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All Journal GUYUB: Journal of Community Engagement Journal of Computing Theories and Applications
Nana Rachmana Syambas
Institut Teknologi Bandung
Religion Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Penerapan Teknologi Content Delivery Network (CDN) untuk Mendukung Digitalisasi Sekolah di Daerah 3T Nana Rachmana Syambas; Syaiful Ahdan; Eki Ahmad Zaki Hamidi; Ratna Mayasari; Ade Nurhayati; Galih Nugraha Nurkahfi; Jupriyadi Jupriyadi; Adi Sucipto; Hasan Nur Arifin; Rohmat Tulloh
GUYUB: Journal of Community Engagement Vol 6, No 4 (2025): Desember
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/guyub.v6i4.12976

Abstract

This Community Service Program was implemented at SMKS Bumi Moro, Pulau Morotai Regency, a school located in a frontier, outermost, and underdeveloped (3T) region. The school was selected due to its limited telecommunication infrastructure, which has significantly constrained the implementation of digital learning. An initial survey revealed that the school relied on a single unstable internet access point, had only 12 active computers for approximately 180 students, and most teachers lacked experience in independently operating a Learning Management System (LMS). These conditions highlighted the urgent need for technological intervention. The program adopted a Participatory Action Research (PAR) approach consisting of four stages: (1) needs analysis through online surveys and interviews with the school principal and 20 teachers; (2) design and implementation of a local Content Delivery Network (CDN) integrated with Starlink-based internet connectivity; (3) training and mentoring on Moodle LMS utilization and the introduction of Artificial Intelligence (AI) applications in learning; and (4) evaluation of program effectiveness. The training involved 30 participants, including 20 teachers and 10 educational staff members. Evaluation using a Likert-scale questionnaire (1–5) showed that 70% of participants were very satisfied and 30% were satisfied, with average scores ranging from 4.6 to 4.9. Post-program observations indicated improved teacher capacity in managing digital classes, conducting online assessments, and utilizing stable internet access. Overall, the program successfully strengthened digital learning infrastructure and teacher competence, offering a replicable model for other schools in 3T regions in Indonesia.
Implementasi Teknologi Content Delivery Network (CDN) Sebagai Akselerasi Digitalisasi Sekolah Nana Rachmana Syambas; Syaiful Ahdan; Eki Ahmad Zaki Hamidi; Ridha Muldina Negara; Ratna Mayasari; Ade Nurhayati; Galih Nugraha Nurkahfi; Jupriyadi Jupriyadi; Adi Sucipto; Hasan Nur Arifin; Rohmat Tulloh
GUYUB: Journal of Community Engagement Vol 6, No 1 (2025): Maret
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/guyub.v6i1.9812

Abstract

Abstract. This community service program aims to accelerate the digitalization of education in Pesisir Barat Regency, Lampung Province, through the implementation of Content Delivery Network (CDN) technology using Starlink services and the Learning Management System (LMS) Moodle. The 3T areas (frontier, outermost, and underdeveloped) in this region face infrastructure challenges that hinder stable and fast internet access, which is crucial to support technology-based learning processes. This program involves the installation of network devices, such as Starlink for stable internet access, gigabit switches, and the integration of the Moodle-based e-learning system. Additionally, intensive training is provided to teachers, administrators, and students on using Moodle as a digital learning platform and managing technology-based educational content. The program's success is measured through several parameters, including internet stability and speed, the improvement of digital skills among teachers and students, and the adoption and utilization rates of LMS Moodle in the learning process. Speed test results show a significant improvement. Survey results indicate a substantial impact on teachers' digital literacy. Based on questionnaires distributed to a total of 30 training participants, 60% (18 participants) reported being very satisfied with the alignment of the training materials with their needs. Regarding the delivery of the materials, 63.33% (19 participants) were very satisfied, 26.67% (8 participants) were satisfied, 6.66% (2 participants) were neutral, and 3.33% (1 participant) were very dissatisfied. Direct observation during the implementation showed that teachers could effectively utilize Moodle LMS to manage digital classes. They were trained to create and organize teaching materials, assign tasks, and monitor student progress. This evaluation also highlights the potential for replicating and sustaining the program in other schools within similar regions. Through this evaluation approach, the program is expected to have a tangible impact on improving the quality of learning, expanding digital access, and serving as a model for implementation in other 3T areas across Indonesia.
Machine Learning Framework for SHM Alarm Log Triage under Alarm Flood and Limited Labeled Data: A Case Study on a Tropical Cable-Stayed Bridge Aris Haris Rismayana; Gatot Sukmara; Nana Rachmana Syambas; Drees Andriyanto Martono; Acep Purqon
Journal of Computing Theories and Applications Vol. 4 No. 2 (2026): JCTA 4(2) 2026
Publisher : Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jcta.17014

Abstract

Structural Health Monitoring (SHM) systems on long-span bridges routinely generate alarm volumes exceeding operators' manual review capacity, a condition known as alarm flood, so that genuine structural anomalies risk being buried among far more numerous instrumentation faults. The problem is acute in developing-country settings, where monitoring falls to small operational teams rather than dedicated staff. This study proposes an alarm-log triage framework that classifies events directly from tabular database records and static sensor metadata, requiring no raw sensor time-series, offering an alternative to the raw-signal paradigm dominating bridge SHM. The dataset comprises 63,934 alarm records logged over 2.5 years on a 641.8-m tropical cable-stayed bridge: labeling collapses as volume rises, leaving only 401 usable labeled records from the pre-flood period, a weakly-supervised task under severe label scarcity. The pipeline integrates alarm-log attributes, causally-ordered temporal window features, and as-built sensor metadata, with fold-internal resampling and recall-oriented operating-point selection. Seven classifiers were benchmarked under identical stratified 5-fold cross-validation, including TabNet alongside linear, kernel-based, tree-ensemble, and neural baselines. Gradient-boosted tree ensembles separate clearly from all other families (F1-Macro 0.7991–0.8860 outside the tree family versus 0.9354–0.9432 within it; McNemar and DeLong tests confirm the separation, p < 0.05). Differences among the tree ensembles themselves are not consistently significant, so LightGBM is reported as the selected deployment model on consistent top-tier performance (F1-Macro 0.9432, AUC-ROC 0.9885 at the default threshold) rather than as demonstrably superior. A two-part ablation shows temporal alarm-rate features supply most of the discriminative power, while explicit imbalance handling yields no measurable benefit at the observed ratio, indicating that such mechanisms should be calibrated to imbalance severity rather than applied by default. The results establish operational alarm logs as a viable, lightweight input for structural event triage and document alarm flood quantitatively in a real bridge SHMS.
Co-Authors Acep Purqon Acep Purqon Ade Nurhayati, Ade Adi Sucipto, Adi Aris Haris Rismayana Drees Andriyanto Martono Eki Ahmad Zaki Hamidi Galih Nugraha Nurkahfi Gatot Sukmara Hasan Nur Arifin Jupriyadi, Jupriyadi Ratna Mayasari Ridha Muldina Negara ROHMAT TULLOH Syaiful Ahdan Syaiful Ahdan