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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 6 Documents
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Search results for , issue "Vol. 14 No. 1 (2023)" : 6 Documents clear
Peramalan Inflasi Kota Balikpapan Menggunakan Metode Singular Spectrum Analysis Sergio, Andrean; Wahyuningsih, Sri; 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 | Full PDF (1290.292 KB) | DOI: 10.30872/eksponensial.v14i1.1098

Abstract

Singular Spectrum Analysis (SSA) is a nonparametric forecasting method capable of separating time series data into interpretable trend, seasonal, cycle, and noise. Methods with component separation are suitable for characterizing economic and business data trends that tend to contain stationary, trend, cycle, and seasonal factors. One of the economic data that can be used in research is inflation. The purpose of this study is to obtain the results of inflation forecast in Balikpapan City from November 2022 to October 2023. Based on the forecasting results of the SSA method on inflation in Balikpapan City, the MAAPE value was 23.53% which showed that the forecasting results were quite accurate. Based on the results of inflation forecast from November 2022 to October 2023, there was a decrease in inflation in November 2022 by -0.64% or it could be said that there would be deflation by 0.64%. Over the next period, inflation tends to increase where the highest inflation will occur in June 2023, which is 1.96%.
Optimasi Fuzzy C-Means Menggunakan Particle Swarm Optimization Untuk Pengelompokan Kabupaten/Kota Di Pulau Kalimantan (Studi Kasus : Data Indikator Kesejahteraan Rakyat Tahun 2020) Febriyanti, Nur Afifah; Goejantoro, Rito; Prangga, Surya
EKSPONENSIAL Vol. 14 No. 1 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1148.931 KB) | DOI: 10.30872/eksponensial.v14i1.1095

Abstract

Fuzzy C-Means (FCM) is a method of grouping data based on the degree of membership whose observation object is based on the information found in the data describing the object. The FCM method has weaknesses in the initial cluster center determination, so it can be overcome by the Particle Swarm Optimization (PSO) method that can be applied to find the optimal solution of the optimal cluster center determination. The purpose of this research is to determine the optimal number of clusters based on the validity indexes of Partition Coefficient (PC) and Modified Partition Coefficient (MPC), and obtain the results of grouping regencies/cities using the FCMPSO method. Based on the FCMPSO method with a validity index of PC and MPC, it produces an optimal cluster of two clusters, the first cluster consisting of 33 regencies/cities on Kalimantan Island and the second cluster consisting of 23 regencies/cities on Kalimantan Island.
Klasifikasi Penyakit Tuberkulosis Menggunakan Metode Naive Bayes (Studi Kasus: Data Pasien Di Puskesmas Petung Kabupaten Penajam Paser Utara) Abidin, Ahmad Aliful; Goejantoro, Rito; Fathurahman, M.
EKSPONENSIAL Vol. 14 No. 1 (2023)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (663.984 KB) | DOI: 10.30872/eksponensial.v14i1.1031

Abstract

The Naive Bayes method is one of the data mining methods used in classifying data and predicting future opportunities based on experience or previous data. This method was proposed by British scientist Thomas Bayes using a branch of mathematics known as probability theory. One of the diseases that can be detected using the classification using the Naive Bayes method is Tuberculous (TB). Tuberculous is an infectious respiratory disease caused by the bacterium Mycobacterium Tuberculosis. The purpose of this study was to determine the results and accuracy of the classification of Tuberculous disease using the Naive Bayes method in one of the health service units, namely Puskesmas Petung, Penajam Paser Utara. The results showed that data mining classification using the Naive Bayes method was appropriate in classifying Tuberculous. For training and testing data, divided into 90:10, the accuracy rate is 87.5%, categorized as Excellent Classification. As for the training and testing data divided into 70:30, the accuracy rate is 90.9%, classified as Excellent Classification.
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.
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.
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%.

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