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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 205 Documents
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Penerapan Model Geographically Weighted Logistic Regression Pada Data Status Kesejahteraan Masyarakat di Kalimantan Tahun 2017 Pratiwi, Nadya; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (776.692 KB) | DOI: 10.30872/eksponensial.v11i1.648

Abstract

Geographically Weighted Logistic Regression (GWLR) model is a regression model developed from logistic regression which is applied to spatial data. The aims of research is a GWLR model determination on dichotomous data of community welfare status based on the Human Development Index (HDI) and to find the factors influencing the probability of high welfare status of each Regency/City on Kalimantan Island in 2017. Parameters estimation of the GWLR model was done at each observation location using a weighted Maximum Likelihood Estimation (MLE) method and maximum likelihood estimator was obtained by Newton Raphson iterative method. Spatial weighting on parameter estimation was determined using Adaptive Gaussian weighting function and optimum bandwidth was determined using Generalized Cross-Validation (GCV) criterion. Based on the result of GWLR parameter testing, it was concluded that the factors influencing the probability of high welfare status of Regency/City on Kalimantan Island in 2017 were school enrollment rates (senior high school), the number of health workers, real per capita income and the open unemployment rate.
Penerapan Metode Fuzzy C-Means Pada Pengelompokan Kabupaten/Kota di Pulau Kalimantan Berdasarkan Indikator Kesejahteraan Rakyat Tahun 2020 Nurmin, Deviyana; Hayati, Memi Nor; Goejantoro, Rito
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (944.672 KB) | DOI: 10.30872/eksponensial.v13i2.1068

Abstract

Clustering is a method of grouping data into several clusters or groups so that data in one cluster has a high level of similarity and data between clusters has a low level of similarity. The clustering method used in this research is Fuzzy C-Means (FCM). FCM is a data grouping technique in which the existence of each data point in a cluster is determined by the degree of membership. To optimize the grouping results, it is necessary to validate the number of clusters using Partition Coefficient (PC). The purpose of this study is to obtain optimal grouping results from the FCM method using the PC validity indices from the people's welfare indicator data in 56 regencies/cities on the island of Kalimantan in 2020. Based on the results of the analysis, the conclusion is that the optimal number of clusters is three clusters. The first cluster consists of 24 regencies/cities on the island of Kalimantan, the second cluster consists of 17 regencies/cities on the island of Kalimantan, and the third cluster consists of 15 regencies/cities on the island of Kalimantan.
Penentuan Rute Terpendek dengan Menggunakan Metode Algoritma Clarke and Wright Savings Damayanti, Dwi Kartika; Purnamasari, Ika; Wasono, Wasono
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (722.012 KB) | DOI: 10.30872/eksponensial.v12i1.762

Abstract

Operations research is a method regarding retrieval optimal decisions in the modeling of systems, both deterministic or probabilistic orginating from real life. One of the operations research methods is The Clarke and Wright savings algorithm, which is an exchange procedure, where a set of route at each step is exchange to get a better set of routes. This method is often referred to as a method. In this research, the Clarke and Wright savings algorithm is used to find out the distribution route and the minimum costs incurred on saving. On distribution of Bottled Water (AMDK) to determine how large savings that occur on the distribution route AMDK. Bottled Water (AMDK) is drinking water that is ready to be consumed directly without having to go through the heating process first. To determine the distribution route using the Clarke and wright savings method, a depot distance matrix is made to customer and from the customer to the customer and then continues to make the clarke and wright savings matrix. After searching for the shortest route using the clarke and wright savings method, the savings value is obtained to determine the customer’s route by sorting from the largest to the smallest value. In region 1 there were 5 trips with a total distance of 210.21 km, in region 2 there were 4 trips with a total distance of 191.35 km, in region 3 there were 5 trips with a total distance of 143.85 km, in region 4 there were 5 routes with a total distance 108.24 km, and in region 5 6 trips were obtained with a total distance of 113.95 km. The total distance travelled to deliver gallons to all routes is 767.59 km.
Model Regresi Cox Weibull Dengan Metode Penaksiran Parameter Efron Partial Likelihood: Studi Kasus : Lama Perawatan Pasien Penderita Tuberkulosis Di Puskesmas Loa Ipuh Tenggarong Tahun 2017 Ihsan, Ihsan; Suyitno, Suyitno; Wahyuningsih, Sri
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (746.089 KB) | DOI: 10.30872/eksponensial.v11i1.639

Abstract

Survival analysis is an analysis that involves statistical tests to analyze data on the time or length of time until the occurrence of a particular event. One regression model for time duration data modeling is the Cox PH regression model. Cox PH regression applied to time duration data with Weibull distribution is called Cox PH Weibull regression. The purpose of this study is to obtain a Cox PH Weibull regression model and determine the factors that influence the length of treatment for tuberculosis patients. The parameter estimation in this study is Efron partial likelihood method. The Efron partial likelihood method is suitable for estimating Cox PH regression parameters to data containing ties. Based on the results of parameter estimation the best model is obtained by using AIC crtiteria. Based on the partial test, age is factor that influence to the length of treatment. The results of the study show that every increasing age patient one year, then length of treatment until the patient recovered, will increas 1,024 times.
Analisis Model Intervensi Fungsi Step Ganda untuk Peramalan Inflasi Indonesia Masrawanti Masrawanti; Sri Wahyuningsih; Memi Nor Hayati
EKSPONENSIAL Vol 10 No 2 (2019): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (730.662 KB)

Abstract

The intervention model is one time series model that can be used to explain the impact of an intervention caused by external or internal factors that occur in a time series data. This model can also be generally used to explain structural changes in a time series data. The purposes of this study are to determine the intervention model of double step function on the increase of the price of fuel oil to the Indonesia’s inflation (yoy), and forecasting Indonesia's inflation (yoy) period 2018. The government's policy to increase of the price of fuel oil in June 2013 and November 2014 is a step intervention because impact of the intervention is permanent. The procedure of forming an intervention model is a double step function that is determining the intervention function that occurs during the research period, dividing the data based on the time of the intervention, modelling, estimating parameters, testing diagnostics, and selecting the best model. Next stage is forming the first and second intervention models. The best model for predicting Indonesia's inflation (yoy) isSARIMA (0,1,1) (1,0,0)12 as the model before the intervention with the order of the first intervention responseand the second intervention response order . The results of forecasting Indonesia's inflation (yoy) in the period 2018 will placed around the average inflation amount 3%.
Penerapan Metode Choice Based Conjoint Hidaya Annur; Desi Yuniarti; Ika Purnamasari
EKSPONENSIAL Vol 10 No 1 (2019)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (542.99 KB)

Abstract

Lecturer is an important factor in the process of teaching and learning process in universities. This study was conducted with the aim to know the characteristics of students of Statistics Program Department of Mathematics at FMIPA Mulawarman University on the characteristics of the expected lecturers. One method that can be used to know the options is the conjoint-based optional method. Choice Based Conjoint (CBC) is a conjoint analysis that measures preferences based on conceptual choices and is used to determine the concept of attributes of lecturer characteristics expected by students. Attributes used in this study are the background of lecturers, lecturer characters, learning methods and interaction in the class. The data analysis technique used in the conjoint-based optional method is the conditional logit model. The result of CBC analysis shows that the attribute that is considered most important by the respondents based on attribute importance value is classroom interaction with percentage of 48,41% and seen from the value of the utility of interaction in the class with a positive value is the interaction in the active class with a value of 1.331. The characteristics of lecturers that are expected to be possessed by lecturers are casual lecturer character, last doctoral education, creative teaching methods and active classroom interaction.
Perbandingan Metode Bootstrap Dan Jackknife Resampling Dalam Menentukan Nilai Estimasi Dan Interval Konfidensi Parameter Regresi Dessy Ariani; Yuki Novia Nasution; Desi Yuniarti
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (549.691 KB)

Abstract

Regression analysis is a study that describes and evaluates the relationship between an independent variable and the dependent variable for the purpose of estimating or predicting the value of the dependent variable based on the value of the independent variables. Resampling is used when samples obtained for analyzing is less. In this study, Bootstrap method and Jackknife method are using. Both methods are used to find the value of regression parameter estimates and confidence intervals of regression parameter values which applied to the data position of Public Deposits in four groups of banks : Persero Banks, Government Banks, National Private Banks and Foreign Banks to knowing the best resampling methods to find the value of regression parameter estimates and confidence intervals of regression parameter values. There are three independent variables which are used in this study, namely investments loans, working capital loans and consumer loans. From the research results, it is obtained that the Jackknife method is the most appropriate method because it has smaller standard error values so Jackknife methods have a narrow range confidence intervals.
Aplikasi K-Nearest Neighbor Dengan Fungsi Jarak Gower Dalam Klasifikasi Kelulusan Mahasiswa: Studi Kasus : Mahasiswa Program Studi Statistika, Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Mulawarman Fadil, Irfan; Goejantoro, Rito; Prangga, Surya
EKSPONENSIAL Vol. 13 No. 1 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (649.085 KB) | DOI: 10.30872/eksponensial.v13i1.881

Abstract

The results of the reaccreditation of the Statistics Study Program, Mulawarman University in 2019 remain accredited B. One of the assessment indicators used in reaccreditation is the student's timely graduation status. Therefore, it is necessary to predict the graduation status of Statistics students, Mulawarman University.. The prediction method used in this research is K-Nearest Neighbor (K-NN). K-NN is a classification method based on studying previously classified data. This method is very easy to understand, easy to applied and also non-parametric method, so that no certain assumptions are needed in the process. The independent variables used in this study were student profiles, including gender, regional origin, cumulative Grade Point Average (GPA) and single tuition fee. The dependent variable in this study is the graduation status of students, namely graduating on time and not graduating on time. The data used were students of the Mulawarman University, Statistics Study Program in 2014, 2015, and 2016. The results showed at k = 7 and the distribution of training and testing data with the proportion of 80:20 obtained optimal accuracy of 0,909 with a TPrate of 0.500, a TNrate. in the amount of 1,000 and AUC value of 0,75 that means fair classification.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (711.284 KB)

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%.
Perbandingan Diagram Kontrol Demerit dan Fuzzy u: Studi Kasus : Kecacatan Produk Kayu Lapis (Plywood) di PT. Segara Timber Mangkujenang, Samarinda Provinsi Kalimantan Timur Tahun 2019 Septilasse, Rebeka Norcaline; Goejantoro, Rito; Wahyuningsih, Sri
EKSPONENSIAL Vol. 11 No. 2 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (716.267 KB) | DOI: 10.30872/eksponensial.v11i2.663

Abstract

Control chart is a graph that provides a picture of a running process whether under controlled conditions or not. Demerit control chart and fuzzy u control chart are very suitable for production quality control. This study was applied to the data of defects of plywood products at pt. segara timber, samarinda, east Kalimantan in 2019. The purpose of this study is to get the results of a comparison of the decision of Demerit control chart and fuzzy u control chart. The results of this study shows the demerit control chart is more thorough than the fuzzy u control chart due to the demerit control chart found 12 out of control observations and the fuzzy u control chart only found 1 out of control observations.

Page 11 of 21 | Total Record : 205

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