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All Journal Jurnal Gaussian BERDAYA: Jurnal Pendidikan dan Pengabdian Kepada Masyarakat MATHunesa: Jurnal Ilmiah Matematika
Dewi Indra Setiawan
Department Of Data Science, Institut Teknologi Sumatera, Jl. Terusan Ryacudu
Humanities Education Mathematics Public Health Social Sciences Other

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PERBANDINGAN REGRESI GENERALIZED POISSON DAN REGRESI BINOMIAL NEGATIF DALAM MENGATASI OVERDISPERSI PADA JUMLAH KASUS KUSTA TIPE MB DI PROVINSI LAMPUNG TAHUN 2024 Dewi Indra Setiawan
MATHunesa: Jurnal Ilmiah Matematika Vol. 14 No. 01 (2026)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v14n1.p464-470

Abstract

Penyakit kusta merupakan salah satu penyakit menular yang masih menjadi masalah kesehatan di Provinsi Lampung, baik dari aspek medis maupun aspek sosial. Pada tahun 2024, jumlah penderita Kusta di Provinsi Lampung mencapai 185 orang yang terdiri atas 174 orang kusta MB (Paucibasiler) dan 11 orang kusta PB. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang mempengaruhi jumlah penderita kusta MB di Provinsi Lampung dengan menggunakan regresi binomial negatif dan generalized Poisson untuk menangani overdispersi data, sebagai dasar rekomendasi pengendalian penyakit. Variabel respon yang digunakan adalah jumlah penderita kusta MB di Provinsi Lampung tahun 2024, sedangkan faktor yang dapat mempengaruhinya adalah persentase rumah Tangga yang memiliki Sanitasi Layak (X1), persentase puskesmas dengan 9 jenis tenaga kesehatan (X2), rasio puskesmas per kecamatan (X3), Persentase Rata-Rata Sanitasi Total Berbasis Masyarakat (X4), persentase sarana air minum yang diawasi/diperiksa kualitas air minumnya sesuai standar (X5), persentase penduduk miskin (X6). Hasil penelitian menunjukkan bahwa regresi generalized poisson lebih baik dalam mengatasi overdispersi dibanding regresi binomial negatif dilihat dari nilai AICnya. Pada taraf siginifikansi 10 persen, faktor yang berpengaruh signifikan pada penyakit Kusta MB adalah persentase rumah Tangga yang memiliki Sanitasi Layak (X1) dan persentase sarana air minum yang diawasi/diperiksa kualitas air minumnya sesuai standar (X5)
Workshop Pembuatan Sistem Monitoring Jaringan Sederhana Menggunakan Python bagi Siswa SMKN 4 Bandar Lampung M. Syamsuddin Wisnubroto; Yuliana Yuliana; Linda Rassiyanti; Ade Lailani; Fajri Farid; Christyan Tamaro Nadeak; Fitri Nurjanah; Indah Suciati; Rian Kurnia; Yusni Puspha Lestari; Dewi Indra Setiawan
BERDAYA: Jurnal Pendidikan dan Pengabdian Kepada Masyarakat Vol. 8 No. 2 (2026)
Publisher : LPMP Imperium

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36407/berdaya.v8i2.1810

Abstract

This community service program was conducted to strengthen vocational students' competencies in network monitoring using Python. The partner school's main challenge was that networking lessons were still centered on hardware-oriented tools such as Mikrotik and Cisco, while software-based monitoring skills had not been introduced systematically. The program took the form of a workshop at SMKN 4 Bandar Lampung on 24 September 2025 and combined short lectures, demonstrations, guided practice, and mini projects. The training module covered basic networking concepts, connectivity and server status, bandwidth and latency, Python fundamentals, and the use of requests, psutil, socket, subprocess, and pandas to build a simple network monitoring system. Evaluation was conducted descriptively using pre-tests, post-tests, and practical assessment. The results showed that the mean pre-test accuracy of 46% from 32 participants increased to 64% in the post-test completed, representing an 18 percentage-point gain. All students also completed the assigned Python-based monitoring practice successfully. The outputs included a training module, poster, short video, and press release to support sustainability and dissemination.
PEMODELAN JUMLAH KASUS KEMATIAN BAYI DAN IBU DI PROVINSI LAMPUNG MENGGUNAKAN BIVARIATE GENERALIZED POISSON REGRESSION Dewi Indra Setiawan; Purhadi Purhadi
Jurnal Gaussian Vol 14, No 2 (2025): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.14.2.433-444

Abstract

Maternal and infant mortality are closely related, as the fetus receives nutrition from the mother through the placenta. Therefore, the mother's health condition during pregnancy directly impacts fetal development. Additionally, the mother's role in caring for the infant significantly affects the child's growth and survival. One of the goals of the Lampung Provincial Health Office’s Regional Medium-Term Development Plan (RPJMD) for 2020–2024 is to reduce maternal and infant mortality. The expected health target by the end of 2024 is to lower maternal deaths to 110 cases and infant deaths to 520 cases. This study employs the Bivariate Generalized Poisson Regression (BGPR) method to identify factors influencing maternal and infant mortality in Lampung Province in 2022. BGPR is suitable for handling overdispersed count data with two correlated response variables. Based on the AICc criterion, the best model includes all prediktor variables. The results show that the percentage of deliveries assisted by health professionals (X1) significantly affects maternal mortality, while both the percentage of deliveries by health professionals (X1) and the percentage of fourth antenatal care visits (K4) (X3) significantly affect infant mortality.
Co-Authors Ade Lailani Christyan Tamaro Nadeak Fajri Farid Fitri Nurjanah Indah Suciati Linda Rassiyanti M. Syamsuddin Wisnubroto Purhadi Purhadi Rian Kurnia Yuliana Yuliana Yusni Puspha Lestari