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All Journal EKSAKTA: Journal of Sciences and Data Analysis JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Media Ekonomi dan Manajemen 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) 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 Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Other

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The Determinants of Dividend Policy: An Empirical Study of Inconsistent Distribution of Dividends Using Balanced Panel Data Analysis Powell Gian Hartono; Wahyuni Rusliyana Sari; Georgina Maria Tinungki; Jakaria Jakaria; Agus Budi Hartono
Media Ekonomi dan Manajemen Vol 36, No 2 (2021): July 2021
Publisher : Fakultas Ekonomika dan Bisnis UNTAG Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (519.718 KB) | DOI: 10.24856/mem.v36i2.2023

Abstract

The inconsistent distribution of dividends is a unique phenomenon and it needs to be examined. Therefore, the purpose of this study is to examine ten predictors affecting dividend policy of the inconsistent distribution of dividends. This study used the purposive sampling method to analyze the data that were obtained from a total sample of 133 observation objects collected in the 19 real estates, property, and building construction companies listed on the IDX Between 2013 - 2019. Furthermore, the method used is hypotheses testing and statistical analysis tool used is the hierarchical multiple panel data regression with the Least Squares Dummy Variables. The results obtained from panel A are firm risk, financial leverage, and investment opportunity that affect the dividend policy. Meanwhile, the panel B results are company risk, financial leverage, investment opportunity, and previous dividend, although the previous dividend had no effect due to the different direction of influence. This study proves the determinants and relevance of the parametric statistical analysis in the inconsistent distribution of dividends. Moreover, it is useful for managerial practitioners to pay attention to predictors for increasing company performances and to ensure investors obtain optimal return of their dividend.
Estimasi Komponen Variansi pada Rancangan Faktorial Acak Lengkap Menggunakan Metode Generalized Least Squares A. Muthiah Nur Angriany; Georgina Maria Tinungki; Raupong Raupong
Jurnal Matematika, Statistika dan Komputasi Vol. 15 No. 2 (2019): JMSK Vol. 15, No. 2, January 2019
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (732.308 KB) | DOI: 10.20956/jmsk.v15i2.5714

Abstract

AbstractsExperiment design is a test or a row of test by using both statistical description and inference statistical. The aim of this test is to change an input to become an output as a respond of the experiment. In the experiment design, variance of factor A, B , AB error of variance are called as variant component. The aim of this study is to estimate variance component on complete random factorial design for fixed model and mixed model by using Generalized Least Squares (GLS)method, where GLS method as a development of Ordinary Least Square method. It used to be applied on data of complete random factorial design, namely like the influence to density pelleting food which is caused by increasing adhesive material and longtime in storage. The results  show that there is no influence of increasing adhesive material to the density of pelleting food. In addition, there exist of diversity of longtime of storage and there exists a diversity  interaction between adding adhesive material and long of time of storage to the density of pelleting food Keywords: Generalized Least Squares, variance component, complete random factorial design AbstrakPerancangan percobaan adalah suatu uji atau sederet uji baik itu menggunakan statistika deskripsi maupun statistika inferensi, yang bertujuan untuk mengubah peubah input menjadi suatu output yang merupakan respon dari percobaan tersebut. Dalam perancangan percobaan,  variansi dari faktor A, variansi dari faktor B, variansi interaksi faktor AB, dan variansi galat disebut dengan komponen varian. Penelitian ini bertujuan untuk mengestimasi komponen variansi pada rancangan faktorial acak lengkap model tetap dan model campuran  menggunakan metode Generalized Least Squares (GLS), dimana metode GLS adalah pengembangan dari metode Ordinary Least Square yang biasa  digunakan untuk mengatasi asumsi homogenitas yang biasa dilanggar dalam perancangan percobaan. Metode tersebut  diterapkan pada data rancangan faktorial acak lengkap yaitu pengaruh berat jenis pakan pellet dengan kombinasi perlakuan penambahan bahan perekat dan lama penyimpanan. Hasil menunjukkan bahwa tidak terdapat pengaruh penambahan bahan perekat terhadap berat jenis pakan pellet. Selain itu, terdapat keragaman faktor lama penyimpan dan terdapat keragaman interaksi  antara faktor penambahan perekat dan lama penyimpanan terhadap berat jenis pakan pellet. Kata kunci: Generalized Least Squares, komponen variansi, rancangan faktorial acak lengkap 
LIKUIDITAS SEBAGAI PREDIKTOR PROFITABILITAS: SEBUAH STUDI EMPIRIS PADA PERUSAHAAN SEKTOR INDUSTRI MANUFAKTUR Powell Gian Hartono; Henny Setyo Lestari; Richy Wijaya; Agus Budi Hartono; Georgina Maria Tinungki
Derivatif : Jurnal Manajemen Vol 14, No 2 (2020): November
Publisher : Universitas Muhammadiyah Metro Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/jm.v14i2.475

Abstract

The purpose of this study is to examine the effect of liquidity with proxies are the current ratio (CR), and the quick ratio (QR) to profitability with proxies are the return on assets (ROA) and the return on equity (ROE), on manufacturing sector companies listed on the Indonesia Stock Exchange with the research periods are 2014 - 2018. The purposive sampling method was used, and as many as twenty companies were sampled. The test uses multiple linear regression analysis; the stage are classical assumption test, the goodness of fit test, F-test, and T-test. The results obtained in the first model with ROA as the criterion are CR and QR as the significant predictors. The results obtained in the second model with ROE as the criterion is QR as the significant predictor, while CR has no significant effect to ROE. These results indicate that each profitability ratio is specifically influenced by the respective liquidity ratios studied so that companies can pay more attention to matters related to these variables in order to support efforts to increase company profitability.Keywords: Current Ratio, Manufacturing Company, Return on Assets, Return on Equity, Quick Ratio
The role of cooperative learning with team assisted individualization to improve the students’ self proficiency Georgina Maria Tinungki
Journal of Science and Science Education Vol 1 No 2 (2017): JoSSE Vol. 1 No. 2 (November 2017)
Publisher : Faculty of Science and Mathematics, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/josse.v1i2p63-73

Abstract

The importance of learning mathematics can not be separated from its role in all aspects of life. This research aims to analyze the achievement of the students’ self-proficiency who are taught by using cooperative learning with Team Assisted Individualization (TAI) and conventional learning. Students need to possess self-proficiency ability well so that they could have confidence that they are capable of confronting and of solving their daily life problems in general or mathematical tasks in particular. The population in this research was students of Statistics study program at one of public universities in Makassar. The sampling technique used in this research was purposive sampling, while the instrument used was self-proficiency scale (SPr) which has been validated. The data were analyzed by using parametric and non-parametric statistics. The result of this research is that the achievement of the students’ self-proficiency who are taught by using cooperative learning with TAI is better than students who are taught by using conventional learning.
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.
Overcoming the Existence of Extreme Outlier Data by Using Robust MM Method Based on The Objective Function of Tukey bisquare Georgina Maria Tinungki
SCIENCE NATURE Vol 1 No 1 (2018): SCIENCE NATURE
Publisher : Faculty of Mathematics and Natural Sciences, University of Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/SNvol1iss1pp022-032year2018

Abstract

A widely used estimation method in estimating regression model parameters is the ordinary least square (OLS) that minimizes the sum of the error squares. In addition to the ease of computing, OLS is a good unbiased estimator as long as the error component assumption () in the given model is met. However, in the application, it is often encountered violations of assumptions. One of the violation types is the violation of distributed error assumption which is caused by the existence of the outlier on observation data. Thus, a solid method is required to overcome the existence of outlier, that is Robust Regression. One of the Robust Regression methods commonly used is robust MM method. Robust MM method is a combination of breakdown point and high efficiency. Results obtained based on simulated data generated using SAS software 9.2, shows that the use of objective weighting function tukey bisquare is able to overcome the existence of extreme outlier. Furthermore, it is determined that the value of tuning constant c with Robust MM method is 4.685 and it is obtained95% of efficiency. Thus, the obtained breakdown point is 50%.
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 Proporsi Kasus Tuberkulosis di Sulawesi Selatan Menggunakan Sparse Least Trimmed Squares Trigarcia Maleachi Randa; Georgina Maria Tinungki; Nurtiti Sunusi
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 3, ISSUE 2, August 2022
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol3.iss2.art6

Abstract

The deadliest infectious disease in Indonesia is tuberculosis (TB), and South Sulawesi is one of the provinces that contributed the most tuberculosis cases in Indonesia in 2018 with 84 cases per 100,000 population. This study aims to identify variables that could explain the proportion of TB cases in South Sulawesi. The data used has many explanatory variables, and there are outliers. Sparse Least Trimmed Squares (LTS) analysis can be used to handle data that has many explanatory variables and outliers. The resulting sparse LTS model successfully selects and shrinks the variables to 14 variables only. In addition, based on the value of R2 and RMSE for the model evaluation, the sparse LTS shows satisfying results rather than classical LASSO. The government can focus on these factors if they want to reduce the proportion of TB cases in South Sulawesi.
Co-Authors A. Muthiah Nur Angriany Agus Budi Hartono Agus Budi Hartono Andi Isna Yunita Andi Kresna Jaya Anisa Anisa Asti Inayati Magfirah Fachry Abda El Rahman Fahrul Usman Fathanah, Nur Herdiani, Erna Tri Iis Cendrah kasih Jakaria Jakaria Kiandra Putri Susanto Lestari, Henny Setyo Mega Selvia Tjahaya Nasrah Sirajang Nurhidaya L NURTITI SUNUSI Powell Gian Hartono Rahman, Aqilah Salsabila Raja, Nur Alfianingsih Raupong Raupong Raupong, Raupong Richy Wijaya S Siswanto Sahriman, Sitti Sirajang, Nasrah Sonya, Sonya Taufiq Akbar Trigarcia Maleachi Randa Victor Liman Wahyuni Rusliyana Sari Waibusi, Hendriete Tiur Marowi