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All Journal Sciencestatistics: Journal of Statistics, Probability, and Its Application
Juanda Juanda
Universitas Lampung
Computer Science & IT Decision Sciences, Operations Research & Management Mathematics

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Artificial Neural Network (ANN) Classification: Titanic Passenger Safety Juanda Juanda; Khoirin Nisa
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol. 1 No. 2 (2023): JULY
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/sciencestatistics.v1i2.5074

Abstract

Scientific and technological innovation has always been the main driver of economic growth and social progress. The rapid development of technology and advances in the internet have made it possible to disseminate information and interact more easily. With the rapid development of technology, a lot of information is shared every second, resulting in big data in terms of different, complex variables. ANN is the result of work in the computer field that is inspired by the capabilities of the human brain which consists of biological neural networks. In recent years, the use of artificial neural networks (ANN) has increased. The research carried out aims to analyze the survival capabilities of Titanic passengers who experienced an accident while sailing and sank. This research uses initial data of 1309 observations with 14 variables. From the research results, 2 hidden variables are the most accurate with an accuracy of 80.5%, compared to the number of hidden variables of 3 (79%) and 4 (79%). So it can be concluded that the number of hidden variables with the same number of hidden screens does not have a significant difference in accuracy
Loglinier Model on Immunization of Baduta Juanda Juanda
Sciencestatistics: Journal of Statistics, Probability, and Its Application Vol. 2 No. 1 (2024): JANUARY
Publisher : Universitas Muhammadiyah Metro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24127/sciencestatistics.v2i1.5529

Abstract

This study aims to analyze the relationship between the type of immunization and the province of origin of children under two years of age (BADUTA) in Indonesia in 2020. This study uses a loglinear model approach to analyze DPT-HB-Hib4 and Measles/MR2 immunization data based on gender and home province. Data was obtained from the Directorate General of Disease Prevention and Control of the Indonesian Ministry of Health. Through statistical analysis using IBM SPSS Statistics 22 software, this research found that there is a relationship between the type of immunization and the child's province of origin. The chi-square test results show that there is a significant relationship between the type of immunization and the child's province of origin. Of the several loglinear models tested, the (J, VP) model is considered the best model based on Goodness-of-fit criteria. Thus, this study concludes that there is a relationship between the type of immunization and the province of origin of children under two years old in Indonesia in 2020.
Co-Authors Khoirin Nisa