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All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam ESTIMASI: Journal of Statistics and Its Application

Raupong, Raupong

Hasanuddin University

Author-ID : 3591995

Education Mathematics

Published : 11 Documents Claim Missing Document

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Hubungan Faktor Kolestrol Terhadap Gula Darah Diabetes dengan Spline Kubik Terbobot Zhazha Alifkhamulki Ramdhani; Anna Islamiyati; Raupong Raupong
ESTIMASI: Journal of Statistics and Its Application Vol. 1, No. 1, Januari, 2020 : Estimasi
Publisher : Hasanuddin University

Diabetes Mellitus (DM) is often recognized through an increase in a person's blood sugar level. Factors that can affect the increase in blood sugar levels of DM patients one of which is cholesterol. It usually contains the bookkeeping of several types of cholesterol, including LDL and total cholesterol. DM data are assumed to experience heterokedasticity so that in this study analyzed using regression of weighted cubic spline nonparametric. The estimation method used is weighted least square (WLS). This study aims to obtain a weighted cubic spline model on cholesterol based DM data. The selection of the best model can be seen based on the criteria for the value of generalized cross validation (GCV) minimum. Based on the analysis obtained weighted cubic spline models for cholesterol factors for blood sugar as follows:

Kemampuan Estimator Spline Linear dalam Analisis Komponen Utama Samsul Arifin; Anna Islamiyati; Raupong Raupong
ESTIMASI: Journal of Statistics and Its Application Vol. 1, No. 1, Januari, 2020 : Estimasi
Publisher : Hasanuddin University

In the formation of a regression model there is a possibility of a relationship between one predictor variable with other predictor variables known as multicollinearity. In the parametric approach, multicollinearity can be overcome by the principal component analysis method. Principal component analysis (PCA) is a multivariate analysis that transforms the originating variables that are correlated into new variables that are not correlated by reducing a number of these variables so that they have smaller dimensions but can account for most of the diversity of the original variables. In some research data that do not form parametric patterns also allows the occurrence of multicollinearity on the predictor variables. This study examines the ability of spline estimators in the analysis of the main components. The data contained multicollinearity and was applied to diabetes mellitus data by taking cholesterol type factors as predictors. Based on the estimation results, one main component is obtained to explain the diversity of variables in diabetes data with the best linear spline model at one knot point.

Regresi Model Data Panel Efek Tetap dengan Metode Within Group pada Data Indeks Pembangunan Manusia Provinsi Sulawesi Selatan Andi Sitti Fahmi Riyanti Hufaini; Raupong Raupong; Nirwan Ilyas
ESTIMASI: Journal of Statistics and Its Application Vol. 1, No. 1, Januari, 2020 : Estimasi
Publisher : Hasanuddin University

This research aims to describe the parameter estimation of the regression model on the panel data by approaches of Fixed Effects Model with within a group method. This research aims to determine the factors that influence the Human Development Index in South Sulawesi Province in 2011-2017 using Panel Data Regression Analysis. The regression model was obtained from the maximum likelihood estimation using within group approach using a mean for each independent variable and the dependent variable to find out the intercept differences in each city or cross-section that explains the effect of regional differences and to find out the intercept differences for cross sectional or time series. The results showed that the average length of the school variable (????1) and life expectancy variable (X2) significantly affects the Human Development Index (Y) in the Province of South Sulawesi in 2011-2017.

Estimasi Parameter Structural Equation Modeling Terhadap Kepuasan Pelanggan Layanan Telekomunikasi Menggunakan Metode Maximum Likelihood Dwicahyo Ramadhan Priyatna; Raupong Raupong; La Podje Talangko
ESTIMASI: Journal of Statistics and Its Application Vol. 1, No. 1, Januari, 2020 : Estimasi
Publisher : Hasanuddin University

Structural Equation Modeling is a statistical technique that is able to analyze the pattern of simultan linear relationships between indicator variables and latent variables. In this study using structural equation modeling to analyze the relationship between perceived quality, perceived value, perceived bestscore, and customer satisfaction. The purpose of this study is to obtain the result parameter model estimation of structural equation modeling using maximum likelihood method and to obtain the level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator. Data collected by distributing questionnaire. Collecting sample in this study using Proporsional Random Sampling technique. To measure the level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator, the model chosen is the model used to measure Indonesian Customer Satisfaction Indeks. From the result of this study obtained in the amount of 92,04% with very satisfied criteria level of students satisfaction from faculty of Mathematics and Natural Science Hasanuddin University toward Tri operator with very satisfied criteria.

Estimasi Parameter Model Poisson Hidden Markov Pada Data Banyaknya Kedatangan Klaim Asuransi Jiwa Vieri Koerniawan; Nurtiti Sunusi; Raupong Raupong
ESTIMASI: Journal of Statistics and Its Application Vol. 1, No. 2, Juli, 2020 : Estimasi
Publisher : Hasanuddin University

The Poisson hidden Markov model is a model that consists of two parts. The first part is the cause of events that are hidden or cannot be observed directly and form a Markov chain, while the second part is the process of observation or observable parts that depend on the cause of the event and following the Poisson distribution. The Poisson hidden Markov model parameters are estimated using the Maximum Likelihood Estimator (MLE). But it is difficult to find analytical solutions from the ln-likelihood function. Therefore, the Expectation Maximization (EM) algorithm is used to obtain its numerical solutions which are then applied to life insurance data. The best model is obtained with 2 states or m = 2 based on the smallest Bayesian Information Criterion (BIC) value of 338,778 and the average predicted number of claims arrivals is 0.385 per day.

Pengaruh Indeks Massa Tubuh dan TrigliseridaTerhadap Gula Darah dengan Model Regresi Nonparametrik Spline Biprediktor Dewi Rahma Ente; Anna Islamiyati; Raupong Raupong
ESTIMASI: Journal of Statistics and Its Application Vol. 2, No. 2, Juli, 2021 : Estimasi
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/ejsa.v2i2.10262

The regression approach can be carried out using three approaches namely parametric, nonparametric and semiparametric approaches. Nonparametric regression is a statistical method used to see the relationship between the response variable and the predictor variable when the shape of the data curve is unknown. Diabetes mellitus (DM) or commonly called diabetes is a disease that is found and observed in various parts of the world today. DM is often marked by a significant increase in blood sugar levels. In this study using blood sugar levels as response variables, body mass index and triglycerides as predictor variables. Data were analyzed using truncated linear spline with one, two and three point knots experiments. The best model is obtained based on the minimum generalized cross validation (GCV) value. The results obtained that the best model is linear spline using three point knots.

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

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.

Rancangan Faktorial Model Campuran Menggunakan Metode Maksimum Likelihood Andi Tenri Riski Amalia; Raupong Raupong; Andi Kresna Jaya
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.11406

Variance is the amount of statistics which measures how far a set of numbers in observation are spread out from its mean. In experimental design, variance are caused by the effect of treatment, block and error of experimental can be estimated by variability of error that commonly referred to variance component. In this study, the maximum likelihood method with Hartley Rou modification was used followed by the Newton Raphson method which was applied to a complete randomized block factorial design mixed model with factor A being fixed and factor B being random. The results of this study for rice production data showed that there is a significant effect on the interaction of genotype and location on rice production. The estimated value of the variance component obtained indicates that there are variations in the influence of location factors, and genotype and location interaction factors on rice production.

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

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.

Estimasi Model Regresi Spline Kubik Tersegmen dengan Metode Penalized Least Square Anna Islamiyati; Anisa Anisa; Raupong Raupong; Jusmawati Massalesse; Nasrah Sirajang; Sitti Sahriman; Alfiana Wahyuni
Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Vol 10, No 2 (2022): Al-Khwarizmi : Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam had Accre
Publisher : Prodi Pendidikan Matematika FTIK IAIN Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24256/jpmipa.v10i2.3197

Abstract:Nonparametric regression is used for data whose data pattern is non-parametric. One of the estimators that can be developed is a segmented cubic spline which is able to show several segmentation changes in the data. This article examines the estimation of segmented cubic spline nonparametric regression models using the Penalized Least Square estimation criteria. The method involves knot points and smoothing parameters simultaneously. In addition, the model is used to analyze data on BPJS claims based on patient age. The results show that the optimal model is at two-knot points, namely 26 and 52 with a smoothing parameter of 0.89. There are three segmentation changes from the cubic data, which consist of young people up to 26 years old, 26-52 years old, and 52 years and over. Abstrak:Regresi nonparametrik digunakan untuk data yang pola datanya bentuk non parametrik. Salah satu estimator yang dapat dikembangkan adalah spline kubik tersegmen yang mampu menunjukkan beberapa segmentasi perubahan pada data. Artikel ini mengkaji estimasi model regresi nonparametrik spline kubik tersegmen melalui kriteria estimasi menggunakan Penalized Least Square. Metode tersebut melibatkan titik knot dan parameter penghalus secara bersamaan. Selain itu, model digunakan untuk menganalisis data klaim BPJS berdasarkan usia pasien. Hasil menunjukkan bahwa model optimal pada dua titik knot yaitu 26 dan 52 dengan parameter penghalus sebesar 0,89. Terdapat tiga segmentasi perubahan data secara kubik, yaitu usia muda hingga 26 tahun, usia 26-52 tahun, dan usia 52 tahun ke atas.

Co-Authors Alfiana Wahyuni Andi Kresna Jaya Andi Sitti Fahmi Riyanti Hufaini Andi Tenri Riski Amalia Anisa Anisa Anna Islamiyati Anna Islamiyati Asti Inayati Magfirah Dewi Rahma Ente Dwicahyo Ramadhan Priyatna Georgina Maria Tinungki Jusmawati Massalesse La Podje Talangko Mega Selvia Tjahaya Nasrah Sirajang Nirwan Ilyas Nur Aminah Ahmad NURTITI SUNUSI Samsul Arifin Sitti Sahriman Vieri Koerniawan Zhazha Alifkhamulki Ramdhani

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