Pemodelan Jumlah Kematian Ibu di Provinsi Sulawesi Selatan Menggunakan Regresi Binomial Negatif

Sauddin, Adnan; Auliah, Nur Indah; Alwi, Wahidah

doi:10.24252/msa.v8i2.17409

Cited by 3 publications

(3 citation statements)

References 1 publication

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“…10 In Bulukumba District, ten incidents of maternal death caused by delays in delivery assistance and limited access to quality health care facilities, especially for pregnant women in the 3T Regions (tertinggal = underdeveloped, terdepan/terjauh = remote, and terluar = frontier/outer). 10,11 The number of health facilities in Bulukumba District consists of nine polyclinics and 20 public health centers (PHC). However, there is only one referral hospital and maternity home for pregnant women.…”

Section: Mmr Inmentioning

confidence: 99%

Key Success Factors in Maternity Waiting Home Implementation: A Qualitative Study in Rural Indonesia

Wenang

Dewi

Emilia

et al. 2023

Preprint

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Background Maternal mortality remains a major challenge to health systems worldwide. One of its main causes is the limited number of health workers and facilities for pregnant women in rural areas. To reduce maternal mortality rates, Indonesia has instated policies to support the implementation of Maternity Waiting Homes (MWHs). Bulukumba District is located in an MWHs implementation area and is representative of the mainland and ocean countryside. Thus, the Bulukumba District was used in this study to investigate the key success factors in MWHs implementation. Methods This is a qualitative study with an exploratory approach. This research was conducted in Bulukumba, South Sulawesi, a rural area in Indonesia, in 2020. Data was collected through focus group discussions (FGD) involving public and civil parties (n = 10), government members (n = 14), professional organizations (n = 8), and local community members (n = 12). The NVivo Release 1.0 software was used in this study’s analysis to code and categorize the transcripts. Results Three themes were identified: stakeholders’ experience in managing MWHs in rural areas, efforts to increase the implementation of MWHs by stakeholders, and stakeholder expectations regarding the implementation of MWHs. Conclusions The key success factors in MWH implementation are leadership and collaboration with each stakeholder. Additionally, the stakeholders’ experiences, efforts, and expectations of MWH implementation can decrease the maternal mortality rate in rural areas.

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Section: Mmr Inmentioning

confidence: 99%

Key Success Factors in Maternity Waiting Home Implementation: A Qualitative Study in Rural Indonesia

Wenang

Dewi

Emilia

et al. 2023

Preprint

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“…Model regresi Binomial negative merupakan model yang berasal dari distribusi poisson-gamma mixture yang merupakan penerapan dari General Linear Model yang menggambarkan hubungan antara variabel dependen dengan variabel independen. Regresi binomial negatif biasanya digunakan untuk memodelkan data dengan variabel respon berupa data count (Sauddin et al, 2020). Regresi binomial negatif digunakan sebagai alternatif dari model regresi poisson yang mengalami overdispersi (var>mean).…”

Section: Regresi Binomial Negatifunclassified

Permodelan Jumlah Kasus Tuberkulosis Di Kabupaten Purbalingga Tahun 2022 Menggunakan Regresi Binomial Negatif

Arum,

Manfaati Nur,

Jihan Syafiqoh

et al. 2023

jodi

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Menurut data dari Dinkes Purbalingga pada bulan Mei 2022 ditemukan 422 kasus TBC dan 9 diantaranya menderita TBC Multi Drug Resistant (MDR) atau kebal obat. Untuk kasus TBC MDR saat ini menjadi perhatian kusus pemerintah, hal ini karena masa penyembuhannya membutuhkan waktu yang lebih lama. Penyakit TB Paru merupakan salah satu penyebab kematian utama di Indonesia dan dunia. Selain menyerang Paru, Tuberculosis dapat menyerang organ tubuh yang lain. Jumlah orang terduga Tuberkulosis tahun 2022 sebanyak 11.324 dan orang terduga tuberkulosis yang mendapatkan pelayanan kesehatan sesuai standar sebanyak 12.072 (106,6%). Oleh karena itu, perlu dilakukan upaya untuk memodelkan jumlah kasus TBC di Kabupaten Purbalingga agar dapat memberikan informasi yang berguna dalam upaya pencegahan dan pengendalian penyakit TBC.Model regresi Poisson sering ditemukan pelanggaran asumsi overdispersi dengan memodelkan faktor-faktor yang berpengaruh terhadap kasus tuberculosis. Alternatif model yang dapat dilakukan untuk mengatasi pelanggaran asumsi overdispersi adalah Model Regresi Binomial Negatif. Berdasarkan nilai AIC diperoleh hasil pemodelan terbaik menggunakan regresi binomial negatif dengan nilai AIC sebesar 191.96 yang lebih kecil dari metode regresi Poisson.Berdasarkan uji parsial dihasilkan bahwa variabel yang berpengaruh terhadap jumlah kasus tuberculosis di Kabupaten Purbalingga adalah X2 yaitu jumlah puskesmas.

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“…Hal ini berdampak pada nilai standar eror yang menjadi underestimate, sehingga kesimpulannya menjadi tidak valid. Beberapa penelitian yang terkait dengan penyelesaian masalah overdispersion diantaranya adalah model regresi generalized poisson (Mahfudhotin 2020) dan regresi binomial negatif (Sauddin et al 2020). Menurut penelitian (Prahutama et al 2017) bahwa salah satu pilihan yang terbaik adalah menggunakan regresi binomial negatif.…”

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Analisis Faktor-Faktor Yang Mempengaruhi Stunting Pada Balita Di Kota Gorontalo Menggunakan Regresi Binomial Negatif

Zubedi

Aliu

Rahim

et al. 2021

Jambura J. Probab. Stat.

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This study aims to model stunting cases in children under five in Gorontalo city in 2018. In this model, it can be seen that the significant factors that affect stunting cases in children under five in Gorontalo city in 2018. This study uses data on stunting cases in 9 (nine) districts in the city of Gorontalo and the factors that influence it. The research data were obtained from the Public Health in Gorontalo city. This study used one response variable, namely the number of cases of stunting and four predictor variables, namely number of toddlers who received exclusive breastfeeding, the percentage of low birth weight (LBW), the percentage toddlers who received complete basic immunization, and number of proper sanitation. The results obtained were the variables of number of toddlers who received exclusive breastfeeding and the percentage toddlers who received complete basic immunization which had a significant effect on stunting cases in children under five in the city of Gorontalo in 2018. This was indicated by the P-value of the variable for number of toddlers who received exclusive breastfeeding of 0.00283 and P-value of variable the percentage toddlers who get complete basic immunization is 0.06564.

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Pemodelan Jumlah Kematian Ibu di Provinsi Sulawesi Selatan Menggunakan Regresi Binomial Negatif

Cited by 3 publications

References 1 publication

Key Success Factors in Maternity Waiting Home Implementation: A Qualitative Study in Rural Indonesia

Key Success Factors in Maternity Waiting Home Implementation: A Qualitative Study in Rural Indonesia

Permodelan Jumlah Kasus Tuberkulosis Di Kabupaten Purbalingga Tahun 2022 Menggunakan Regresi Binomial Negatif

Analisis Faktor-Faktor Yang Mempengaruhi Stunting Pada Balita Di Kota Gorontalo Menggunakan Regresi Binomial Negatif

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