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All Journal EKSAKTA: Journal of Sciences and Data Analysis Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Matematika UNAND InPrime: Indonesian Journal Of Pure And Applied Mathematics ESTIMASI: Journal of Statistics and Its Application PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Journal of Mathematics, Computation and Statistics (JMATHCOS) Indonesian Journal of Statistics and Its Applications
NURTITI SUNUSI
Department Of Statistics, Faculty Of Mathematics And Natural Science, Hasanuddin University, Makassar, Indonesia.
Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Transportation Other

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Journal : ESTIMASI: Journal of Statistics and Its Application

 1 
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (259.075 KB) | DOI: 10.20956/ejsa.v1i2.9302

Abstract

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.
Pemodelan Regresi Nonparametrik Spline Poisson Pada Tingkat Kematian Bayi di Sulawesi Selatan Novilia Jao; Anna Islamiyati; Nurtiti Sunusi
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.11997

Abstract

Poisson regression analysis is a method used to analyze the relationship between predictor variables and response variables with a Poisson distribution. However, not all data have an orderly pattern, so the Poisson regression is not appropriate to use. To solve this problem, a multivariable Poisson nonparametric regression with a spline truncated estimator was used. In this research, the estimation parameters of multivariable Poisson nonparametric regression was applied to data of infant mortality rates in South Sulawesi in 2017. The infant mortality rate can be measured from the number of infant deaths under one year. The method of selecting the optimal knot point uses the Generalized Cross Validation (GCV) method. The best model is formed on a linear spline model with one knot point. Based on the estimation of the parameters formed, it shows that the variable number of babies with low birth weight (x1) and the number of infants who are exclusively breastfed (x3) significantly affect the number of infant deaths.  Keywords: GCV, Multivariable Nonparametric Regression, Poisson, Spline Truncated, Total Infant Mortality.
Analisis Peluang Steady State Pada Kasus Covid-19 di Indonesia Menggunakan Rantai Markov Ika Pratiwi Haya; Andi Kresna Jaya; Nurtiti Sunusi
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.24802

Abstract

Covid-19 in Indonesia began to be recorded on March 2, 2020 with the number of positive patient cases as many as 2 people with the passage of time Covid-19 cases in Indonesia are always increasing. To see the development of Covid-19 cases in the future period, the opportunity for the number of Covid-19 cases can be used using the Markov chain. The Markov chain method is carried out using a transition probability matrix which is seen from the number of additions to positive Covid-19 patients in a steady state or a situation for a long period of time. Based on the results of the range of additions to the number of positive cases of Covid-19, 6 states were used. Furthermore, the calculation of the Markov Chain in the stationary state of Covid-19 cases in Indonesia after 328 days or 11 months obtained the probability of each state, namely state 1 of 0.0005, state 2 of 0.0069, state 3 of 0.1707, state 4 of 0.1462, state 5 of 0.1884 , and state 6 is 0.4873. Prediction of the addition of positive Covid-19 patients obtained results as many as 2058 patients in state 5 for July 1, 2022 with actual data as many as 2049 patients.
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.
Co-Authors Aceng Komarudin Mutaqin Agus Yodi Gunawan Andi Kresna Jaya Anna Islamiyati Caesar, Nadia Nazwadiah Edy Saputra Rusdi Georgina M. Tinungki Georgina Maria Tinungki Hedi Kuswanto Herdiani, Erna Tri Ika Pratiwi Haya Masjidil Aqsha Miolo, Alya Safira Irtiqa Nasrah Sirajang Nina Fitriyati Nirwan Ilyas Nirwan Nirwan Novilia Jao Nur Aminah Ahmad Puji Puspa Sari Ramadhani, Nur Aliah Rasyid, Herlina Rasyid, Riska Raupong, Raupong S Siswanto Siswanto Siswanto Sri Wahyuningsih Sutawanir Darwis Trigarcia Maleachi Randa Vieri Koerniawan YULIANA.DEWI Putri Zainuddin, Zaraswati Dwyana