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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. 12 No. 1 (2021)" : 12 Documents clear

Metode Hierarchical Density-Based Spatial Clustering of Application with Noise (HDBSCAN) Pada Wilayah Desa/Kelurahan Tertinggal di Kabupaten Kutai Kartanegara: (Studi Kasus : Data Hasil Pendataan Potensi Desa (PODES) Tahun 2018) Wahyuni, Nanda Anggun; Hayati, Memi Nor; Rizki, Nanda Arista
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

The underdeveloped areas are generally the districts which are relatively underdeveloped compared to other regions on a national scale. Determination of underdeveloped villages is often done in order to determine the distribution of government assistance so that assistance can be distributed appropriately. The identification is based on facilities, infrastructure, access, social, population and economy provided in the Village Potential data (PODES). The concept of grouping based on regional or spatial is done to find out certain characteristics in an area. HDBSCAN is a grouping concept with a parameter called Mpts. The purpose of this study is to know the number of clusters formed in the grouping of underdeveloped villages / urban areas in Kutai Kartanegara Regency using the HDBSCAN method. The Mpts parameters that is used in this study is from 2 to 6. Based on the results of the analysis, the clusters formed in the grouping of underdeveloped villages / urban areas in Kutai Kartanegara Regency using the HDBSCAN method, were 3 clusters. Cluster 0 consists of 19 villages / urban areas , cluster 1 consists of 4 villages / urban areas and cluster 2 consists of 61 villages / urban areas. Based on the analysis, villages / urban areas included in cluster 1 could be the main target of the government in providing assistance and development of regional facilities / infrastructure.

Klasifikasi Rumah Tangga Miskin Di Kecamatan Kaubun Tahun 2020 Dengan Menggunakan Metode Improved Chi-Square Automatic Interaction Detection Yuliasari, Pratiwi Dwi; Goejantoro, Rito; Amijaya, Fidia Deny Tisna
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Classification was grouping samples based on similarities and differences by using categorical variables. The classification method used in this study was the Improved Chi-square Automatic Interaction Detection (I-CHAID) which was an improvement from the CHAID method. This research aims to provide an overview of poor households and classify poor households, and to compare the accuracy of the classification results for each data proportion. The data used is household data in Kaubun District in 2020 with poor and non-poor status. The results of this study indicate that there were 10 households with poor status, and households were classified as poor if the frequency of eating is less than 3 times a day, and the best classification accuracy results use the proportion of training data of 60% and testing data of 40%.

Analisis Faktor-Faktor yang Mempengaruhi Jumlah Kasus Tuberkulosis di Indonesia Menggunakan Model Geographically Weighted Poisson Regression Karima, Nabila Al; Suyitno, Suyitno; Hayati, Memi Nor
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Tuberculosis is a contagious disease suffered by humans caused by mycobacterium tuberculosis bacteria. Tuberculosis in Indonesia must be eradicated both preventive and treatment. One effort that can be given to the community to reduce tuberculosis cases is by providing information on the factors that influence tuberculosis cases through Geographically Weighted Poisson Regression (GWPR) modeling. The number of tuberculosis cases in Indonesia is a count data with a small chance of occurrence so that it is suspected to have a Poisson distribution. Cases of tuberculosis are spatial data (spatial heterogeneity). The purpose of this study is to determine the GWPR model of the number of tuberculosis cases in Indonesia and determine the factors that influence tuberculosis cases in Indonesia. The research data are secondary data obtained from the Indonesian Ministry of Health. Parameter estimation method is Maximum Likelihood Estimation (MLE). Spatial weighting is calculated by using the Adaptive Gaussian weighting function and the optimum bandwidth is determined by using the Cross-Validation (CV) criteria. The research results showed that the exact Maximum Likelihood (ML) estimator could not be obtained analytically and the approximation of ML estimator was obtained by using the Newton-Raphson iterative method. Based on the results of the parameter testing of GWPR model, it was concluded that the factors affecting the number of tuberculosis cases were local and varied in 34 provinces. The factor affecting locally are the number of poor people, the percentage of houses unfit for habitation, the percentage of districts/cities that do not have a PHBS policy and the percentage of TPM not meeting health requirements, meanwhile factors influencing globally are the number of poor people.

Analisis Cluster Pada Produk Mie Instan Berdasarkan Komposisi Yang Terkandung Dengan Menggunakan Metode Ward Sam, Faza Syahrudin; Syaripuddin, Syaripuddin; Wasono, Wasono
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Cluster analysis is a grouping of data (objects) based on only the information found in the data that describes the object and the relationships between data. The variance method commonly used is the Ward method where the average for each cluster is calculated. At each stage, the two clusters that have the smallest increase in sum of squares in the cluster are combined.. Some compositions of ingredients in noodles, for example, fat, protein, carbohydrates, food fiber, sugar and sodium. The composition of the noodles that are dangerous one of which is Monosodium Glutamate (MSG). The purpose of this research is to find out how many clusters are formed based on the composition of the content of instant noodle products. Based on the results of cluster research formed based on the composition of the contents of 43 instant noodle samples are 9 clusters where the first cluster consists of 2 members, the second cluster consists of 7 members, the third cluster consists of 5 members, the fourth cluster consists of 7 members, the fifth cluster consists of 6 members, the sixth cluster consists of 4 members, the seventh cluster consists of 4 members, the cluster the eighth consists of 1 member and the ninth cluster consists of 7 members.

Peramalan Jumlah Titik Panas Provinsi Kalimantan Timur Menggunakan Analisis Intervensi Fungsi Pulse Saputra, Ahmad Ronaldy; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Intervention analysis is a time series analysis that used to explain the influence of intervention caused by external and internal factors. As for the number of hotspot in East Borneo which was increased in 2015. The purpose of this study was to determine the best intervention model for forecasting the number of hotspots in East Borneo. In the initial stage of the intervention analysis is to divide the data into 2 parts, namely data before the intervention and data after the intervention occurred. The results of the analysis obtained the best model for the data before the intervention occurred were SARIMA (0,1,1)(0,1,1)12. The next step was identifying the intervention function by observing the residual graph of the SARIMA model and obtained the order b = 0, s = 0 and r = 0 with the AIC value of the intervention model of -143,16. Furthermore, based on the intervention model obtained forecasting results is increased from July to September 2019. The number of hotspots with the highest number of hotspots occurring on September 2019 with 249 hotspots. Then decreasing on October 2019 to 183 hotspots. On November 2019 it dropped significantly to 13 hotspots.

Upaya Pencegahan Pencemaran Air Sungai Mahakam melalui Pemodelan Geographically Weighted Logistic Regression pada Data BOD Inayah, Ulfah Resti; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Since the early years, Mahakam River has important roles in supporting human needs in East Kalimantan province. Activities around Mahakam watershed such as restaurants, fishery, and industries were in the potential of generating waste around the flow area. The waste consisted of domestic and nondomestic waste. The waste was a threat to the Mahakam River water quality. Water pollution around the Mahakam River was a threat to public health, and therefore, there’s a need for precaution. One of the precautions is to give the public information regarding the factors that influence the chances of polluted water in the Mahakam River increased through logistic regression modeling. One way to detect water pollution is to indicate by using Biochemical Oxygen Demand (BOD). BOD data was suspected spatial, therefore the appropriate statistical modeling is Geographically Weighted Logistic Regression (GWLR). GWLR is a regression model that developed from a logistic regression in which parameter estimation is done locally at every observation location. The purpose of the research is to determine the GWLR model on the BOD data of Mahakam River and to find out the factors that influence water pollution at 27 observation points along with the Mahakam River flow. The parameter estimation method is the Maximum Likelihood Estimation (MLE). The spatial weighting is calculated by using the Adaptive Bisquare weighting function and the optimum bandwidth is determined by using Generalized Cross-Validation (GCV) criteria. Research shows that the closed-form of the Maximum Likelihood estimator can’t be obtained analytically and the approximation is obtained by using Newton-Raphson (N-R) iterative method. Based on parameter testing of the GWLR model result, it was concluded that the factors were influences the probability of Mahakam River water were polluted based on the BOD indicator was locally and different in each 27 observation locations. The factors that influence locally were water temperature, acidity, Total Dissolved Solids (TDS), ammonia concentration, and water debit, meanwhile, the factors which influence globally were acidity and TDS.

Analisis Cluster Single Linkage Berdasarkan Potensi Desa Di Kabupaten Kutai KartanegaraTahun 2019 Suyanto, Suyanto; Syaripuddin, Syaripuddin; Wasono, Wasono
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Data mining is a step in the process of Knowledge Discovery in Database (KDD) which consists of the application of data analysis and the discovery of algorithms that produce certain enumerations of patterns in the data,Cluster Analysis is one of the methods in multivariate statistical analysis that is used to group objects into groups based on their characteristics, so the objects in one group have more homogeneous characteristics compared to objects in other groups. Single Linkage is a clustering process based on the closest distance between objects. If two objects are separated by a short distance, then the two objects will merge into one cluster. This study aims to obtain a cluster of village potential in Kutai Kartanegara Regency in 2019, based on the variable availability of educational facilities, the availability of health facilities, the availability of health workers, the availability of coin / card public telephones, the existence of lodging, the existence of market buildings, the existence of supermarkets, the existence of banks, the population obtaining credit facilities, the existence of other Non KUD cooperatives., Based on the results of the analysis, it can be seen that, Clusters formed in the grouping of potential villages / villages in Kutai Kartanegara Regency using a single linkage method are as many as 2 clusters.

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

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.

Analisis Faktor-Faktor Yang Berpengaruh Terhadap Pencemaran Air Sungai Mahakam Menggunakan Pemodelan Geographically Weighted Logistic Regression Pada Data Dissolved Oxygen Lestari, Vivi Dwi; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Geographically Weighted Logistic Regression (GWLR) model is a local model of the logistic regression model applied to spatial data. Parameter estimation is performed at each observation location using spatial weighting. The spatial weighting is calculated by using an adaptive tricube function and bandwidth optimum was obtained based on Generalized Cross Validation (GCV) criteria. The purpose of this study was to obtain a GWLR model on the water pollution indicator Dissolve Oxygen (DO) in Mahakam River in East Kalimantan Province and to find factors affecting the probability of the Mahakam River water was not polluted based on DO indicator. The research data is secondary obtained from Environmental Department of East Kalimantan. The parameter estimation method was Maximum Likelihood Estimation (MLE). The research result showed that the closed form of ML estimator could not be found analytically and it can be approximed by using Newton-Raphson iterative methods. Based on the result of partial hypothesis test, the factors influencing the probability of the Mahakam River water was not polluted is different for every observation location. They were phosphate consentration, total dissolved solid and nitrite consentration. The factor influencing globally was total dissolved solid.

Analisis Regresi Probit Biner Bivariat: (Studi Kasus: Indeks Pendidikan dan Indeks Pengeluaran di Pulau Kalimantan Tahun 2017) Ariessela, Syeli; Goejantoro, Rito; Purnamasari, Ika
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Bivariate binary probit regression is a regression analysis that uses two dependent variables and each has two categories. This regression analysis is used on education index data and expenditure index of district/city on Kalimantan island in 2017. The best model obtained in this regression analysis is a model that uses 4 independent variables namely APS 16-18 years, percentage of poor population, open unemployment rate, and GRDP ACMP (Gross Regional Domestic Product at Current Market Prices). The parameters that significantly influence the two dependent variables are the APS 16-18 years in models 1 and 2 and the percentage of poor people in model 2. In Samarinda, every change of the APS 16-18 years, the percentage of poor people, and the open unemployment rate of 1 the unit will increase the probability of Samarinda entering the education index and high expenditure index categories by 0,33 percent, 0,42 percent and 0,07 percent, respectively. Every change of GRDP ACMP by 1 unit will reduce the probability of Samarinda entering the education index and the high expenditure index by 1,63 percent.

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Meiliyani Siringoringo

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Kalimantan timur

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Home Page

OAI Link

Editorial Team

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Reviewer

Google Scholar

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

Abstract

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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