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All Journal EKSAKTA: Journal of Sciences and Data Analysis JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) DERIVATIF BAREKENG: Jurnal Ilmu Matematika dan Terapan Journal of Honai Math Specta Journal of Technology ESTIMASI: Journal of Statistics and Its Application Science Nature Journal of Science and Science Education International Journal of Digital Entrepreneurship and Business (IDEB) Hasanuddin Journal of Sociology (HJS). Jurnal Manajemen dan Pemasaran Jasa Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Journal of Mathematics, Computation and Statistics (JMATHCOS)
Georgina Maria Tinungki
Departemen Statistika, Universitas Hasanuddin
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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Journal : ESTIMASI: Journal of Statistics and Its Application

 1 
Penggunaan Analisis Korespondensi Sederhana dalam Pemetaan Wilayah Potensi Bencana di Provinsi Sulawesi Tengah Iis Cendrah Kasih; Georgina Maria Tinungki; Nasrah Sirajang
ESTIMASI: Journal of Statistics and Its Application Vol. 2, No. 1, Januari, 2021 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v2i1.10234

Abstract

Disaster cases need to be analyzed considering that when a disaster occurs it will have an extraordinary impact. The statistical method that can be used to study disaster cases is a simple correspondence analysis. This study aims to map areas with the potential for natural disasters in the province of Central Sulawesi. So, in the analysis, regions are grouped according to row profile values that are greater than the average. The result of simple correspondence analysis obtained flood disaster has the potential to occur in Banggai, Morowali, Donggala, Buol, Parigi Moutong, Tojo Una-una, Sigi, and North Morowali. While the dominant tornado disaster occurred in Banggai Kepulauan, Banggai, Poso, Toli-toli, Parigi Moutong and Sigi. For regional landslides with potential Banggai Islands, Donggala, Toli-toli, Parigi Moutong, and Sigi. Then Banggai Islands and the City of Palu are the dominant regions for earthquake disasters. The results of the grouping can be the basis of government and community focus in tackling the dominant disasters occurring in their respective regions so as to minimize the impact when natural disasters occur.
Analisis Diskriminan Linear Robust Dengan Metode Winsorized Modified One-Step M-Estimator Mega Selvia Tjahaya; Raupong; Georgina Maria Tinungki
ESTIMASI: Journal of Statistics and Its Application Vol. 3, No. 1, Januari, 2022 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.11302

Abstract

Discriminant analysis is a method used to classify an individual (object) into a group. Discriminant analysis is divided into classical linear discriminant analysis and classical quadratic discriminant analysis. Discriminant analysis must fulfilled the assumptions of normality and homogeneity of the variance-covariance matrix, however this method is very sensitive to data contains outliers. Robust linear discriminant analysis with the winsorized modified one-step M-estimator(WMOM) approach is a method that can resolve outliers data. WMOM works by trimming these outliers then replacing the outliers with the highest or lowest value of the remaining data by using criteria trimming MOM. This study aims to obtain a linear robust discriminant function with the WMOM method using the Sn scale on diabetes and prediabetes data for the period December 2016-January 2017. Based on the results of the analysis and discussion of this method, the discriminant function is obtained with a classification error rate of 16.67%. Keywords: Diabetes, One-Step M-estimator, Prediabetes, Robust Linear Discriminant Analysis, Winsorized Modified.
Model Regresi Bivariate Zero-Inflated Poisson Pada Kematian Ibu dan Bayi Andi Isna Yunita; Andi Kresna Jaya; Georgina Maria Tinungki
ESTIMASI: Journal of Statistics and Its Application Vol. 3, No. 1, Januari, 2022 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.11557

Abstract

Overdispersion is a condition with greater variance than the mean. One of the causes overdispersion is more zero-value observations so the Zero-Inflated Poisson (ZIP) regression model can be used. As for modeling a pair of discrete data is correlated and overdispersion, it can be used the Bivariate Zero-Inflated Poisson (BZIP) regression model. The BZIP regression model is a model with response variables with mixed distributions between Bivariate Poisson distribution and a point probability at (0,0). Parameters of the BZIP regression model are estimated using maximum likelihood estimation (MLE) with expectation maximization (EM) algorithm. This research was applied to data on number of maternal and infant mortality in the city of Makassar in 2017. The result obtained is the AIC value of the BZIP regression model is 170.976 smaller than the Bivariate Poisson regression model is 198.120. This shows that the BZIP regression model is better used for data with overdispersion.
Estimasi Parameter Model Regresi Data Panel Efek Tetap dengan Metode First Difference Asti Inayati Magfirah; Raupong; Georgina Maria Tinungki
ESTIMASI: Journal of Statistics and Its Application Vol. 3, No. 2, Juli, 2022 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.11278

Abstract

This study aims to estimate the regression parameters fixed effects panel data model using the first difference method on the influence of Life Expectancy, Average Length of School, and Per capita Expenditure on the Human Development Index of South Sulawesi in 2012 - 2018. The first difference method is used to obtain intercept differences in each district/city explaining the effect of regional differences. The first difference process results in autocorrelation of data so after the first difference is done the generalized least square method is used to estimate the parameters. The results show Life Expectancy, Average Length of School, and Per capita Expenditure has a significant influence on the Human Development Index of South Sulawesi in 2012 - 2018 simultaneously or partially.
Pemodelan Regresi Binomial Negatif Bivariat pada Data Jumlah Kematian Ibu dan Bayi di Provinsi Sulawesi Selatan Tahun 2020 Nurhidaya L; Erna Tri Herdiani; Georgina Maria Tinungki
ESTIMASI: Journal of Statistics and Its Application Vol. 4, No. 1, Januari, 2023 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.vi.25082

Abstract

In general, negative binomial regression is used for univariate discrete data that is overdispersive and follows the Poisson distribution. In the real world, a case is often influenced by two discrete variables that are correlated with each other. Therefore, in this paper we will examine the regression that is influenced by two independent variables, has overdispersion properties and follows a bivariate Poisson distribution. This regression is called bivariate negative binomial regression with model parameters estimated using the Maximum Likelihood Estimation (MLE) method and Newton Raphson iterations. The formation of this model is based on the Famoye method, while in general it uses the Cheon method. Furthermore, the results of this study were applied to data on the number of maternal and infant deaths in South Sulawesi Province in 2020. The results obtained were the number of puskesmas that had a significant effect on the number of maternal deaths and the proportion of handling obstetric complications, the proportion of pregnant women implementing the K4 program, the proportion of deliveries in facilities health services, the proportion of postpartum mothers implementing the KF2 program and the number of puskesmas have a significant effect on the number of infant deaths.
Analisis Value at Risk pada Portofolio Saham PT. Adaro Energy Tbk dan PT. Bukit Asam Tbk Menggunakan Metode Copula Archimedean Victor Liman; Georgina Maria Tinungki; Anisa Anisa
ESTIMASI: Journal of Statistics and Its Application Vol. 4, No. 2, Juli, 2023 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v4i2.25575

Abstract

Value at Risk (VaR) is statistical method used in risk analysis in stock investments. Stock returns that are not normally distributed cause the risk calculation to be less precise, so to overcome this, the copula method can be used. Copula is a method based on dependencies between variables. The most commonly known copula family is the Archimedean copula which consists of the Clayton, Frank, and Gumbel copula. VaR is expected to be a feasible method to use, so it is important to perform backtesting. In this research, we use data on the daily closing price of PT. Adaro Energy Tbk and PT. Bukit Asam Tbk May 11, 2020 until June 15, 2022. The best copula based on the smallest Empirical copula value is Frank copula. VaR estimates for the 90%, 95%, and 99% confidence levels respectively were 2.688%, 3.545%, and 5.014%. The higher the confidence level, the VaR value is also higher. Based on backtesting results, VaR with Frank copula method is valid at 90%, 95%, and 99% confidence levels.
Implementasi Algoritma Centroid Linkage dan K-Medoids dalam Mengelompokkan Kabupaten/Kota di Sulawesi Selatan Berdasarkan Indikator Pendidikan Raja, Nur Alfianingsih; Tinungki, Georgina Maria; Sirajang, Nasrah
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 1, Januari, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i1.13605

Abstract

Cluster analysis is a multivariate analysis technique that aims to cluster the observational data or variables into clusters in such a way that each cluster is homogeneous according to the factors used for clustering. This study used the Centroid linkage algorithm that was useful for forming groups based on the distance between centroids and the K-Medoids algorithm that was based on the use of the most centered object (medoid) to group districts/cities and obtained comparison results based on the education indicator data in South Sulawesi. The implementation of the Centroid Linkage Algorithm and K-Medoids on the education indicator data in South Sulawesi in 2018, showed that the grouping of districts/cities in South Sulawesi produced 2 clusters with cluster 1 of 21 districts/cities, and cluster 2 of 3. To determine the best method, it was seen from the value of the Standard Deviation ratio in the cluster 〖(S〗_W) and Standard Deviation between Clusters 〖(S〗_B) showed the same standard deviation ratio (S) in the Centroid Linkage algorithm and K-Medoids that was equal to 104,967.
Estimasi Parameter Regresi Ridge Robust pada Data Profil Kesehatan Sulawesi Selatan Waibusi, Hendriete Tiur Marowi; Tinungki, Georgina Maria; Sahriman, Sitti
ESTIMASI: Journal of Statistics and Its Application Vol. 5, No. 2, Juli, 2024 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v5i2.25520

Abstract

ABSTRACT Multicollinearity is one of the assumption violations in regression analysis. The existence of multicollinearity causes the standard error to increase. Ridge regression is one of the regression analysis approaches that can overcome this problem. Besides multicollinearity, another problem that often occurs is outliers. The existence of outliers causes the data not to be normally distributed. Ridge Robust Least Trimmed Square Regression is a method that can be used to overcome multicollinearity and outlier problems in the data simultaneously in the regression analysis model. The purpose of this study was to obtain the estimation results of the least trimmed square ridge robust regression model on the Health Profile data of South Sulawesi in 2017. From the results and discussion it was found that the least trimmed square ridge robust regression method has an Rsquare value or ?2 which is 88% and an MSE value 1.96, thus indicating that the ridge robust least trimmed square model fits better in dealing with data containing multicollinearity and outliers. Keywords: Robust Ridge Regression, Least Trimmed Square, Multicollinearity, Outlier, Infant Mortality Rate.
Perbandingan Kinerja Peta Kendali Exponentially Weighted Moving Average dan Peta Kendali Double Exponentially Weighted Moving Average dalam Pengendalian Kualitas Produksi Butsudan di PT. Maruki International Indonesia Sonya, Sonya; Herdiani, Erna Tri; Tinungki, Georgina Maria
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 1, Januari, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i1.25751

Abstract

Quality control is an effort in the production process to maintain product quality and minimize the occurrence of defects. One of the quality control tools is a control chart. An exponentially weighted moving average (EWMA) control chart is used to detect small shifts in the process mean. The result of the development of the EWMA control chart is the double exponentially weighted moving average (DEWMA) control chart, which increases the exponential smoothing process, where the control chart is considered more sensitive in detecting small shifts in the process mean. This study aims to obtain a comparison of the performance of the EWMA and DEWMA control charts in controlling the quality of butsudan production at PT. Maruki International Indonesia. The results obtained show that the DEWMA control chart has better performance in detecting small shifts compared to the EWMA control chart based on the smallest ARL value, at λ=0.1 the DEWMA control chart has an ARL value 1.1363 which is smaller than the ARL of EWMA control chart is 1.2268.
Model Robust Geographically Weighted Regression pada Data Kemiskinan di Sulawesi Selatan Tahun 2019 Rahman, Aqilah Salsabila; Tinungki, Georgina Maria; Herdiani, Erna Tri
ESTIMASI: Journal of Statistics and Its Application Vol. 6, No. 2, Juli, 2025 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v6i2.18046

Abstract

Geographically Weighted Regression (GWR) is a method of spatial analysis that can be used to perform analysis by assigning weights based on the geographical distance of each observation location and the assumption of having spatial heterogenity. The result of this analysis is an equation model whose parameter values apply only to each observation location and are different from other observation locations. However, when there are outliers at the observation location, a more robust estimation method is needed. One of the robust methods that can be applied to the GWR model is the Least Absolute Deviation method. In this study, model estimation was carried out on the factors that affect poverty in South Sulawesi in 2019 using Robust Geographically Weighted Regression (RGWR) with the Least Absolute Deviation (LAD) method. Determination of weighting is done by using the adaptive kernel bisquare weighting function. The results obtained are RGWR models which are different and apply only to each district/city in South Sulawesi. In addition, it was also found that the RGWR model with the LAD method was the best model for data that experienced spatial heterogenity and contained outliers.
Co-Authors A. Muthiah Nur Angriany Abdul Fathin Fawwaz Agus Budi Hartono Amirullah, Andini Riantika Putri Amirullah Andi Isna Yunita Andi Kresna Jaya Anisa Anisa Asti Inayati Magfirah Chendra, Rita Ruth Chendra Fachry Abda El Rahman Fahrul Usman Fathanah, Nur Hamzah, Hadi Siswadi Hamran Hartono, Patrick Gunawan Herdiani, Erna Tri Iis Cendrah kasih Isthi Wahyuning Tyas, Isthi Wahyuning Kiandra Putri Susanto Lestari, Henny Setyo Mega Selvia Tjahaya Muh. Hadrianto Nasrah Sirajang Nurhidaya L NURTITI SUNUSI Powell Gian Hartono Rahardja, Liana Rahman, Aqilah Salsabila Raja, Nur Alfianingsih Raupong Raupong Raupong, Raupong Richy Wijaya S Siswanto Sahriman, Sitti Sirajang, Nasrah Sonya, Sonya Suade, Yuyun Karystin Meilisa Taufiq Akbar Triany, Novika Ayu Trigarcia Maleachi Randa Victor Liman Waibusi, Hendriete Tiur Marowi