cover
Contact Name
Meiliyani Siringoringo
Contact Email
meiliyanisiringoringo@fmipa.unmul.ac.id
Phone
+6285250326564
Journal Mail Official
eksponensial@fmipa.unmul.ac.id
Editorial Address
Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Mulawarman Jl. Barong Tongkok, Kampus Gunung Kelua Kota Samarinda, Provinsi Kalimantan Timur 75123
Location
Kota samarinda,
Kalimantan timur
INDONESIA
Eksponensial
Published by Universitas Mulawarman
ISSN : 20857829     EISSN : 27983455     DOI : https://doi.org/10.30872/
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.
Articles 205 Documents
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (972.023 KB)

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.
Analisis Diagram Kontrol Fuzzy U: Studi Kasus: Kecacatan Produk Kayu Lapis (Plywood) di PT. Segara Timber Mangkujenang, Samarinda Provinsi Kalimantan Timur Tahun 2018 Fauzia, Rina; Yuniarti, Desi; Hayati, Memi Nor
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 (854.197 KB) | DOI: 10.30872/eksponensial.v11i1.647

Abstract

Fuzzy in general means that an element can be classified into two sets simultaneously. Fuzzy control diagrams are very suitable to be used for observations that produce information (data) that is uncertain, unclear and based on one's subjectivity. This study was applied to data on plywood products in PT. Segara Timber, Samarinda, East Kalimantan Province in 2018. The purpose of this study is to get the results of the decision fuzzy u control diagram. Based on the results of the use of the fuzzy control diagram u produce the most found decisions are rather in control that is equal to 26 observations, while the second most is rather out of control that is equal to 22 observations, and out of control that is equal to 14 and in control of 5 out of 67 observation.
Penerapan Metode Full-Profile Dalam Pengumpulan Data Untuk Analisis Konjoin Roy Tridoni Situmorang; Desi Yuniarti; Ika Purnamasari
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Conjoint analysis is an analytical technique that is used to examine the impact of attributes of goods or service. Conjoint analysis can be applied to know the attribute that become the main choice of student of Mulawarman University in choosing GSM prepaid card product. Where the attribute used are SMS tariff, phone tariff, internet package, signal and bonuses. The purpose of this study is to know the combination of attribute level which is most interested by student and relative importance value from each attribute. The result of this study is the combination of attributes of the GSM prepaid card that the student are interest in are the SMS package tarif with the utility value is 1,445, the phone tarif per minute with the utility value is 0,525, full 4G internet package with the utility value is 2,51, strong signal with the utility value is 1,895, SMS bonus with the utility value is 1,42. The attribute that become the student’s preferred choice in choosing GSM prepaid card is internet package with the relative importance value is 0,352.
Aplikasi Data Mining Market Basket Analysis untuk Menemukan Pola Pembelian di Toko Metro Utama Balikpapan Nadya Rahmawati; Yuki Novia Nasution; Fidia Deny Tisna Amijaya
EKSPONENSIAL Vol 8 No 1 (2017)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

The development of information technology in the transaction process in supermarkets compete to improve the quality and utility in order to achieve dissemination of information easily and quickly which is accurate and effective. This situation encourages the development of techniques that automatically find the relationship between item in the database. This study aims to analyzing and knowing association rules formed by using apriori algorithm. Market basket analysis’s steps are doing descriptive analysis, grouping the data transactions, applying apriori algorithm on the data, calculating the value of support and calculating the value of confidence. With the value of the minimum support 10% and minimum value of confidence 40%, the results obtained are one rule of association on the first day, four rules of association on the second day, one rule of association on the third day, four rules of association on the fourth day, six rules of association on the fifth day, nine rules of association on the sixth day, and four rules of association on the seventh day.
Peramalan Dengan Menggunakan Metode Double Exponential Smoothing Dari Brown Etri Pujiati; Desi Yuniarti; Rito Goejantoro
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Consumer Price Index (CPI) is one of the economic indicator that givethe information about the price of goods andservices which paid by consumer. CPI in Samarinda City increases so long which the pattern of the data is indicating a trend pattern. Time series forecasting designed to handle the trend of data which used a double exponential smoothing method. The purpose of this study is to determine the using of the parameters α and the forecasting amount of CPI in Samarinda City for three months that use double exponential smoothing method. The best parameter α which use to forecast CPI in Samarinda City is (0,61). To forecast CPI in Samarinda City is using double exponential smoothing method obtained F72+m=119,83+1,62 m. The forecasting result of CPI in Samarinda City from January to March 2015 are 121,44, 123,06, and 124,68.
Optimasi Fuzzy C-Means Menggunakan Particle Swarm Optimization Untuk Pengelompokan Kabupaten/Kota Di Pulau Kalimantan (Studi Kasus: Data Indikator Kesejahteraan Rakyat Tahun 2020) Deviyana Nurmin; Memi Nor Hayati; Rito Goejantoro
EKSPONENSIAL Vol 14 No 1 (2023): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (948.946 KB) | DOI: 10.30872/eksponensial.v14i1.1002

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.
Penyelesaian Assignment Problem Dengan Menggunakan Metode Program Dinamis: (Studi Kasus : CV. Sinar Utama) Karundeng, Franklin Peter Anton; Purnamasari, Ika; Yuniarti, Desi
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.358 KB) | DOI: 10.30872/eksponensial.v12i2.806

Abstract

Assignment problem that maximize profits or minimize time, distance and cost by placing the appropiate workforce with ability. Solving the assignment problem can be done by dynamic program method. To apply the dynamic program method the number of sources assigned should be equal to the number of tasks to be completed.Otherwise each source should be assigned only for one task. The purpose of this study is to determine the minimum total time of completion of work and know the assignment of employees has been optimal. The data used is the time of assignment of employees completing the work on the worksop in showroom CV. Sinar Utama of Samarinda. From the analysis result using dynamic program method obtained by total completion time of 85 minutes and by looking at the comparison before and after using dynamic program method that total employee assignment time by using dynamic program method equal to 257 minutes and before using dynamic program method that is equal to 530 minutes. It can be concluded that the total minimum work completion time of 85 minutes and based on the comparison before and after using the dynamic program method idicates that the assignment of employee has been optimal.
Model Cox Proportional Hazard Pada Kejadian Bersama (Ties) dengan Metode Breslow Nazmi Soraya; Yuki Novia Nasution; Sri Wahyuningsih
EKSPONENSIAL Vol 9 No 1 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Cox proportional hazard model at the tied incident is a modification from Cox model while there are two or more individual that experienced tied. Parameter estimation in procedure formation of cox generally uses maximum partial likelihood estimation (MPLE) that maximised the function of partial likelihood. In incident with ties case, the modification at partial likelihood is done with breslow approach. The data used in this research were Dengue Hemorrhagic Fever patients (DHF) who were hospitalized at Dirgahayu Hospital Samarinda from July 2016 until June 2017. There are 100 patients with 5 independent variables that are suspected to affect the healing of Dengue Hemorrhagic Fever (DHF) patients, namely sex, age, platelet count, hematocrit count, and duration of fever before hospitalized. From the calculation of data used R 2.11.1 software, Cox proportional hazard model using Breslow method, it is obtained that significant variable, are the count of platelets and hematocrit, and the duration of fever before hospitalized, patient who had normal platelet count had a chance of healing 2.359 times faster than patients had a thrombocytopenia (low platelet). For the amount of heamatocrit each patient who had a normal hematocrit had a chance of healing 2.364 times faster than patients who had under-normal hematocrit, and each one day addition to duration of patient's long history fever before hospitalized, decreased the chance of healing by 0.849 times.
Model Regresi Logistik Spasial Tiara Nurul Ma’ala; Desi Yuniarti; Memi Nor Hayati
EKSPONENSIAL Vol 7 No 2 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

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Abstract

Logistic regression modeling procedure is applied to model the response variable (Y) which is based on one or more categorical explanatory variable (X) which is categorical or continuous. In the application of logistic regression is often found that there are spatial influences that affect the model. The existence of spatial relationships between regions that cause necessary to accommodate the spatial diversity into the model, so that the analysis used logistic regression spatial. First law of geography says that everything is related to everything else, but near things are more related than distant things. Then, when a region becomes a major cause of the spread of a disease is suspected, the region will provide the spread of a disease to the new area adjacent to it. The way to find out the adjacent area with the same characteristics can be done with spatial logistic regression method.The spread of TB disease in Samarinda City is quite high. TB is a chronical disease which has been known by the public and feared of its infection. This study’s aim is to determine the appropriate model to estimate the spread of TB disease. From this model it is known that the factors that influence the number of people with TB disease in every village in Samarinda City in the year 2013 are the number of primary school in every village and the spatial effect. This means that there is the influence of spatial factors to the spread of TB disease in every village in Samarinda City in the Year 2013.
Model Regresi Weibull Pada Data Kontinu yang Diklasifikasikan: Studi Kasus: Indikator Pencemaran Air BOD di DAS Mahakam Tahun 2016 Panduwinata, Hesty Dwiyugo; Suyitno, Suyitno; Huda, Moh. Nurul
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 (765.081 KB) | DOI: 10.30872/eksponensial.v13i2.1051

Abstract

Weibull Regression is a model of regression developed from Weibull distribution in which scale parameter is expressed in the regression parameters. The Weibull regression models discussed in this study are the Weibull survival regression, Weibull hazard regression and regression model for the mean. The Weibull survival regression model is a model of the probability that the Mahakam River water is polluted. The Weibull hazard regression model is a model of velocity of the polluted Mahakam River water, and the Weibull regression for the mean is the model used to predict the average value of BOD (Biochemical Oxygen Demand). The purpose of this study was to obtain the Weibull regression model on BOD water pollution indicator data in the Mahakam River basin, to determine the factors that influence the Weibull regression model. The parameter method is maximum likelihood estimation (MLE). Based on the parameter estimation results, the maximum likelihood estimator is obtained by using the method of Newton-Raphson iteration. The results of hypothesis testing, it is concluded that the factors that influence the Weibull regression model are pH, Total Dissolved Solid (TDS) and water discharge.

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