Article Per Year (5 Year)
p-Index From 2021 - 2026
1.116
P-Index
This Author published in this journals
All Journal JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Statistika Universitas Muhammadiyah Semarang AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Jurnal Kreativitas PKM Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika VARIANSI: Journal of Statistics and Its Application on Teaching and Research
Memi Nor Hayati
Universitas Mulawarman
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI

 1 
Forecasting Stock Price PT. Telkom Using Hybrid Time Series Regression Linear– Autoregressive Integrated Moving Average Model Kartika Ramadani; Sri Wahyuningsih; Memi Nor Hayati
Jurnal Matematika, Statistika dan Komputasi Vol. 18 No. 2 (2022): JANUARY 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v18i2.18837

Abstract

The hybrid method is a method of combining two forecasting models. Hybrid method is used to improve forecasting accuracy. In this study, the Time Series Regression (TSR) linear model will be combined with the Autoregressive Integrated Moving Average (ARIMA) model. The TSR linear model is used to obtain the model and residual value, then the residual value of the TSR linear model will be modeled by the ARIMA model. This combination method will produce a hybrid TSR linear-ARIMA model. The case study in this research is stock closing price (daily) of PT. Telkom Indonesia Tbk. The stock closing price (daily) of PT. Telkom Indonesia Tbk in 2020 showed an decreasing and increasing trend pattern. The results of this study obtained the best model of hybrid TSR linear-ARIMA (2,1,1) with the proportion of data training and testing is 70:30. In the best model, the MAD value is 56.595, the MAPE value is 1.880%, and the RMSE value is 78.663. It is also found that the hybrid TSR linear-ARIMA model has a smaller error value than the TSR linear model. The results of forecasting the stock price of PT. Telkom Indonesia Tbk for the period 02 January 2021 to 29 January 2021 formed a decreasing trend pattern.
Geographically Weighted Poisson Regression Model with Adaptive Bisquare Weighting Function (Case study: data on number of leprosy cases in Indonesia 2020) Ineu Sintia; Suyitno Suyitno; Memi Nor Hayati
Jurnal Matematika, Statistika dan Komputasi Vol. 19 No. 1 (2022): SEPTEMBER, 2022
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v19i1.21879

Abstract

Abstract Geographically Weighted Poisson Regression (GWPR) is a Poisson regression model which is applied on spatial data. The parameter estimation of GWPR is done in each observation location through spatial weighting. This study aims to determine the GWPR model of the number of leprosy cases in each province of Indonesia 2020 and to find the influencing factors. The research uses secondary data collected from Indonesian Ministry of Health and Central Statistics Agency. The spatial weighting is calculated by using the adaptive bisquare function, while the optimum bandwidth is determined by using Generalized Cross-Validation criteria (GCV). The parameter estimation of GWPR uses Maximum Likelihood Estimation (MLE) method. The result of research show that the closed form of Maximum Likelihood (ML) estimator can not be found analytically and that the approximation of ML estimator is found by using Newton-Raphson iterative method. Based on the parameter significance test of the GWPR model, the factors that influenced the number of leprosy cases locally are the percentage of households that have access to proper sanitation, population density, the percentage of people who experience health complaints and outpatient, the number of health workers, the percentage of poor people, the percentage of districts/cities that carry out healthy living community movement (GERMAS) and the percentage of habitable houses. While the factors that globally affected the number of leprosy cases are  the percentage of households that have access to proper sanitation, population density, the percentage of people who experience health complaints and outpatient, the number of health workers, the percentage of poor people, the percentage of districts/cities that carry out GERMAS.  
Co-Authors Darnah Darnah, Darnah Desi Yuniarti Dini Elizabeth Dwi Husnul Mubiin Ika Purnamasari Ineu Sintia Kartika Ramadani Khairun Nida M. Fathurahman Meiliyani Siringoringo Nur - Azizah Riska Veronika Rito Goejantoro, Rito Sekar Nur Utami Siti Mahmuda Sri Wahyuningsih Surya Prangga Suyitno Suyitno