Pemodelan Kasus Pneumonia Berat pada Balita di Kota Surabaya Menggunakan Zero-Inflated Negative Binomial
DOI:
https://doi.org/10.59632/leibniz.v6i01.730Keywords:
nol berlebih, overdispersi, pneumonia berat pada balita, Zero-Inflated Negative BinomialAbstract
Pneumonia berat pada balita merupakan salah satu permasalahan kesehatan masyarakat yang signifikan, khususnya di perkotaan seperti Surabaya, karena dapat meningkatkan risiko morbiditas dan mortalitas balita. Data jumlah kasus pneumonia berat pada balita di Kota Surabaya berbentuk data cacah yang menunjukkan adanya overdispersi serta proporsi nilai nol berlebih. Penelitian ini bertujuan untuk memodelkan jumlah kasus pneumonia berat pada balita di Kota Surabaya menggunakan model Zero-Inflated Negative Binomial (ZINB) serta mengidentifikasi faktor-faktor yang memengaruhinya. Analisis awal menggunakan regresi Poisson menunjukkan ketidaksesuaian asumsi akibat overdispersi dan nilai nol berlebih, sehingga pemodelan dilanjutkan menggunakan beberapa pendekatan termasuk regresi ZINB. Pemilihan model dilakukan berdasarkan nilai Akaike Information Criterion (AIC). Hasil analisis menunjukkan bahwa model ZINB memiliki nilai AIC paling rendah dan mampu mengakomodasi karakteristik data dengan baik. Pada model ZINB, variabel jumlah rumah tangga dengan akses air bersih terbukti berpengaruh signifikan pada komponen count maupun pada komponen logit. Selain itu, variabel dummy tahun 2023 juga berpengaruh signifikan pada komponen count, yang menunjukkan jumlah kasus pneumonia berat yang lebih rendah dibandingkan dengan tahun 2022. Hasil ini menunjukkan bahwa akses air bersih merupakan faktor lingkungan yang berperan penting dalam menurunkan jumlah kasus pneumonia berat pada balita di Kota Surabaya.
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