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All Journal Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) BAREKENG: Jurnal Ilmu Matematika dan Terapan ESTIMASI: Journal of Statistics and Its Application STATISTIKA
Herdiani, Erna Tri
Department Of Statistics, Faculty Of Mathematics And Natural Science, Hasanuddin University, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Medicine & Pharmacology Physics Transportation

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Journal : ESTIMASI: Journal of Statistics and Its Application

 1 
Peramalan Jumlah Penumpang Kapal Laut Menggunakan Metode Fuzzy Runtun Waktu Chen Orde Tinggi Rizki Adiputra; Erna Tri Herdiani; Sitti Sahriman
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.v2i1.10328

Abstract

The port has become an important part of people's lives. On certain days there is an increase in the number of ship passengers which can slow down operational activities from the port, thus causing a buildup of passengers at the port. therefore, the port must be prepared to deal with the buildup of passengers at the port. Based on this, the researchers made a prediction or forecasting the number of ship passengers at Makassar Soekarno Hatta Port in the coming period to find out how much the estimated number of passengers at Makassar Soekarno Hatta Port. The results of these studies can be input to the PT. Pelabuhan Indonesia IV (Persero ) Makassar if there will be a surge in passengers in the future period. researchers used the fuzzy method of high order chen time series in forecasting or prediction in this study . The researcher divides the data onto training and testing data . The results of the study using fuzzy time series with the best high order chen are that the second order produces MAPE error size of 0,143 , MSE 13470993,9 and MAE of 9478,52 . The result of prediction of testing data onto one period in the future is 52.608.
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.
Peta Kendali Atribut Menggunakan Zero-Inflated Generalized Poisson Ratmila Mammi; Erna Tri Herdiani; Nasrah Sirajang
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.v4i2.12932

Abstract

If the variable is a discrete random variable with Poisson distribution, the data analysis must fulfill the equidispersion assumption. In reality, these assumptions are not fulfilled because the variance is greater than the mean which is called overdispersion. Overdispersion in data can occur due to the proportion of excess zero values in these variables. To estimate the parameters, the MLE method can be used on data that has a certain distribution by maximizing the likelihood function, it obtained is implicit or nonlinear so that it cant be solved analytically. To get the numerical solution, it solved by using the EM algorithm. The estimation results of the ZIGP distribution parameters are used to create control chart limits for the 2016 Neonatal Mortality Rate data in Makassar with limits of , , and . The  chart ARL value is , which is greater than the chart ARL value, which is  which indicates that the  chart is better at detecting outliers.
Peta Kendali p Berdasarkan Metode Peningkatan Transformasi Akar Kuadrat Rasyid, Riska; Herdiani, Erna Tri; Sunusi, Nurtiti
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.v5i1.18487

Abstract

When the proportion of nonconformities is small, the effectiveness of the  control chart performance becomes inadequate because it has a skewness that causes asymmetryc. Therefore, the Improved Square Root Transformation (ISRT) method is used to construct the  attribute control chart to increase the accuracy of the chart control limit which is called the ISRT-  control chart. In this study, the effectiveness of the ISRT-  control chart perfomance is compared with the  control chart after being applied to the data on the number of defects in the newspaper production process at PT. Radar Sulteng Membangun. The results showed that the production process at PT. Radar Sulteng Membangun was not in a statistically controlled and the ARL value obtained on the ISRT-  control chart is much smaller than the ARL value for the  control chart, so that the ISRT-  chart is more effective and sensitive to detecting changes in the production process which produces in a small proportion of nonconformities.
Analisis Regresi Data Panel Dengan Model Efek Umum, Model Efek Tetap Dan Model Efek Acak (Studi Kasus: Inflasi Dan Indeks Pembangunan Manusia) ada, Nuralyatussa’; Herdiani, Erna Tri; Sirajang, Nasrah
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.v5i2.33279

Abstract

Panel data regression analysis is a method for modeling the influence of independent variables on dependent variables, on a combination of cross-section and time-series data. This research aims to estimate a panel data regression model with a generalized effects model using the least squares method, estimate a fixed effects model with the Least Square Dummy Variable and estimate a random effects model with Generalized Least Square on inflation and human development index data. The results obtained show that the factors that have a significant influence at the 5% level on the inflation rate in 2014-2019 are the dollar exchange rate with a coefficient of determination of the general effects model of 61.06%, then the HDI level in South Sulawesi in 2011-2017 is significantly influenced by factors such as average length of schooling and life expectancy with a coefficient of determination of the fixed effects model of 89.73%, and the HDI level in South Sulawesi in 2016-2019 is significantly influenced by the factors of life expectancy, per capita expenditure and poverty with a coefficient of determination of the random effects model amounting to 63.07%.
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 ada, Nuralyatussa’ Aidawayati Rangkuti Andi Fitri Ayu Andi Kresna Jaya Andi waru A. Paluseri Anisa Anisa Anisa Anisa Arwini Arisandi Fathanah, Nur Fitriani Fitriani Georgina Maria Tinungki Ika Fitriana Irawaty Irawaty Maria Tinungki, Georgina Mayashari, Mayashari Mustabsyirah, Mustabsyirah Najamuddin, Fadhila Febriyanti Nasrah Sirajang Nasruddin, Nurmasyita Nirwan Ilyas Nuravia Nuravia Nurhidaya L NURTITI SUNUSI Puji Puspa Sari Rahman, Aqilah Salsabila Rasyid, Riska Ratmila Mammi Rizki Adiputra Saleh AF Samsul Arifin Sirajang, Nasrah Sitti Sahriman Sitti Sahriman Sonya, Sonya Sri Astuti Thamrin Suci Barlian Sari Takdir, Agung Muhammad