Garuda - Garba Rujukan Digital

All

Eksponensial

exponensial
Website

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

1 2

Search results for , issue "Vol. 12 No. 2 (2021)" : 12 Documents clear

Perbandingan Metode C-Means dan Fuzzy C-Means Pada Pengelompokan Kabupaten/Kota Di Kalimantan Berdasarkan Indikator IPM Tahun 2019 Mahmudi, Mahmudi; Goejantoro, Rito; Amijaya, Fidia Deny Tisna
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

The Human Development Index is an indicator used to measure one important aspect related to the quality of the results of economic development, namely the degree of human development. Data Mining is a technique or process for obtained information from large database warehouses. Based on its function, one of the data mining tasks was to group data, where the method used in this study was the C-Means and Fuzzy C-Means grouping methods. The two classification methods were applied to the human development index indicator data. The purpose of this study was to determined the best method based on the ratio of the standard deviation in clusters to the standard deviation between clusters. Based on the results of the analysis, it was concluded that the best method is the C-Means method with the value of the standard deviation value in the cluster against the standard deviation between clusters of 0.434 which results in 5 clusters, namely cluster 1 consisting of 9 districts / cities, cluster 2 consisting of 7 districts / cities, cluster 3 consists of 10 districts / cities, cluster 4 consists of 15 districts / cities and cluster 5 consists of 15 districts / cities.

Model Geographically Weighted Weibull Regression pada Indikator Pencemaran Air Biochemical Oxygen Demand di Daerah Aliran Sungai Mahakam Rahmah, Siti Mahmudatur; Suyitno, Suyitno; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Geographically Weighted Weibull Regression (GWWR) Model is a Weibull regression model applied to spatial data. Estimation of the GWWR model is performed at every observation location using spatial weighting. The purpose of this study was to determine the GWWR model of water pollution indicator Biochemical Oxygen Demand (BOD) data and the factors that influence BOD in the Mahakam River. The estimating parameters method of the GWWR model was the Maximum Likelihood Estimation (MLE) and it’s estimator was obtained by Newton-Raphson Iterative method. Spatial weighting in parameter estimation was determined using the Adaptive Bisquare weighting function and bandwidth optimum was determined by using Generalized Cross-Validation (GCV) criteria. Based on the GWWR model parameters testing, the factors that influence BOD locally was nitrate concentrations, while the factors influence globally were temperature and nitrate concentration.

Perbandingan Metode Klasifikasi Naive Bayes dan K-Nearest Neighbor pada Data Status Pembayaran Pajak Pertambahan Nilai di Kantor Pelayanan Pajak Pratama Samarinda Ulu Rahmaulidyah, Fatihah Noor; Hayati, Memi Nor; Goejantoro, Rito
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Classification is a systematic grouping of objects into certain groups based on the same characteristics. The classification method used in this research are naive Bayes and K-Nearest Neighbor which has a relatively high degree of accuracy. This research aims to compare the level of classification accuracy on the status data of value-added tax (VAT) payment. The data used is data on corporate taxpayers at Samarinda Ulu Tax Office in 2018 with the status of VAT payment being compliant or non-compliant and used 3 independent variables are income, type of business entity and tax reported status. Measurement of accuracy using APER in the Naive Bayes method is 17.07% and in K-Nearest Neighbor method is 19,51%. The comparison results of accuracy measurements between the two methods show that the naive Bayes method has a higher level of accuracy than the K-Nearest Neighbor method

Optimalisasi K-Means Cluster dengan Principal Component Analysis pada Pengelompokan Kabupaten/Kota di Pulau Kalimantan Berdasarkan Indikator Tingkat Pengangguran Terbuka Rais, Muhammad; Goejantoro, Rito; Prangga, Surya
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Data mining or often also called knowledge discovery in databases is an activity that includes collecting, using historical data to find regularity, patterns, or relationships in large data sets resulting in useful new information. Cluster analysis is an analysis that aims to group data based on its likeness. This research uses the K-Means method combined with PCA. The K-Means method groups data in the form of one or more clusters that share the same characteristics. While the PCA method was used to reduce research variables. This grouping method was applied to the data indicator of the unemployment rate of districts/cities in Kalimantan Island in 2018. The cluster validation used in this study was the Davies-Bouldin Index (DBI). Based on the results of the analysis, it was concluded that the number of principal components formed was as many as 2 principal components. The most optimal grouping of districts/cities in Kalimantan island in 2018 was to use 2 clusters with a DBI value of 0,507. The grouping of districts/cities in Kalimantan Island in 2018 produced 2 clusters, cluster 1 consisting of 51 districts/cities and clusters of 2 consisting of 5 districts/cities. Cluster 1 was a cluster that has the highest percentage of the poor population and the highest labor force participation rate when compared to cluster 2. While cluster 2 was a cluster that has an index value of human development, population, number of the labor force, number of unemployed, population density, and the minimum wage of district/city was high compared to cluster 1.

Peramalan Produksi Kelapa Sawit Menggunakan Metode Pegel’s Exponential Smoothing Sinaga, Yetty Veronica Lestari; Wahyuningsih, Sri; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Time series data analysis using Pegel's exponential smoothing method are an analysis of time series that is influenced by trend and seasonal data patterns. The data used in this study was oil palm production in East Kalimantan Province from January 2014 until December 2018. This study aims to predict oil palm production for January, February, March in 2019. Forecasting results were verified based on the MAPE value and monitoring signal tracking method. The results showed that in the Pegel method, the exponential smoothing model without a multiplicative seasonal trend with a MAPE value of 7.84% had better forecasting accuracy than the other methods. The forecast results of the Pegel's exponential smoothing method without a multiplicative seasonal trend can be used to predict the next 3 periods, namely January, February and March 2019. The forecast results for the next 3 periods have increased in succession.

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

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.

Pengklasifikasian Status Gizi Balita di Puskesmas Sempaja Samarinda menggunakan Probabilistic Neural Network (PNN) Tahun 2019 Lestari, Putri Ayu Dwi; Hayati, Memi Nor; Nasution, Yuki Novia
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Probabilistic Neural Network (PNN) is a model in Artificial Neural Networks (ANN) that is used for classification. PNN depends on the smoothing parameter (α). PNN has the advantage of being able to value of problems that previously existed in the back propagation method of ANN. The PNN method in this study was applied to the nutritional status of toddlers. Assessment of the nutritional status of toddlers can be determined through measurements of the human body known as anthropometry. Parameters for determining nutritional status based on anthropometry are age, weight and height. Therefore, in this study, a classification of the nutritional status of children under five is carried out to determine whether the toddler is experiencing good nutrition or poor nutrition. It was found that PNN with the best classification accuracy rate on the nutritional status of toddlers, namely the proportion of training data and testing data of 50%: 50% with α = 1, with accuracy results between training data and training data of 85% and accuracy results between data testing of the training data by 70%.

Model Geographically Weighted Univariat Weibull Regression pada Data Indikator Pencemaran Air Dissolve Oxygen di Daerah Aliran Sungai Mahakam Kalimantan Timur Tahun 2018 Sugiarto, Sugiarto; Suyitno, Suyitno; Rizki, Nanda Arista
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Geographically Weighted Univariat Weibull Regression (GWUWR) model is a regression model applied to spatial data. Parameter estimation of GWUWR model is performed at every observation location using spatial weighting. The purpose of this study is to determine the GWUWR model at the water pollution indicator data namely dissolved oxygen (DO) at Mahakam river in East Kalimantan and to find out the factors that influence DO in Mahakam river. The research data are secondary from the environmental services East Borneo. The research response variable was DO, meanwhile the predictor variables were pH, Total Dissolve Solid, Total Suspended Solid, Nitrate and Amonia. Parameter estimation method is Maximum Likelihood Estimation (MLE). Spatial weighting was determined using the Adaptive Gaussian weighting function and optimum bandwidth determination criteria used Generalized Cross-Validation (GCV). Based on the result of the parameter testing of GWUWR model it was concluded the factors influencing DO locally were pH, Total Dissolve Solid and ammonia concentrations, while the factors influencing globally were Total Dissolve Solid and ammonia concentration

Penerapan Metode Klasifikasi Multinomial Naive Bayes: (Studi Kasus: PT Prudential Life Samarinda Tahun 2019) Rinaldi, Rival; Goejantoro, Rito; Syaripuddin, Syaripuddin
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Life insurance is a risk management service provide payment to policyholders in the event of a disaster that has been stipulated in the agreement. A classification system needs to be done to facilitate the company in making decisions to provide policies to customers. One system that can be used is multinomial Naive Bayes. Multinomial Naive Bayes is a simple probabilistic classification that has more than two groups or categories. An algorithm using Bayes theorem assumes all independent variables. The aim of this study is to obtain an accuracy level of 5 different proportions with the Naive Bayes multinomial method used in insurance customer payment status data. The data used is the customer data of PT. Prudential Life Samarinda in 2019 with the status of current premium payment, substandard and non-current and using 5 independent variables, namely income, age, amount of premium payment, sex and employment. The results of the measurement of classification accuracy using APER status premium payment on insurance customer data of PT. Prudential Life 2019 Naive Bayes multinomial method showed 22,96% misclassification at 50:50 proportion, at the proportion of 60:40 there were 21,43% misclassification, at the proportion of 70:30 there were 19,05% misclassified, at proportions 80:20 had a misclassification of 14,29%, and a proportion of 90:10 has a misclassification of 7,14%.

Analisis Sistem Antrean Untuk Optimalisasi Jumlah Server Menggunakan Model Keputusan Tingkat Aspirasi: (Studi Kasus : Restoran Cepat Saji di Samarinda Central Plaza) Felysia, Novia; Wahyuningsih, Sri; Nasution, Yuki Novia
EKSPONENSIAL Vol. 12 No. 2 (2021)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

This research aims to obtain information on the number of cashiers with optimal performance in the fast food restaurant at Samarinda Central Plaza queue system using R Studio software. The queue model applied in this research is (M1/M2/c):(FCFS/∞/∞) with First Come First Served (FCFS) queue discipline. The optimal number of cashiers are determinated by using the aspiration level decision model. The results of the analysis showed that the optimal number of cashiers was 3 cashiers with an average number of customers in the queue as many as 1 customer every 15 minutes, the average number of customers in the queue system as many as 2 customers every 15 minutes, the average waiting time for customers in the queue for 1.2 minutes, the average waiting time of customers in the queue system for 6 minutes, and the percentage of idle time is 2.26% that is about 20.34 seconds

Page 1 of 2 | Total Record : 12

1 2

Filter by Year

2021 2021

Filter By Issues

All Issue Vol. 16 No. 2 (2025): Jurnal Eksponensial Vol. 16 No. 1 (2025): Jurnal Eksponensial Vol. 15 No. 2 (2024): Jurnal Eksponensial Vol. 15 No. 1 (2024): Jurnal Eksponensial Vol. 14 No. 2 (2023) Vol 14 No 1 (2023): Jurnal Eksponensial Vol. 14 No. 1 (2023) Vol. 13 No. 2 (2022) Vol. 13 No. 1 (2022) Vol. 12 No. 2 (2021) Vol. 12 No. 1 (2021) Vol. 11 No. 2 (2020) Vol. 11 No. 1 (2020) Vol 10 No 2 (2019) Vol 10 No 2 (2019): Jurnal Eksponensial Vol 10 No 1 (2019) Vol 9 No 2 (2018) Vol 9 No 1 (2018) Vol 8 No 2 (2017) Vol 8 No 1 (2017) Vol 7 No 2 (2016) Vol 7 No 1 (2016) More Issue

Home Page

OAI Link

Editorial Team

Contact

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

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Home Page

OAI Link

Editorial Team

Contact

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

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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