Kuntoro Kuntoro
Faculty of Public Health, Universitas Airlangga, 60115 Surabaya, East Java, Indonesia

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APPLICATION OF THE HOLT-WINTERS EXPONENTIAL SMOOTHING METHOD ON THE AIR POLLUTION STANDARD INDEX IN SURABAYA Silmi Muna; Kuntoro Kuntoro
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 10 No. 1 (2021): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v10i1.2021.53-60

Abstract

The Air Pollution Standards Index (APSI) is an indicator that shows how clean or polluted the air is in a city. It also portrays the health impacts towards the people who breathe it in. Based on the Indonesian Ministry of Environment monitoring through the Air Quality Monitoring Station (AQMS), the city of Surabaya only had 22 up to 62 days of air categorized as good in a year. The purpose of this study was to forecast APSI as a scientific-based reference for making decisions and policies that were appropriate in tackling the effects of air pollution on health. This study was non-obstructive or non-reactive research. The research method used was time series to identify the time relationship. The data used were secondary data taken from the APSI documents from 2014 to 2019 at the Surabaya City Environment Agency. The results of this study obtained the best model through α (0.8), γ (0.5), and δ (0.6) with the values of MAPE (0.104355), MAD (0.00842), and MSD (0.001050) calculated with the Holt-Winters exponential smoothing method. The highest produced forecast value of APSI was in September 2020, and the smallest was in January 2020. This study suggests the government of Surabaya to create policies and programs to suppress the number within APSI.
DIFFERENCE OF POWER TEST AND TYPE II ERROR (β) ON MARDIA MVN TEST, HENZE ZIKLER'S MVN TEST, AND ROYSTON'S MVN TEST USING MULTIVARIATE DATA ANALYSIS Wahyul Anis; Kuntoro Kuntoro; Soenarnatalina Melaniani
Jurnal Biometrika dan Kependudukan (Journal of Biometrics and Population) Vol. 10 No. 2 (2021): JURNAL BIOMETRIKA DAN KEPENDUDUKAN
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jbk.v10i2.2021.153-161

Abstract

The Mardia MVN test, Henze Zikler's MVN test, and Royston's MVN test are the most widely used tests to analyze multivariate normal (MVN) data, but there have not been many studies explaining the advantages and disadvantages of these tests. The research objective was to analyze the difference in test strength and type II (β) error in the Mardia MVN test, Henze Zikler's MVN test, and Royston's MVN test. The research data were analyzed using three MVN tests, namely the Mardia MVN test, Henze Zikler's MVN test, and Royston's MVN test. The results of the analysis in the form of test strength and type II error (β) would be compared at alpha (α) 1%, 5%, 10%, 15%, 20%, and 25%. The comparison results explained that the Mardia test had the greatest test strength and the smallest type II (β) error. The study concluded that the Mardia MVN test was a multivariate normal test better than Henze Zikler's MVN test and Royston's MVN test.