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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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Perbandingan Hasil Analisis Cluster dengan Menggunakan Metode Single Linkage dan Metode C-Means Maria Goreti; Yuki Novia Nasution; Sri Wahyuningsih
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (267.086 KB)

Abstract

Cluster analysis is one of the multivariate analysis which is used to classify objects into groups based on similarity of observed variables, in order to obtain the similarity of objects in the same group compared between objects of different groups. Cluster analysis is divided into two methods, they are is hierarchy method that start grouping with two or more objects that have the closest similarity and non-hierarchical method that begin with the process of determining the number of clusters in advance. This study aims is to determine whether there are differences in the results of the cluster grouping formed by using the hierarchy method, that is single linkage method, and non-hierarchical method, that is C-means method. Data, which is taken from the Environment Agency West Kutai, is data Ambient Air Quality Levels in Plantation Company in West Kutai in 2014. The results showed that based on the type of pollutants from all aleven the eleventh plantation companies have different results clusters formed from both methods which were used. With the characteristics of each cluster or groups: single linkage method for the first cluster has good air quality and its members as much as 7 companies, second Cluster both have poor air quality and its members as much as two companies and for the third Cluster have fairly good air quality and its members as much as 2 companies. As for the method of C-means for the first cluster has good air quality and its members as many as four companies, second Cluster both have poor air quality and its members as many as four companies and third Cluster have fairly good air quality and its members as much as 3 companies. For the average value of the ratio of standard deviation in the group (Sw) and between groups (Sb) by using the method of single linkage has a smaller value that is equal to 0.022 while C-means method is equal to 0.063. Thus, in the case of the classification of the ambient air quality in plantation companies in West Kutai 2014, single linkage method better at classifying than C-means method.
Perbandingan Peta Pengendali Rata-rata Bergerak Dengan Peta Pengendali Rata-rata Bergerak Geometrik Nurdayanti Nurdayanti; Darnah Andi Nohe; Rito Goejantoro
EKSPONENSIAL Vol 7 No 2 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

The Moving Average Control Chart is a control chart of data observation for small average shift process. The Geometric Moving Average Control Chart is a control chart of specific weight, making it more effective in detecting the smallest change in process. The purpose of this study is to determine whether the wood width which produced by Suryadi Moulding are controlled by Moving Average and Geometric Moving Average Control Chart, and between the two control chart the research want to know which is the best chart.Based on the results of research in the wood width data obtained that the Moving Average and Geometric Moving Average Control Chart there are no points on the outside of the control limits so that it can be concluded that the wood width which produced by Suryadi Moulding Samarinda on the under controlled conditions. If viewed from the width limit controller chart because of the wide limit on the Geometric Moving Average Control Chart is better than the Moving Average Control Chart because the wide limit on the Geometric Moving Average Control Chart is narrower so the result of this control chart is more accurate.
Pemodelan Faktor-Faktor yang Berpengaruh Terhadap Indeks Pembangunan Manusia (IPM) di Kalimantan dengan Geographically Weighted Logistic Regression (GWLR) Lili Widyastuti; Desi Yuniarti; Memi Nor Hayati
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (596.241 KB)

Abstract

Human Development Index (HDI) is an indicator to measure the success in building the quality of human life (community/population) and HDI can be used to see the results of the development. The average of Kalimantan HDI in 2016 has low HDI value however there is also high HDI value. Be observed from the score of those HDI, Kalimantan only has two categories those are medium and high. The statistical method used for determining the IPM model is the Geographically Weighted Logistic Regression (GWLR) method. GWLR is a local form of logistic regression in which geographic factors are considered and it is assumed that the data distributed Bernoulli are used to analyzing spatial data. This research was conducted to know the model of HDI and the factors that influence HDI in Kalimantan with GWLR using Adaptive Bisquare Kernel. The results showed that by using Adaptive Bisquare Kernel there are 56 different models for each district/city with the factors that affect the HDI in Kalimantan in 2016 vary by district/city as follows; the percentage of the poor population, the percentage of open unemployment, the percentage of the population graduated from college.
Perbandingan Hasil Revised Distribution Method dan Metode Stepping Stone dengan Penentuan Nilai Awal Menggunakan Metode North West Corner dalam Meminimumkan Biaya Pendistruibusian Barang Zulaiha Eka Saputri; Yuki Novia Nasution; Wasono Wasono
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 (469.36 KB)

Abstract

Globalization and free trade era make the distribution of goods as if not limited by region. In the process of distribution of goods, cost calculation becomes a very important factor, to minimize the cost of distribution, it is necessary to apply a transportation modeling. Revised Distribution Method (RDI) is a method of transportation that does not use initial solutions in its completion. The RDI method is different with the Stepping Stone Method that uses the initial solution to determine the optimal solution. The purpose of this research is to minimize the cost of distribution of LPG gas 3 Kg using RDI and Stepping Stone method and then compare the two methods to see optimal results. The result shows that RDI method has 10 iterations with minimum cost of Rp 26.719.520,- thus saving 41% with cost difference of Rp 18.280.480,- from previous transportation cost of Rp 45.000.000,- while Stepping Stone method has 4 iterations with result a minimum charge of Rp 24.000.000,- thus saving 47% with a difference of Rp 20.968.000,- from the previous fee of Rp 45.000.000,-. So it can be concluded that the stepping stone method is a more appropriate method to minimize the amount of transportation costs at PT. Tri Pribumi Sejati.
Pemodelan Geographically Weighted Regression (Gwr) Dengan Fungsi Pembobot Adaptive Kernel Bisquare Untuk Angka Kesakitan Demam Berdarah di Kalimantan Timur Tahun 2015 Aditiya Risky Tizona; Rito Goejantoro; Wasono Wasono
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Dengue Fever in East Borneo is thought to be a spatial problem that affected by geographic factor and linear regression analysis that is often can not describe with Good Relations pattern. The solution for this problem can be solved using Geographic Weighted Regression Method (GWR) to review and Troubleshooting geographic factor. This research Model proposed to consider GWR model with geography factor or location as the weight to estimate the model parameters, the weight type that used for this research is Adaptive Bisquare. Based on the analysis, this research revealed different model to every observations and different indicators. The eight locations are Paser, Kutai Kartanegara, West Kutai, East Kutai, Berau, Balikpapan, Samarinda dan Bontang. Those locations have variable that affected the morbidity number of dengue fever equally specifically house, elementary school facilities and public place that do not meet the requirements of health, and also waste transported while for the observation location of Penajam Paser Utara has the affected variable of dengue fever morbidity number equally which are house, waste transported, elementary school facilities and public place that do not meet the requirements of health, and also the citizen that do not have the healthy and hygienic lifestyle pattern.
Klasifikasi Lama Masa Studi Mahasiswa Menggunakan Perbandingan Metode Algoritma C.45 dan Algoritma Classification and Regression Tree Hadi Dwi Darmawan; Desi Yuniarti; Yuki Novia Nasution
EKSPONENSIAL Vol 8 No 2 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Classification is the grouping samples based on the characteristics of the similarities and differences using target variable category. In this study, the decision tree is formed using C4.5 algorithm and Classification and regression tree (CART) algorithm to classify a student’s study period class of 2016 FMIPA UNMUL. C4.5 algorithm is a non binary classification tree where the branches of trees can be more than two on C4.5 algorithm, decision tree is established based on Entropy value. The purpose of CART algorithm is to get an accurate data as group identifier of a classification. CART can be applied in three main steps, namely the establishment of a classification tree, trimming of the classification tree, and determination of optimal classification tree. The main goal of this research is to determine factors which may effect on all predicate graduation who was graduated on 2016 using C4.5 algorithm and CART algorithm and also to know comparison accuracy of classification result by C4.5 algorithm and CART algorithm. The result showed that factors which affected the duration of all graduation using C4.5 algorithm are major (X4), region school (X5) and region origin (X3) and factors affected to the duration of all graduation using CART algorithm are major (X4) and Cumulative Achievement Index (X1). Precision classification in CART algorithm is better than C4.5 algorithm. C4.5 algorithm was able to predict with 40% accuracy while the CART algorithm has a predictive accuracy of 60%.
Penerapan Metode Vogel’s Approximation Method (VAM) dan Modified Distribution (MODI) Dalam Penyelesaian Transshipment Problem Aisyah Aisyah; Ika Purnamasari; Yuki Novia Nasution
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Transshipment method is an extension of the transportation method. The method of transhipment itself can not be directly to the destination becausethe goodstransported must experience transit, while the method of transporting direct shipment from factory to destination. The data used in this study is data that has been obtained from PT. Nestle Balikpapan Where the data is processed by using the VAM method as a method of initial solution and MODI Method as a Final solution, the data aims to find out whether by using both of methods can reduce operational cost of PT. Nestle Balikpapan and the difference of operational cost before application and after using both of that method. Based on the results of the research can be obtained that by using the Initial Solution Solution with VAM can minimize the cost of 43,54% of the initial cost and continued with the final Solution Method that is MODI for the optimality testing by reduced 44,14%
Peramalan dengan Metode Seasonal Autoregressive Integrated Moving Average (SARIMA) di Bidang Ekonomi Verawaty Bettyani Sitorus; Sri Wahyuningsih; Memi Nor Hayati
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

A present event is probably a reiteration from a past event. The reiteration of an event every particular time period indicates seasonal pattern. Seasonal Autoregressive Integrated Moving Average (SARIMA) is one of the methods that is used for data forecasting which has seasonal pattern. The purposes of this research are finding out the best SARIMA model and forecasting the inflation in Indonesia for period January 2016 until December 2016 using the best SARIMA model. Sample of this research is 96 Indonesia inflation data (mtm) for period January 2008 until December 2015. The technique of this research is purposive sampling. There are five steps of SARIMA method, those are model identification, model estimating, diagnostic checking, selecting the best model, and forecasting. Based on the analysis, the best SARIMA model is SARIMA (1,0,0)(0,1,0)12. The forecasting of Indonesia inflation 2016 has similar pattern with the previous time. The inflation increases in January 2016 and decreases in February 2016 until April 2016. The inflation increases again in Mey 2016 until August 2016 and decreases in September 2016 until November 2016. At last, the inflation increases in December 2016.
Penerapan Analisis Joint-Space dan Analisis Faktor dalam Persepsi Mahasiswa FMIPA UNMUL terhadap Penggunaan Aplikasi Messenger pada Smartphone Emi Harmianti; Ika Purnamasari; Memi Nor Hayati
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (217.243 KB)

Abstract

Multidimensional Scaling Analysis (MDS) is a technique that can be used to determine the relative views of respondents to an object which is then represented in a multidimensional map. Joint-Space Analysis is a type of MDS that aims to determine the coordinates of the position of each object and variable pictured together on a map perception (perceptual map). While the factor analysis is a branch of multivariate analysis to determine the factors of concern to respondents. This study aims to determine the position of messenger applications on smartphones based on attributes that are owned, as well as to identify factors that concern respondents in choosing the messenger application based on attributes of the messenger application by the respondents are students FMIPA UNMUL. The data used in this research is primary data from research by spreading the questionnaire with the number of respondents (students FMIPA UNMUL) as many as 100 people. Results from this study indicate that the BlackBerry Messenger application, LINE, WhatsApp best position with all superior attributes that exist within the application.While the application KakaoTalk third place with some excellent attributes of the display, application updates, promotions, connection, performance applications, contacts and groups, stickers and emoticons, as well as account settings. Meanwhile, the Yahoo Messenger application and WeChat is the weakest of applications in a variety of attributes that exist in the messenger application. From the results of the factor analysis, found that there are two factors that concern the consumer in choosing a smartphone messenger app that attribute connections and promotion.
Pemodelan Regresi Weibull Pada Data Kontinu Yang Diklasifikasikan (Studi kasus: Data Indikator Pencemaran Air Dissolved Oxygen Pada DAS Mahakam Kalimantan Timur Tahun 2020) Sudarman, Alfiannur Rizki; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 14 No. 1 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v14i1.993

Abstract

Weibull regression model is a Weibull distribution that is directly influenced by covariates. Weibull regression models discussed in this study are Weibull survival regression model, Weibull hazard regression, and Weibull mean regression. The Weibull regression model in this study was applied to water pollution indicator of dissolved oxygen (DO) data in the Mahakam watershed of East Kalimantan in 2020. The purpose of this study was to obtain a Weibull regression model for water pollution indicator of DO data, to obtain the factors that influence the Weibull regression model, and to interpretation the Weibull regression model of water pollution indicator of DO data. The study’s result is that the Newton-Raphson iterative approach was used to find the approximate of maximum likelihood estimator. Based on the hypothesis testing, it is concluded the factors that influence the water pollution indicator of DO data the Mahakam watershed in 2020 are total suspended solid (TSS), total dissolved solid (TDS), nitrate and ammonia.

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