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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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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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Pengelompokan Puskesmas Berdasarkan Kasus Balita Stunting di Kabupaten Paser Menggunakan Metode K-Medoids Puspita, Ika; Hayati, Memi Nor; Nohe, Darnah Andi
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.v14i1.1089

Abstract

The number of cases of stunting toddler in Paser Regency increased by 6.66% from 2018 to 2019%. The increased in the number of stunting toddler in Paser Regency shows that the efforts made by the Paser Regency Government have not been effective in reducing the prevalence of stunting toddler because the stunting toddler rate in Paser Regency is still above the threshold set by the World Health Organization (WHO), which is a maximum of 20%. Therefore, an appropriate strategy is needed to find out which areas receive special attention and treatment, one of method to be used is cluster analysis. Cluster analysis is divided into two methods, namely the hierarchical method and the non-hierarchical method. The non-hierarchical method begins by establishing the number of groups. One of the methods included in the non-hierarchical method is K-medoids. In this study, clustering will be carried out in cases of stunting toddlers in Paser Regency using the K-medoids method. This study aims to determine the optimal cluster formed by selecting the smallest Davies Buoldin Index (DBI) value from the 2019 Community Health Center grouping in Paser Regency. The clusters formed for the K-medoids method in this study were 2 clusters, 3 clusters, and 4 clusters. Based on the results of the analysis, the K-medoids method for 2 clusters, 3 clusters and 4 clusters was based on the DBI values ​​of 0.977, 1.470, and 1.670, respectively. The optimal group for classifying stunting toddler cases in Paser Regency in 2019 is 2 cluster using K-medoids method.
Aplikasi Metode Double Exponential Smoothing Holt Dengan Optimasi Golden Section Untuk Peramalan Nilai Ekspor Provinsi Kalimantan Timur Andini, Putri Dwiayu Aulia; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 15 No. 1 (2024): Jurnal Eksponensial
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v15i1.1278

Abstract

Exponential smoothing is a method of time series analysis used to forecast the future. The choice of forecasting method takes into account data patterns, such as Double Exponential Smoothing (DES) Holt is used on data that has a trend pattern, and Triple Exponential Smoothing (TES) Holt-Winters is used on trend and seasonal data. The aim of this research is to obtain the best forecasting method by optimizing the golden section on the export value of East Kalimantan Province from 2015 to 2022 and to obtain the results of forecasting the export value of East Kalimantan Province for the next 3 months using the best method by optimizing the golden section. The research results show that the parameter value using golden section optimization is for and for with a MAPE value of . Successive forecasting results in January 2023 are January 2023 is 3.503,201 million USD, February 2023 is 3.577,731 million USD, and March 2023 is 3.612,201 million USD.
Penerapan Metode K-Means Dalam Pengelompokan Kabupaten/Kota Di Kalimantan Berdasarkan Indikator Pendidikan Messakh, Gerald Claudio; Hayati, Memi Nor; Sifriyani, Sifriyani
EKSPONENSIAL Vol. 14 No. 2 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v14i2.1103

Abstract

Cluster analysis is an analysis that aims to classify data based on the similarity of spesific characteristics. Based on the structure, cluster analysis is divided into two, namely hierarchical and non-hierarchical methods. One of the non-hierarchical methods used in this study is K-Means. K-Means is a partition-based non-hierarchical data grouping method. This purpose of this study is to obtain the best results of grouping regencies/cities on the island of Kalimantan based on education indicators using the K-Means method based on the smallest ratio of standard deviation. Based on the results of the analysis, it can be concluded that the best grouping results based on the smallest ratio of standard deviation is 0.6052 which produces optimal clusters of 2 clusters with the first cluster consisting of 14 Regencies/Cities while the second cluster consists of 42 Regencies/Cities on Kalimantan Island
Regresi Logistik dengan Metode Bayes untuk Pemodelan Indeks Pembangunan Manusia Kabupaten/Kota di Pulau Kalimantan Syafitri, Febriana; Goejantoro, Rito; Wasono, Wasono
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v12i2.802

Abstract

Human Development Index (HDI) is an indicator that can measure success in efforts to build the quality of human life. HDI is also a measure of the prosperity of a region which is observed based on three dimensions, namely health, education and economy. Based on HDI publication by the Central Statistics Agency in 2018, it showed that the scores of HDI for 56 districts/cities in Kalimantan Island only has two categories of HDI which are medium and high. Bayesian method is a parameter estimation technique that combines the likelihood and prior distribution functions. The estimation with Bayesian method was solved using Markov Chain Monte Carlo simulation (MCMC) with Gibbs Sampler algorithm. The aim of this study is to examine the modelling of the factors that influence the HDI of districts/cities in Kalimantan Island and determine the accuracy of the model classification using logistic regression with Bayesian method. The data used is the HDI of districts/cities in Kalimantan Island in 2018. Bayesian method is a parameter estimation technique that combines the likelihood and prior distribution functions. The estimation with Bayesian method was solved using Markov Chain Monte Carlo simulation (MCMC) with Gibbs Sampler algorithm. The results of modelling and analysis on districts/cities HDI data on Kalimantan Island showed that the factors that significantly influence HDI are the number of paramedic, the number of health facility and the participation rate of high school. The results of the classification accuracy of the model amounted to 82,14% which resulted in 37 districts/cities are categorized as the HDI medium category and 19 districts/cities are categorized as the HDI high category.
Analisis Data Ketinggian Permukaan Air Sungai Mahakam Daerah Kutai Kartanegara Tahun 2010-2016 Menggunakan Model Autoregressive Integrated Moving Average (ARIMA) Dengan Efek Outlier: Studi Kasus: Data Rata-rata Ketinggian Tiap Bulan Permukaan Air Sungai Mahakam, Tenggarong, Kalimantan Timur Agustianto, Rezky; Purnamasari, Ika; Suyitno, Suyitno
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v11i1.643

Abstract

Measurement of water level is useful as a guide for flood events in an area. As a result of global warming it is predicted that rainfall will increase and the water level will be high, so that the chances of flooding will increase. The method often used in forecasting is the method of Autoregressive Integrated Moving Average (ARIMA). ARIMA is one of the time series forecasting methods that has been studied in depth by Box and Jenkins. ARIMA's basic concepts include,identification of models, parameter estimation, diagnostic checks and forecasting. Forecasting results with the ARIMA method are inaccurate, on data that contains outliers. The weakness of the ARIMA method can be overcome using the ARIMA method with outlier detection. The type of outlier detection in this study is additive outlier (AO). The purpose of this study was to determine the ARIMA forecasting model with an outlier effect on the average water level data of the Mahakam River in the Kutai Kartanegara Region in front of the Tenggarong Museum Building from January 2010 - December 2016. The results showed that the best forecasting model was the river Mahakam Kutai Kartanegara Region is ARIMA ([12], 1,0) with the addition of 4 outlier effects and measure of goodness is AIC with a value of 250,0776.
Peramalan Pendapatan Asli Daerah Kota Samarinda Menggunakan Metode Double Exponential Smoothing Dari Brown Devira, Annisa Suci; Nasution, Yuki Novia; Suyitno, Suyitno
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.v14i2.1138

Abstract

Forecasting is a technique for estimating a value in the future by paying attention to past data and current data. One of the forecasting methods for exponentially increasing or decreasing data patterns is Exponential Smoothing. Exponential Smoothing is a method that shows the weighting decreases exponentially with respect to the older observation values. The linear model of the Exponential Smoothing method that uses a two-time smoothing process is Brown's Double Exponential Smoothing method. This study aims to get a forecast of Regional Original Income (PAD) in Samarinda with the double exponential smoothing method. Research data is secondary data from the Samarinda City Regional Revenue Agency (BAPENDA) file. The conclusion of the study is that the results of forecasting PAD in the city of Samarinda in 2021 are IDR 3.374.750.000.000 with an accuracy rate of Mean Absolute Percentage Error (MAPE) of 0,41%.
Pencegahan Penyakit Kusta di Lingkungan Hutan Tropis Lembab Kalimantan Melalui Pemodelan Geographically Weighted Poisson Regression Wati, Fatma; Suyitno, Suyitno; Hayati, Memi Nor
EKSPONENSIAL Vol. 12 No. 1 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v12i1.756

Abstract

Geographically Weighted Poisson Regression (GWPR) model is a regression model developed from Poisson regression which is applied to spatial data. Parameter estimation of the GWPR model is done at each observation location using spatial weighting. This study goal is to obtain the GWPR model and the factors influencing the number of leprosy cases in each regency(municipality) on Kalimantan Island in 2018. Spatial weighting was obtained by using the adaptive bisquare kernel function and optimal bandwidth was determined by using Generalized Cross-Validation (GCV) criteria. The data of this study was secondary data namely the number of leprosy cases in 56 regency on Kalimantan Island in 2018. The parameter estimation method of GWPR model is Maximum Likelihood Estimation (MLE). The results of analysis showed that maximum likelihood estimator is obtained by using the Newton-Raphson iterative method and the factors affecting the number of leprosy cases in each regency were different and locally. The factors influencing locally were the number of health facilities, the number of health workers, the number of male population and population density.
Penyelesaian Masalah Pemrograman Kuadratik Menggunakan Metode Beale Erlina, Erlina; Syaripuddin, Syaripuddin; Amijaya, Fidia Deny Tisna
EKSPONENSIAL Vol. 13 No. 1 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v13i1.889

Abstract

Quadratic programming is a special form of nonlinear programming which has the general form of the objective function in the form of a quadratic functions and the constraints in the form of linear functions. One of the methods used to solve the quadratic programming model is Beale’s method. This method is a modification of the simplex method for linear programming problems. This study aims to determine the optmal results of paddy production data in Balikpapan city using Beale’s method. The quadratic programming model was formed using the least squares method with the objective functions by selecting two types of plants,namely lowland paddy and upland paddy. Furthermore, the quadratic programming model formed that is formed is solved using Beale’s method. The data used is data on the paddy production of balikpapan city in 2005-2019. Based on the calculatios, the objective function is with the constraint functions and . After calculating using Beale’s method, the optimal result for the maximum yield of lowland paddy and upland paddy is quintals with a harvested area of hectares of lowland paddy and a harvested paddy of hectares of upland paddy.
Penentuan Cadangan Premi Asuransi Jiwa Dengan Metode Fackler Faturachman, Faturachman; Suyitno, Suyitno; Rizki, Nanda Arista
EKSPONENSIAL Vol. 13 No. 1 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v13i1.876

Abstract

Insurance is an agreement between two parties, where one party is obliged to pay and the other party has the obligation to provide compensation to the premium payer if something happens to the party in accordance with the agreement that has been made. The main problem faced by insurance companies is that the fees paid through premiums are not sufficient to finance compensation payments at the beginning of the policys, To overcome the shortage of costs the insurance company must have a reserve fund called a premium reserve. The purpose of this study was to determine the reserve for term, endowment and whole life insurance premiums using the Fackler method. The variables used in this study are the customer's age, gender, payment term, interest rate and the sum insured. In this study, premium reserves were calculated for participants aged 30 years, men and women, with a payment term of 30 years, an interest rate of 6.75%, and an insurance value of Rp. 100,000,000. Based on the calculation results, the reserve value of term life insurance premium for customers with 30 years of age and the insurance period of 30 years increases at the beginning of the year to the 21st year, after which it decreases until the reserve at the end of the 30th year, the value of the lifetime insurance premium reserve. life for customers with 30 years of age always increases from the beginning of the year to the last year where the payment for male customers is Rp. 93,176,962 and women in the amount of Rp. 93,296,217,156250. The reserve value of dual-purpose life insurance premiums for customers with 30 years of age and insurance period of 30 years always increases from the beginning of the year to the end of the year of payment of Rp. 100,000,000. The large difference in premium reserves for men and women is due to the higher chance of life for women than men.
Penerapan Algoritma K-Medoids pada Pengelompokan Wilayah Desa atau Kelurahan di Kabupaten Kutai Kartanegara: Studi Kasus : Data Hasil Pendataan Potensi Desa (PODES) Tahun 2018 Ibrahim, Rizky Nur; Hayati, Memi Nor; Amijaya, Fidia Deny Tisna
EKSPONENSIAL Vol. 11 No. 2 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/eksponensial.v11i2.658

Abstract

Kutai Kartanegara Regency (Kukar) was recorded as the largest contributor to the poor population in East Kalimantan (Kaltim) Province in 2017, so that appropriate strategies are needed to solve proverty problems. The development strategy is prioritized for the regions with the largest number of poor people. Identification is conducted based on facilities, infrastructures, access, social, population and economy is provided in the Village Potential data (PODES). K-Medoids is a grouping method that uses representative objects as a central point, which can be used to find out the characteristics of a region. This research is aimed to find out the optimal cluster formed by choosing the largest value of Silhouette Coefficient (SC) from the grouping of villages / political district in Kukar Regency using PODES data in 2018. Clusters that will be formed in this research are 2 clusters, 3 clusters, 4 clusters and 5 clusters. Based on the analysis, it can be seen that the value of SC 2 cluster is 0.430, the value of SC 3 cluster is 0.174, the value of SC 4 cluster is 0.175 and the value of SC 5 cluster is 0.196. So that the largest SC or optimal cluster values ​​obtained in the grouping of 2 clusters with a SC value of 0.430. Cluster 1 consists of 186 villages / political dsitrict and cluster 2 consists of 46 villages / political district.

Page 17 of 21 | Total Record : 205

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