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All Journal ELS Journal on Interdisciplinary Studies in Humanities Parameter: Journal of Statistics Bulletin of Applied Mathematics and Mathematics Education
Octaviana, Dita
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Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Mathematics Social Sciences

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Applying negative binomial regression analysis to overcome the overdispersion of Poisson regression model for malnutrition cases in Indonesia Setyawan, Yudi; Suryowati, Kris; Octaviana, Dita
Bulletin of Applied Mathematics and Mathematics Education Vol. 2 No. 2 (2022)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/bamme.v2i2.4948

Abstract

Indonesia is one of the developing countries that is struggling to eradicate malnutrition problem. Malnutrition that occurs over a long period of time can have an impact on deaths for the sufferers and decreasing human’s quality of life. This study aims to model the case of malnutrition that occurred in Indonesia Provinces during 2015, and get the main factors that cause malnutrition problem. Variables studied consists of Malnutrition (Y), Vitamin A consumption (X1), Exclusive breastfeeding (X2), Immunization (X3), Water quality (X4), Healthcare center (X5), and Poverty level (X6). Based on the Kolmogorov-Smirnov test, the results of malnutrition data in Indonesia Province in 2015 does not follow Poisson distribution because of overdispersion. The presence of overdispersion cases in the Poisson regression model will have an impact on the inappropriateness of inferences. An alternative model that can accomodate this case is negative binomial regression model.  By using this model, factors that are considered influencing malnutrition cases in Indonesia provinces in 2015 are Immunization (X3), Water quality (X4), and Poverty level (X6). The best model obtained from negative binomial regression analysis is μ ̂_i=exp(2.5111-0.0338X_3+0.0295X_4+0.0576X_6).
Improving Student’s English Vocabulary Mastery through Scattergories Game Octaviana, Dita; Hastini, Hastini; R Mertosono, Sudarkam; Mahrum, Mochtar
ELS Journal on Interdisciplinary Studies in Humanities Vol. 8 No. 2 (2025): JUNE
Publisher : Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34050/els-jish.v8i2.44398

Abstract

The intent of this study is to determine whether employing Scattergories Game is effective in order to enhance the vocabulary mastery of grade eighth students of SMP Negeri 2 Palu. The pre-experimental research design was utilized by the researcher. In determining the sample, the researcher employed a purposive sampling technique. The selected sample was class VIII B, comprising 32 students. Data were obtained through the use of both pre-tests and post-tests. The outcomes of the data analysis indicates that the mean score of student’s post-tests 85.06 is higher than students pretest score 57.97. The research findings that the t-counted value (31.157) is higher than the t-table value (2.039). This indicates that the hypothesis of the study is accepted. In conclusion, scattegories game is effective to improve students' vocabulary mastery of the student’s grade at SMP Negeri 2 Palu
Application of Negative Binomial Regression Analysis to Overcome the Overdispersion of Poisson Regression Model for Malnutrition Cases in Indonesia Setyawan, Yudi; Suryowati, Kris; Octaviana, Dita
Parameter: Journal of Statistics Vol. 2 No. 2 (2022)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/27765660.2022.v2.i2.15903

Abstract

Indonesia is one of the developing countries that is struggling to eradicate the malnutrition problem. Malnutrition that occurs over a long period of time can have an impact on the deaths of sufferers and decrease human quality of life. This study aims to model the case of malnutrition that occurred in Indonesia Provinces during 2015 and get the main factors that cause the malnutrition problem. Variables studied consist of Malnutrition (Y), Vitamin A consumption (X1), Exclusive breastfeeding (X2), Immunization (X3), Water quality (X4), Healthcare center (X5), and Poverty level (X6). Based on the Kolmogorov-Smirnov test, the results of malnutrition data in Indonesia Province in 2015 do not follow Poisson distribution because of overdispersion. The presence of overdispersion cases in the Poisson regression model will have an impact on the inappropriateness of inferences. An alternative model that accommodates this case is the negative binomial regression model. By using this model, factors that are considered influencing malnutrition cases in Indonesia provinces in 2015 are Immunization (X3), Water quality (X4), and Poverty level (X6).
Co-Authors Hastini, Hastini Kris Suryowati, Kris Mahrum, Mochtar R Mertosono, Sudarkam Setyawan, Yudi