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All Journal Journal of Applied Data Sciences Prosiding Seminar Nasional Pengabdian Kepada Masyarakat
Dian Handayani
Universitas Negeri Jakarta
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Environmental Science Public Health Other

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On the Use of Zero-Inflated Mixed Models for Count Data: A Simulation and Empirical Evidence Anang Kurnia; Zafira Fakhriyah; Kusman Sadik; Dian Handayani
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1303

Abstract

This paper evaluates the performance of classical count regression models (Poisson, Negative Binomial, Generalized Poisson), zero-inflated models (Zero-Inflated Poisson/ZIP, Zero-Inflated Negative Binomial/ZINB, Zero-Inflated Generalized Poisson/ZIGP), and zero-inflated mixed models (ZIPMM, ZINBMM, ZIGPMM) for over-dispersed count data, particularly due to excess zeros and unobserved heterogeneity. Using simulation and empirical studies, we evaluated the performance of the models based on their predictive capability and their ability to yield valid inferences through hypothesis testing. The simulation, replicated 1000 times, involves 27 scenarios that combine various sample sizes, proportions of zero counts, and response variable distributions. Our findings indicate that ZIGPMM and ZINBMM provide the smallest root mean square error (RMSE) values. Although the Poisson model yields a relatively small RMSE, it does not adequately account for overdispersion, leading to underestimated standard errors and potentially misleading significance tests. The negative binomial model yields dispersion estimates closest to 1, indicating good performance, whereas ZIGP, ZINB, ZIGPMM, and ZINBMM perform better when zero counts are extremely high. Empirical analysis of data on under-five mortality due to pneumonia in Java Island, Indonesia, indicates that ZINB, ZINBMM, and ZIGPMM have the smallest Akaike Information Criterion (AIC), making them the most suitable models. These models show that exclusive breastfeeding and vitamin A have no significant effect on under-five child mortality due to pneumonia, while severe malnutrition has a statistically significant impact (α=0.05).
PELATIHAN PENGENALAN ALGORTIMA DAN PEMROGRAMAN VISUAL SISWA SMP DENGAN SCRATH Faroh Ladayya; Dian Handayani; Siti Rohmah Rohimah; Nilam Novita Sari; Vera Maya Santi; Erin Naudy Kemalasari; Zahra Ayu Rahmadani
Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025): PROSIDING SEMINAR NASIONAL PENGABDIAN KEPADA MASYARAKAT - SNPPM2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Abstrak Perkembangan teknologi di abad ke-21 menuntut generasi muda untuk memiliki keterampilan berpikir komputasional, pemecahan masalah, dan dasar pemrograman. Namun, di daerah pedesaan seperti Kabupaten Sukabumi, pemanfaatan teknologi dalam proses pembelajaran masih terbatas. Kegiatan pengabdian ini bertujuan untuk mengenalkan dasar-dasar algoritma dan pemrograman visual kepada siswa SMP Negeri 1 Kabupaten Sukabumi melalui media Scratch. Scratch adalah software pemrograman berbasis visual yang mudah digunakan bagi pemula, serta mampu menstimulasi kreativitas siswa dalam membuat animasi dan permainan sederhana. Kegiatan ini sejalan dengan Sustainable Development Goals (SDGs) pada poin Quality Education dengan membekali siswa keterampilan algoritma dan pemrograman dasar agar lebih siap menghadapi tantangan era digital. Metode pelaksanaan kegiatan meliputi penyampaian materi, serta praktik langsung menggunakan modul pembelajaran yang telah disusun. Hasil kegiatan menunjukkan bahwa siswa antusias mengikuti pelatihan dan mampu memahami konsep dasar algoritma melalui praktik pemrograman visual. Analisis kuesioner pendahuluan dan akhir menunjukkan adanya peningkatan motivasi, wawasan, serta keterampilan siswa dalam memahami algoritma dan pemrograman visual. Dengan demikian, pelatihan ini berkontribusi positif dalam memberikan bekal awal literasi digital dan pemrograman bagi siswa SMP, yang diharapkan dapat menjadi fondasi untuk pembelajaran teknologi lebih lanjut. Abstract The development of technology in the 21st century requires young generations to possess computational thinking, problem-solving skills, and basic programming literacy. However, in rural areas such as Sukabumi Regency, the integration of technology into the learning process remains limited. This community service activity aims to introduce the fundamentals of algorithms and visual programming to students at SMP Negeri 1 Sukabumi Regency, through the use of Scratch. Scratch is a visual-based programming software that is easy for beginners to use and encourages students’ creativity in creating simple animations and games. This activity aligns with the Sustainable Development Goals (SDGs), particularly Goal 4: Quality Education, by equipping students with basic algorithmic and programming skills to prepare them for the challenges of the digital era. The implementation method included material delivery, and hands-on practice using a specially designed learning module. The results showed that students were enthusiastic during the training and successfully understood basic algorithmic concepts through visual programming practice. Analysis of pre- and post-questionnaires indicated an increase in students’ motivation, knowledge, and skills in understanding algorithms and visual programming. Therefore, this training contributed positively by providing an initial foundation in digital literacy and programming for junior high school students, which is expected to serve as a stepping stone for more advanced technology learning in the future.
Co-Authors Anang Kurnia Erin Naudy Kemalasari Faroh Ladayya Kusman Sadik Nilam Novita Sari Siti Rohmah Rohimah Vera Maya Santi Zafira Fakhriyah Zahra Ayu Rahmadani