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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 205 Documents

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Penerapan Metode Klasifikasi Chi-Square Automatic Interaction Detection dan Exhaustive Chi-Square Automatic Interaction Detection: Studi Kasus: Data Masa Studi Mahasiswa Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Mulawarman Nurhasanah, Nurhasanah; Goejantoro, Rito; Suyitno, Suyitno
EKSPONENSIAL Vol. 13 No. 1 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

The Chi-Square Automatic Interaction Detection (CHAID) and Exhaustive CHAID methods are nonparametric statistical methods that can be used to classify. CHAID and Exhaustive CHAID were used to determine the significant relationship between the dependent variable and the independent variables based on the chi-square independence test. This study was applied to data on the study period of students of FMIPA UNMUL batch 2014. Based on the CHAID and Exhaustive CHIAD methods, it can be seen that the dependent variable of the study period has a significant relationship with the independent variable, namely the study program and GPA predicate. Where students who graduated on time for the Statistics, Biology and Chemistry study program with a satisfactory GPA predicate of 82 students and with a very satisfactory GPA predicate and cum laude with 46 students. Meanwhile, students who did not graduate on time for the Statistics, Biology and Chemistry study program with an adequate GPA predicate of 5 students, a satisfactory GPA predicate of 41 students, very satisfactory and cum laude with 3 students. Students who graduated on time for the Physics study program were 13 students and those who did not graduate on time were 34 students. The chi-square independence test performed on the CHAID method uses fewer possible categorical pairs than the Exhaustive CHAID method which uses all possible categorical pairs so that it requires a long computational and calculation time.

Analisis Survival Lama Masa Pengobatan Dan Tingkat Kesembuhan Pasien Narkoba Di Lembaga Terapi Dan Rehabilitasi Pondok Pesantren Ibadurrahman Tenggarong Seberang Fathur Rachman; Sri Wahyuningsih; Yuki Novia Nasution
EKSPONENSIAL Vol 7 No 1 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (588.886 KB)

Survival analysis is used to analyze of the long life data, in general this method used to estimate and the time curve survival which is Life Table Method, Model of Cox Proportional Hazard or the Cox model and Product Limit Method (Kaplan Meier). This script well knowing about the model of Cox Proportional Hazard for the influencing factors in the recovery term of the Narcotics Patients in the Institution of Therapy and Rehabilitation Pondok Pesantren Ibadurrahman Tenggarong Seberang and knowing of the influencing factors in the recovery term of the Narcotics Patients in the Institution of Therapy and Rehabilitation Pondok Pesantren Ibadurrahman Tenggarong Seberang. The research data is done for 114 of Narcotics Patients. The Procedural in making Cox Proportional Hazard model including to several parts, they are deciding of variables which used to, assumption exam of Cox Proportional Hazard model, choosing the best model with backward exam, deciding variable which influenced of the cure rates duration. The usage data are forming by 5 variables, such as Gender, Education, The use of Smoking, Ages, and Parenting, based on the research was found the model of Cox Proportional Hazard for the influence factors in hi curing is: hi(t,x)=exp(-0.694 x4) h0(t). The influence factors in curing of the Narcotics Patients are the age of the patient since the therapy.

Perbandingan Metode Klasifikasi Naive Bayes dan K-Nearest Neighbor: Studi Kasus : Status Kerja Penduduk Di Kabupaten Kutai Kartanegara Tahun 2018 Novalia, Viona; Goejantoro, Rito; Sifriyani, Sifriyani
EKSPONENSIAL Vol. 11 No. 2 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Classification is a technique to build a model and assess an object to put in a particular class. Naive Bayes is one of algorithm in the classification based on the Bayesian theorem, which assumes the independencies of one class with another class. K-nearest neighbor is an algorithm in the classification method for classifiying based on data that has a closest distance between one object and another object. Naive Bayes and k-nearest neighbor methods are used in classification of the employment status of citizen in Kutai Kartanegara regency because has a good accuracy and produce a small error rate when using large data sets. This research aim to compared optimal performance accuracy of both methods on the classifiying of the employment status of citizen. The data used are employment status of citizen in Kutai Kartanegara Regency based on SAKERNAS of East Kalimantan Province in 2018 and used 5 factors namely age, sex, status in the household, marital status, and education to predict employment status of citizen. Based on the analysis, classification the employment status of citizen with naive Bayes method has accuracy of 90,08% and in the k-nearest neighbor has accuracy of 94,66%. To evaluate the accuracy of classification used calculation of Press’s Q. Based on Press’s Q value showed that both of classification methods are accurate. From that analysis, can be concluded that the k-nearest neighbor method works better compared with the naive Bayes method for the case of the employment status of citizen in Kutai Kartanegara Regency.

Model Dinamis: Autoregressive Dan Distribusi Lag Muhajir Choir Nurahman; Sri Wahyuningsih; Desi Yuniarti
EKSPONENSIAL Vol 7 No 2 (2016)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (281.16 KB)

Regression model using time series data not only use the effect of changing the independent variables on the dependent variable in the same period and for the same period of observation, but also use the period of time before. The purpose of this study was to determine the dynamic model autoregressive and distribution lag by type of infinite lag, and to know the effect of US dollar exchange rate against GDP in 1993-2013. Based on the analysis of data has that GDP and US dollar exchange rate has a rising trend pattern, and obtained by a simple regression model. But this model can not be used because of two assumptions have not been met and that there are heteroscedasticity and autocorrelation. So this model should be transformed using log, and log transformation model is obtained from a simple regression. The transportation model can be used as desiredint his model is only one assumption are not met and that there are autocorrelation. Then sub sequently estimating models and obtained Koyckas well as all assumptions are met, namely residual normal distribution, no problem heteroscedasticity and autocorrelation. Thus, the obtained dynamic distribution models also lag within finite lag types.

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

Penentuan Jalur Terpendek dengan Metode Heuristik Menggunakan Algoritma Sarang Semut (Ant Colony): Studi Kasus: Jalan Arteri Sekunder Kota Samarinda Hidayat, Alfian; Purnamasari, Ika; Siringoringo, Meiliyani
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Ant Colony algorithm was adopted from the behavior of ant colonies, known as the system of ants, ant colonies are naturally able to find the shortest route on their way from nest to food source places. Colony of ants can find shortest route between the nest and food sources based on the trajectory of footprints that have been passed. The density of ant footprints on the path is always updating because of the evaporation of the footprints and the determination of ant pathways using probability calculations. This study aims to determine the results of determining the shortest path using the ant colony algorithm as the best route from the Samarinda City secondary arterial road with the route starts from Slamet Riyadi road to DI Panjaitan road. Based on the results of the study using the ant colony algorithm obtained the shortest path of 8.307 kilometers with footprint density of 1.005.

Penjadwalan Proyek Dengan Metode Program Evaluation and Review Technique (PERT) Nur Annisa Roziya; Ika Purnamasari; Wasono Wasono
EKSPONENSIAL Vol 9 No 2 (2018)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Project scheduling is one of the techniques developed in operations research to solve management problems to obtain optimal solutions. One of the methods used for project scheduling is the method of Program Evaluation and Review Technique (PERT). In PERT method, three time estimates are used, that is optimistic time (a), pessimistic (b), and realistic (m). In this study, PERT method is used to determine the optimal duration and probability value of the completion of the Grand Sangatta housing project on house type 36 which is sourced from CV Miftah Collection. The data obtained are primary data and interview. Based on the results of the analysis, it can be know the activities that are on the critical path are the activities of making the foundation (B), concrete (D), wall (E), roof (H), ceiling (I), and painting (L). The minimum time duration of completion of type 36 homes is 34 days with a 50% confidence level which was originally scheduled for 60 days.

Pemodelan Regresi Spasial Data Panel: Studi Kasus : Indeks Pembangunan Manusia di Provinsi Kalimantan Timur Menurut Kabupaten/Kota Tahun 2017-2020 Murdani, Endah Mulia; Fathurahman, M; Goejantoro, Rito
EKSPONENSIAL Vol. 13 No. 2 (2022)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Panel data is a combination of cross-section data and time-series data. The panel data regression can model the panel data. In its development, panel data regression has been developed to model spatial data, called panel data spatial regression. Spatial data is data that considers the empirical observations and considers the location factor of these observations. This study examines the spatial regression modeling of panel data and applies it to model the factors that influence the Human Development Index (HDI) of districts/cities in East Kalimantan Province from 2017 to 2020. HDI is a composite index that measures the average achievement in the three basic dimensions of human development that are considered very basic, namely life expectancy, knowledge, and a decent standard of living. HDI is one of the measuring tools considered to reflect the status of human development in a region and plays an essential role in improving the quality of human resources. The results show that the panel data spatial regression model suitable for modeling the HDI of districts/cities in East Kalimantan Province from 2017 to 2020 is the Spatial Autoregressive Fixed Effect (SAR-FE) model. The rate of economic growth and the district/city minimum wage factors that significantly influence the HDI of districts/cities in East Kalimantan Province from 2017 to 2020 based on the SAR-FE model is the rate of economic growth and the district/city minimum wage. Keywords : Panel Data, Spatial Data, Panel Data Spatial Regression, SAR-FE, HDI

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.

Pengujian Hipotesis Parameter Model Mixed Geographically Weighted Regression Data Indeks Pembangunan Manusia di Kalimantan Tahun 2016 Utami, Riska Putri; Suyitno, Suyitno; Hayati, Memi Nor
EKSPONENSIAL Vol. 11 No. 1 (2020)
Publisher : Program Studi Statistika FMIPA Universitas Mulawarman

Mixed Geographically Weighted Regression (MGWR) model is a Geographically Weighted Regression (GWR) model with some parameters are global (have the same value) and several other parameters are local (have different values) for each observation location. The purpose of this study is to obtain a MGWR model on the Human Development Index (HDI) data and find out the factors that influence the HDI of each district (city) in the provinces of East Kalimantan, Central Kalimantan and South Kalimantan in 2016. The parameter estimation method is carried out through two stages (backshift), namely local parameter estimation by using the Weighted Least Square (WLS) method and global parameter estimation by using the Ordinary Least Square (OLS) method. Spatial weighting on local parameter estimation is obtained by using an adaptive Bisquare weighting functions, where optimum bandwidth determination uses Generalized Cross-Validation (GCV) criterion. Based on the result of MGWR parameter testing, it was concluded that the school enrollment rates (SMP) affected the HDI of all districts (cities) in East Kalimantan, Central Kalimantan and South Kalimantan, while the population density affects the HDI only in a few districts (cities), namely East Kutai, Balikpapan, Samarinda and Bontang.

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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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Kalimantan timur

INDONESIA

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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