). This study aims to model the number of infant mortality in East Nusa Tenggara Province in 2015 and what factors affect the occurrence of cases of infant mortality in East Nusa Tenggara Province using Poisson regression. The results of research with Poisson regression factors influencing the number of infant mortality is the number of deliveries assisted by health personnel (x1), the percentage of pregnant women receiving FE3 tablets (x2), the number of obstetric complications handled (x4), the percentage of low birth weight babies (x5), the number of exclusively breastfed babies (x6), the percentage of households Live clean and healthy (x7), and the number of deliveries is helped by non-medical personnel (x8).
Analysis of (M/G/c): (GD/∞/∞) Menggunakan Software Lazarus Akbar Maulana; Yuki Novia Nasution; Nanda Arista Rizki
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Queueing theory is a theory that concerns in the mathematical study of queue or row of waiting. The formation of the queue is occurs when the need for a service exceed the capacity of the service. In this study, an analysis is done to determine whether the queue model (M/G/c) :(GD/∞/∞) can be applied to the Workshop of Utomo Motor Yamaha Samarinda Seberang. Primary data is used and is taken for 3 days in a random busy period selected in May to August 2017. The result is the queue system on Utomo Motor Yamaha using FCFS queue discipline with 4 parallel mechanics, and follows the (M/G/4) :(GD/∞/∞) model. The average of the waiting time in the queue on Monday is 0,38 hours and Wednesday is 0,35 hours. The average of the customers in the queue on Monday and Wednesday is the same as much 2 customer. The average of the customers in the system on Monday and Wednesday is the sama as 5 customers. The average of the waiting times that customers spend on the system on Monday is 0,93 hour and Wednesdayis 0,94 hours and on May 22nd, 2017 is 0,81 hours. In order to calculate the queue model more quickly, a program is made using Lazarus software to search the queue model on daily data.
Penaksiran Parameter dan Pengujian Hipotesis Model Regresi Weibull Univariat Suyitno Suyitno
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (509.861 KB) | DOI: 10.30872/eksponensial.v8i2.41

Abstract

In this study, a univariate Weibull regression model is discussed. The Weibull regression is a regression model developed from the Weibull distribution, that is the Weibull distribution depending on the covariates or the regression parameters. The univariate Weibull regression (UWR) model can involve the survival function model and the mean model of the response variable with the scale parameter stated in the terms of the regression parameters. The aim of this study is to estimate the UWR model parameters using the maximum likelihood estimation (MLE) method, and to test the regression parameters. The result shows that the closed form of the maximum likelihood estimator can not be found analytically, and it can be approximed by using the Newton-Raphson iterative method. The regression parameters testing involves simultaneous and partial test. The test statistic for simultaneous test is Wilk's likelihood ratio. Wilk statistic follows Chi-square distribution, which can be derived from the likelihood ratio test (LRT) method. The test statistic for partial test is Wald and it follows standard normal distribution. The alternative test statistik for partial test is squared of Wald statistic, where it follows Chi-square distribution with one degree of freedom.
Klasifikasi Persediaan Barang Menggunakan Analisis Always Better Control (ABC) dan Prediksi Permintaan dengan Metode Monte Carlo Ricca Noviani; Yuki Novia Nasution; Nanda Arista Rizki
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

ABC analysis is a method of inventory control to manage a small number of item but has a high utilization. Inventories are categorized into three classes A, B, and C. The objective of the research is to manage the inventories using ABC analysis, EOQ, ROP, and to provide an overview of the next-year demand of the drug items using Monte Carlo method. ABC analysis results show that out of 79 drug items, class A consists of 19 drug items with usage value 69,11%, class B consists of 19 drug items with usage value 20,29%, and class C consists of 41 drug items with usage value 10,60%. Based on economic order quantity method, minimum ordering quantity of drug are two items and maximum ordering quantity of drug are 96 items.Based on reorder point method, the minimum quantity of drug for reordering is zero item and the maximum quantity of drug for reordering are seven items. Monte Carlo method results show that Fludane Plus 60 ml has the minimum demand on January - Desember 2017 which is only one bottle a month and Actifed Cough Merah 60 ml has the maximum demand which is 78 - 81 bottles a month. Lapisiv 100 ml, Kamulvit B12 Sirup 120 ml, Fludane Plus 60 ml and Miconazole 2% has the highest accuration with the percentage of error 0% and Ikadryl DMP Sirup 100 mlhas the lowest accuration with the percentage of error 0,22%.
Penerapan Metode If-Then dari Rough Set Theory dalam Menangani Kecelakaan Lalu Lintas di Kota Samarinda Tahun 2016 Martua Tri Januar Sinaga; Rito Goejantoro; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Traffic accidents have caused many victims and lost materials, so itbecomes one of casesneed special attention every year. Therefore, it required a serious treatment to avoid the incidence of traffic accidents, so it can reduce the number of victimsbe inflicted. The aim ofthis study to determine the greatest factor/conditioncausing the fatality rate of traffic accidents and to determine the rules of decision rules from data that has been collected. The data used was secondary data taken from the report of traffic accidents recapitulation at Laka Lantas Unit, Satlantas Samarinda City. The analytical methods used to analyze the data are descriptive statistics analysis and Rough Set Theory. Based on the result, it can be seen the largest frequency of the victim who died is in traffic accidents that occur in sunny conditions. Moreover it is obtained 53 decision rules from the fatalities of victims by the traffic accidents in Samarinda City. The most powerful rule is "if a male student involved in a traffic accide nt at residential area and the road condition feasible passed by vehicles then the victim is likely to get serious injuries" with weight of 0.80.
Pemodelan Penduduk Miskin di Provinsi Maluku Dengan Menggunakan Metode Backward Salmon N. Aulele; Henry W. M. Patty
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Poverty is a complex issue, for it is not only related to the low level of income and consumption, but also to the low level of education, health and powerlessness to participate in development as well as various issues that are relevant to human development. According to the Badan Pusat Statistik (BPS), poverty is the inability to meet certain standards of basic needs, both food and non-food. The results of BPS survey on March 2017 showed that Maluku Province is ranked 4th in the poorest province in Indonesia with a poverty percentage of 18.45% of the total population in Maluku. This study aims to analyze the number of poor people in Maluku and its affecting variables by using backward method. The results show that Southwest Maluku Regency has the highest percentage of poor people in Maluku 31.01% and Ambon City has the lowest percentage of poor people with 4.64% of the poor. While the significant variables which affecting the percentage of poor people in Maluku are the percentage of households whose fuel for cooking is from wood; the percentage of population aged 7-24 years who is not / has never attended school; the percentage of population aged 7-24 years no longer schooling; the percentage of open unemployment rate; and the percentage of labor force participation rate per Regency/City in Maluku.

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