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All Journal Jurnal Kajian Ilmiah Jurnal ABDIMAS (Pengabdian kepada Masyarakat) UBJ
Agus Hidayat
Fakultas Ilmu Komputer; Universitas Bhayangkara Jakarta Raya
Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Penguatan Infrastruktur Digital Desa Melalui Penerapan Jaringan RT/RW-Net Di Desa Neglasari, Sumedang Carudin Carudin; Joni Warta; Asep Ramdhani Mahbub; Agus Hidayat
Jurnal Pengabdian kepada Masyarakat UBJ Vol. 9 No. 2 (2026): Juni - Desember 2026
Publisher : Lembaga Penelitian Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/k94nzx09

Abstract

Neglasari Village, Darmaraja District, Sumedang Regency, needs a more structured local network to support village administration, information delivery, public access, coordination activities, and local economic services. This community service activity aimed to strengthen village digital infrastructure through the implementation of an RT/RW-Net network. The activity was carried out using a participatory approach through observation, needs mapping, network topology design, device installation and configuration, user training, and initial evaluation. The network architecture was designed by connecting the internet source, modem/ONT, router gateway, distribution device, access points, and users at priority service areas. Training was also provided to village officers and users to improve their understanding of network utilization, access ethics, password security, and basic troubleshooting. The initial results show that the RT/RW-Net network provided a more structured connectivity foundation for village digital services. In addition, participants gained basic knowledge of network use and maintenance, enabling the village to manage simple connectivity issues more independently. This program supports the gradual and sustainable development of digital village services in Neglasari Village.
Deteksi Stunting Menggunakan Dual-Vae, Gan, Dan Transformer Pada Data Antropometri Wowon Priatna; Joni Warta; Agus Hidayat; Adam Arif Budiman
Jurnal Kajian Ilmiah Vol. 26 No. 3 (2026): September 2026
Publisher : Lembaga Penelitian, Pengabdian Kepada Masyarakat dan Publikasi (LPPMP)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/g4x45463

Abstract

Stunting detection based on anthropometric data requires a classification model capable of capturing complex relationships among child growth characteristics. This study developed a stunting detection model integrating Dual Variational Autoencoder (Dual-VAE), Generative Adversarial Network (GAN), and Transformer using age, sex, weight, and height as predictors. The dataset consisted of 40,071 records of children aged 0–59 months from Jeneponto Regency, Indonesia. Two class-oriented VAE branches were used to learn complementary latent representations of stunted and non-stunted children. GAN-based enrichment was applied to the stunted latent representation, while the Transformer modeled interactions among the resulting latent features. Model performance was evaluated using stratified five-fold cross-validation. The proposed model achieved an accuracy of 0.9960 ± 0.0007, F1-score of 0.9950 ± 0.0008, G-Mean of 0.9957 ± 0.0007, MCC of 0.9917 ± 0.0014, AUROC of 0.9999 ± 0.0001, and AUPRC of 0.9998 ± 0.0001. The results showed that combining class-oriented latent representations, controlled generative enrichment, and feature-interaction modeling produced high and consistent classification performance for anthropometric-based stunting detection.
Co-Authors Adam Arif Budiman Asep Ramdhani Mahbub Carudin Carudin Joni Warta Priatna , Wowon