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All Journal Jambura Journal of Mathematics Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) ESTIMASI: Journal of Statistics and Its Application Indonesian Journal of Statistics and Its Applications
Sitti Sahriman
Statistics Department, Faculty Of Mathematics And Natural Sciences, Hasanuddin University
Humanities Computer Science & IT Education Engineering Mathematics Public Health Other

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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.
Model ARIMA dengan Variabel Eksogen dan GARCH pada Data Kurs Rupiah Ririn Arianti; Sitti Sahriman; La Podje Talangko
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.11603

Abstract

Autoregressive integrated moving average with exegenous variable (ARIMAX) model is the development of ARIMA model with addition of other time series data as exogenous variable that affect the dependent variable. ARIMAX model is used to analyze and predict data on the rupiah exchange rate against the US dollar with inflation as an exogenous variabel. The exchange rate has an residual variance that is not constant  so that the GARCH model is used to overcome the problem of heteroscedasticity. The results of this research show that forecasting the rupiah exchange rate against the US dollar fot the period January 2010 – December 2019 with the ARIMAX(0,1,1) – GARCH(1,0) model is the best model with a MAPE (1,1655) value which shows a low percentage compared to the ARIMAX model.
Penerapan Metode Stepwise dan Dominance Analysis Pada Regresi Logistik Biner (Studi Kasus: Data Hipertensi Di Indonesia) Muhammad Idman; La Podje Talangko; Sitti Sahriman
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.12211

Abstract

Binary logistic regression is a method to describe the relationship between response variable that has two categories and one or more predictor variables. One of methods that can be used to obtain best model in logistic regression is stepwise. Stepwise method is a method that sets  and  as criteria to build model. Dominance analysis is used in this research to determine the importance rank of predictor variables by comparing the coefficient of determination  value before and after the predictor variable entered the model. Binary logistic regression can be used to find the relationship between hypertension and the factor risks. This study aims to obtain best model and to obtain the importace rank each predictor variable of binary logistic regression on data of hypertension in Indonesia. The result of this study shows that best model which is obtained is model with predictor variable of Heart Problems, High Cholesterol, Kidney Disease, Imperfect Vision, Breathlessness, and Nausea/ Vomitting. According to the value of  McFadden, predictor variable of High Cholesterol infests first rank in the importance of predictor variable or gives the greatest contributions in explaining variety of Status of Hypertension than other predictor variables.Binary logistic regression is a method to describe the relationship between response variable that has two categories and one or more predictor variables. One of methods that can be used to obtain best model in logistic regression is stepwise. Stepwise method is a method that sets  and  as criteria to build model. Dominance analysis is used in this research to determine the importance rank of predictor variables by comparing the coefficient of determination  value before and after the predictor variable entered the model. Binary logistic regression can be used to find the relationship between hypertension and the factor risks. This study aims to obtain best model and to obtain the importace rank each predictor variable of binary logistic regression on data of hypertension in Indonesia. The result of this study shows that best model which is obtained is model with predictor variable of Heart Problems, High Cholesterol, Kidney Disease, Imperfect Vision, Breathlessness, and Nausea/ Vomitting. According to the value of  McFadden, predictor variable of High Cholesterol infests first rank in the importance of predictor variable or gives the greatest contributions in explaining variety of Status of Hypertension than other predictor variables.
Co-Authors Afifah Afifah Ainun Mawaddah Abdal Alfiana Wahyuni Anisa Anisa Anisa Anisa Anisa Kalondeng Anna Islamiyati Anna Islamiyati Bunga Aprilia Edy Saputra Rusdi Herdiani, Erna Tri I Gusti Agung Komang Diafari Djuni Hartawan Irma Andriani Jusmawati Massalesse Jusmawati Massalesse Kasbawati Kasbawati La Podje Talangko Muhammad Idman Muralia Hustim Naimah Aris Najhah Aris Nasrah Sirajang Nur Erawaty Nurdin Nurdin Okta Nofri Raupong, Raupong Ririn Arianti Rizki Adiputra Sakinah Oktoni Sri Astuti Thamrin Vieri Koerniawan