Angesti, Shafira Jasmine (2025) Pemodelan Kasus Balita Diare Di Kabupaten Tuban Dengan Metode Geographically Weighted Negative Binomial Regression. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Kabupaten Tuban yang terletak di Provinsi Jawa Timur mencatat adanya peningkatan jumlah kasus diare balita selama periode 2020-2022, dengan cakupan pelayanan yang belum optimal. Selain itu, metode penelitian mengenai kejadian diare pada balita di Kabupaten Tuban masih sangat terbatas. Penyebaran diare dipengaruhi oleh kondisi lingkungan sekitar, sehingga pendekatan spasial diperlukan dalam memahami faktor-faktor yang memengaruhinya. Metode analisis yang digunakan adalah Geographically Weighted Negative Binomial Regression (GWNBR). Pembobot yang digunakan adalah fungsi adaptive bisquare kernel dan fungsi adaptive tricube kernel. Variabel prediktor yang digunakan dalam penelitian ini meliputi persentase balita yang menerima ASI eksklusif, persentase pemberian vitamin A pada balita, persentase balita yang menerima imunisasi campak, dan persentase rumah tangga dengan cakupan air bersih serta digunakan variabel exposure berupa jumlah balita. Hasil penelitian menunjukkan tidak adanya perbedaan yang signifikan antara model Negative Binomial Regression (NBR) dengan model GWNBR. Berdasarkan nilai AICc, model NBR dengan variabel exposure merupakan model terbaik, karena menghasilkan nilai AICc terkecil daripada model lainnya. Variabel yang berpengaruh terhadap jumlah kasus balita adalah persentase balita yang menerima ASI eksklusif dan persentase pemberian vitamin A.
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Tuban Regency, located in East Java Province, has recorded an increase in the number of diarrhea cases among children under five during the 2020–2022 period, with suboptimal service coverage. Furthermore, research method on childhood diarrhea cases in Tuban Regency remains limited. Since diarrhea transmission is influenced by environmental conditions, a spatial approach is needed to understand the contributing factors. The analysis method used in this study is Geographically Weighted Negative Binomial Regression (GWNBR), with adaptive bisquare kernel and adaptive tricube kernel functions as weighting schemes. The predictor variables include the percentage of children under five receiving exclusive breastfeeding, the percentage receiving vitamin A supplementation, the percentage receiving measles immunization, and the percentage of households with access to clean water. An exposure variable in the form of the number of children under five is also included. The results show no significant difference between the Negative Binomial Regression (NBR) model and the GWNBR model. Based on the corrected Akaike Information Criterion (AICc), the NBR model with an exposure variable is the best model, as it yields the lowest AICc value among all models. The significant factors affecting the number of diarrhea cases among children under five are the percentage of children receiving exclusive breastfeeding and vitamin A supplementation.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Diare, Exposure, Geographically Weighted Negative Binomial Regression, Diarrhea, Exposure, Geographically Weighted Negative Binomial Regression |
| Subjects: | H Social Sciences > HA Statistics > HA30.6 Spatial analysis H Social Sciences > HA Statistics > HA31.3 Regression. Correlation. Logistic regression analysis. Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Faculty of Science and Data Analytics (SCIENTICS) > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Shafira Jasmine Angesti |
| Date Deposited: | 04 Aug 2025 08:46 |
| Last Modified: | 04 Aug 2025 08:46 |
| URI: | http://repository.its.ac.id/id/eprint/127193 |
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