Modeling of the Number of Toddler Pneumonia Sufferers in DKI Jakarta using Negative Binomial Regression
Acute lung tissue infection caused by various microorganisms, including fungi, viruses, and bacteria, is known as pneumonia. Pneumonia is the highest cause of child death worldwide. In Indonesia, pneumonia remains the leading cause of death among toddler (12-59 months old). By 2021, the national co...
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| Format: | Article |
| Language: | English |
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cita konsultindo
2024-01-01
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| Series: | Asian Journal of Management, Entrepreneurship and Social Science |
| Subjects: | |
| Online Access: | https://www.ajmesc.com/index.php/ajmesc/article/view/639 |
| _version_ | 1797366343858651136 |
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| author | Lucky Simarda Dian Lestari Fevi Novkaniza Arman Haqqi Sindy Devila |
| author_facet | Lucky Simarda Dian Lestari Fevi Novkaniza Arman Haqqi Sindy Devila |
| author_sort | Lucky Simarda |
| collection | DOAJ |
| description |
Acute lung tissue infection caused by various microorganisms, including fungi, viruses, and bacteria, is known as pneumonia. Pneumonia is the highest cause of child death worldwide. In Indonesia, pneumonia remains the leading cause of death among toddler (12-59 months old). By 2021, the national coverage of pneumonias among toddler was 34.8%, and the provinces with the highest coverage for toddler pneumonia were DKI Jakarta (53.0%), Banten (46.0%), and West Papua (45,7%). To find out the pattern of the relationship between the number of young people with pneumonia and the variables that affect it, a custom mathematical model is needed. The number of cases of toddler pneumonia in DKI Jakarta is a data count distributed by Poisson. Poisson regression is perfectly suitable for analyzing data that qualifies equidispersion. However, on the data, the number of toddler pneumonia cases in DKI Jakarta does not meet the equidispersion condition because the variance value is greater than the average or is called overdispersion. One of the methods developed to deal with overdispersion is negative binomial regression. The analysis showed that the average case of toddler pneumonia in Jakarta DKI was 454, Duren Sawit district recorded the highest case of 1329 cases and Sawah Besar district recorded the lowest case as 50 cases. The AIC criteria indicate that the Negative Binomial Regression model is a suitable model for modeling the number of cases of toddler pneumonia in Jakarta DKI with the smallest AIC value of 592,57. The best modeling results using the negative binomial regression method show two significant variables, they are the numbers of toddlers given exclusive breastfeeding and the numbers toddlers that were affected by covid-19.
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| first_indexed | 2024-03-08T17:03:49Z |
| format | Article |
| id | doaj.art-4f439b1440274f5bb4820e5dd60409ca |
| institution | Directory Open Access Journal |
| issn | 2808-7399 |
| language | English |
| last_indexed | 2024-03-08T17:03:49Z |
| publishDate | 2024-01-01 |
| publisher | cita konsultindo |
| record_format | Article |
| series | Asian Journal of Management, Entrepreneurship and Social Science |
| spelling | doaj.art-4f439b1440274f5bb4820e5dd60409ca2024-01-04T06:32:49Zengcita konsultindoAsian Journal of Management, Entrepreneurship and Social Science2808-73992024-01-01401Modeling of the Number of Toddler Pneumonia Sufferers in DKI Jakarta using Negative Binomial RegressionLucky Simarda0Dian Lestari1Fevi Novkaniza2Arman Haqqi3Sindy Devila4Department of Mathematics , Faculty of Mathematics and Natural Science, Universitas IndonesiaDepartment of Mathematics , Faculty of Mathematics and Natural Science, Universitas IndonesiaDepartment of Mathematics , Faculty of Mathematics and Natural Science, Universitas IndonesiaDepartment of Mathematics , Faculty of Mathematics and Natural Science, Universitas IndonesiaDepartment of Mathematics , Faculty of Mathematics and Natural Science, Universitas Indonesia Acute lung tissue infection caused by various microorganisms, including fungi, viruses, and bacteria, is known as pneumonia. Pneumonia is the highest cause of child death worldwide. In Indonesia, pneumonia remains the leading cause of death among toddler (12-59 months old). By 2021, the national coverage of pneumonias among toddler was 34.8%, and the provinces with the highest coverage for toddler pneumonia were DKI Jakarta (53.0%), Banten (46.0%), and West Papua (45,7%). To find out the pattern of the relationship between the number of young people with pneumonia and the variables that affect it, a custom mathematical model is needed. The number of cases of toddler pneumonia in DKI Jakarta is a data count distributed by Poisson. Poisson regression is perfectly suitable for analyzing data that qualifies equidispersion. However, on the data, the number of toddler pneumonia cases in DKI Jakarta does not meet the equidispersion condition because the variance value is greater than the average or is called overdispersion. One of the methods developed to deal with overdispersion is negative binomial regression. The analysis showed that the average case of toddler pneumonia in Jakarta DKI was 454, Duren Sawit district recorded the highest case of 1329 cases and Sawah Besar district recorded the lowest case as 50 cases. The AIC criteria indicate that the Negative Binomial Regression model is a suitable model for modeling the number of cases of toddler pneumonia in Jakarta DKI with the smallest AIC value of 592,57. The best modeling results using the negative binomial regression method show two significant variables, they are the numbers of toddlers given exclusive breastfeeding and the numbers toddlers that were affected by covid-19. https://www.ajmesc.com/index.php/ajmesc/article/view/639Count Data, Overdispersion, Poisson Regression |
| spellingShingle | Lucky Simarda Dian Lestari Fevi Novkaniza Arman Haqqi Sindy Devila Modeling of the Number of Toddler Pneumonia Sufferers in DKI Jakarta using Negative Binomial Regression Asian Journal of Management, Entrepreneurship and Social Science Count Data, Overdispersion, Poisson Regression |
| title | Modeling of the Number of Toddler Pneumonia Sufferers in DKI Jakarta using Negative Binomial Regression |
| title_full | Modeling of the Number of Toddler Pneumonia Sufferers in DKI Jakarta using Negative Binomial Regression |
| title_fullStr | Modeling of the Number of Toddler Pneumonia Sufferers in DKI Jakarta using Negative Binomial Regression |
| title_full_unstemmed | Modeling of the Number of Toddler Pneumonia Sufferers in DKI Jakarta using Negative Binomial Regression |
| title_short | Modeling of the Number of Toddler Pneumonia Sufferers in DKI Jakarta using Negative Binomial Regression |
| title_sort | modeling of the number of toddler pneumonia sufferers in dki jakarta using negative binomial regression |
| topic | Count Data, Overdispersion, Poisson Regression |
| url | https://www.ajmesc.com/index.php/ajmesc/article/view/639 |
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