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Studi Pembeban Transformator Distribusi Pada PT. PLN (Persero) Rayon Sungguminahasa Wildan Wildan; Rahmat Rahmat; Hendy Prasetyo; Sulfikar Sulfikar
EEICT (Electric, Electronic, Instrumentation, Control, Telecommunication) Vol 9, No 1 (2026)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/eeict.v9i1.23092

Jenis Penelitian ini merupakan jenis penelitian deskriptif kuantitatif yaitu memberikan gambaran dan menganalisis tentang pembebanan transformator distribusi pada PT. PLN (Persero) Rayon Sungguminasa. Pada kondisi ideal, transformator tiga fasa memiliki besaran yang sama pada setiap fasanya; perbedaannya hanya terletak pada sudut fasa yang seharusnya berjarak 120°. Namun, dalam praktiknya kondisi ideal ini sulit tercapai karena masing-masing fasa pada sisi sekunder umumnya menyalurkan daya ke beban yang berbeda-beda. Akibatnya, terjadi ketidakseimbangan beban pada setiap fasa. Hasil analisa data yang diperoleh menunjukkan bahwa pembebanan pada transformator distribusi di wilayah kerja PT. PLN (Persero) Rayon Sungguminasa masih menunjukkan adanya beberapa transformator distribusi yang melebih batas maksimum 80%, dan untuk hasil analisa data ketidakseimbangan beban juga menunjukkan adanya beberapa transformator distribusi yang melebihi batas maksimum 25%.

Comparative Analysis of Structural-Based Reduction and Brute Force Algorithms for Determining Metric Dimensions in Tree Graphs Afifah Farhanah Akadji; Abdul Gani F. S. H. Lihawa; Maharani Eka; Karina A. Sasmito; Hendy Prasetyo; Andi Sitti Dwi Auliyani
Journal of Digital Technology and Computer Science Vol. 3 No. 2 (2026): April 2026
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/dtcs.v3i2.696

Purpose – This study aims to overcome the computational inefficiency of the Brute Force method in determining the metric dimension of tree graphs by evaluating the performance of a Structural-Based Reduction Algorithm. The study addresses the high computational cost of exhaustive search approaches and proposes a more efficient structural alternative. Methods – This research applies a comparative computational experimental approach by implementing both the Brute Force method and the proposed reduction algorithm on non-isomorphic tree graphs obtained from the McKay dataset. The algorithm is based on Slater’s theorem regarding leaves and stem vertices in tree graphs. Instead of testing all possible vertex combinations, the algorithm utilizes structural relationships to determine the metric dimension more efficiently. The comparison focuses on result consistency and computational execution time. Findings – Experimental results show that the proposed reduction algorithm achieves 100% accuracy, producing metric dimension values identical to those generated by the Brute Force method for all tested graphs. In terms of efficiency, the proposed method performs significantly better. For a tree graph with 20 vertices, the Brute Force method requires approximately 79 seconds, while the reduction algorithm completes the computation in only 0.005 seconds. Research implications – The findings indicate that structural analysis can reduce computational complexity in determining metric dimensions of tree graphs. However, the current approach is limited to acyclic graph structures and may require modification for cyclic graphs. Originality – This study introduces a deterministic and scalable alternative for determining metric dimensions in tree graphs through structural reduction principles.

Perancangan Aplikasi Layanan Desa Cerdas Berbasis AI Terintegrasi WhatsApp untuk Klasifikasi Laporan Warga di Desa Hutadaa Abdul Gani Fadhlulrahman S. H. lihawa; Hendy Prasetyo; Syahrir Abdussamad; Rahmad Hidayat Dongka; Wildan Wildan; Ade Irawaty Tolago; Yasin Mohamad; Ulfatun Nadifa; Rahmatia Alam
Empiris Jurnal Pengabdian Pada Masyarakat Vol. 4 No. 1 (2026): April 2026
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59713/kdytt710

The community reporting system in Hutadaa Village, West Limboto District, remains dependent on manual mechanisms, leading to delayed responses, unstructured documentation, and difficulty for village officials in prioritizing issues. This community service activity aims to design a prototype of an AI-based smart village service application integrated with the WhatsApp platform, enabling automated classification of community reports and assessment of urgency levels. The design was carried out through four stages: field interview-based needs identification, system architecture design, workflow simulation, and limited testing with village officials. The system was designed by integrating WhatsApp Business API, an AI-based image processing module, and a report management interface for village officials. Simulations demonstrated that the system can classify reports into categories (infrastructure, sanitation, social, emergency) and assign urgency levels (low, medium, high) based on analysis of photo and text content, achieving a category classification accuracy of 82.5% and urgency assessment accuracy of 77.5% under good image quality conditions. Interface testing by village officials yielded positive responses regarding ease of use and feature relevance. The designed system has the potential to improve the efficiency of public services at the village level. Full implementation and long-term impact evaluation are required in subsequent service activities. Sistem pelaporan masyarakat di Desa Hutadaa, Kecamatan Limboto Barat, masih bergantung pada mekanisme manual yang menyebabkan keterlambatan penanganan, dokumen laporan yang tidak terstruktur, dan kesulitan bagi aparat desa dalam menetapkan prioritas penanganan. Kegiatan pengabdian ini bertujuan merancang prototipe aplikasi layanan desa cerdas berbasis kecerdasan buatan (AI) yang terintegrasi dengan platform WhatsApp, yang memungkinkan klasifikasi otomatis laporan warga beserta penilaian tingkat urgensinya. Perancangan dilaksanakan melalui empat tahap: identifikasi kebutuhan berbasis wawancara lapangan, desain arsitektur sistem, simulasi alur kerja, dan uji coba terbatas bersama perangkat desa. Sistem dirancang dengan mengintegrasikan WhatsApp Business API, modul pemrosesan gambar berbasis AI, dan antarmuka manajemen laporan untuk aparat desa. Simulasi menunjukkan bahwa sistem mampu mengklasifikasikan laporan ke dalam kategori (infrastruktur, kebersihan, sosial, darurat) dan menetapkan tingkat urgensi (rendah, sedang, tinggi) berdasarkan analisis konten foto dan teks, dengan akurasi klasifikasi kategori sebesar 82,5% dan akurasi penilaian urgensi sebesar 77,5% pada kondisi gambar berkualitas baik. Pengujian antarmuka oleh perangkat desa menghasilkan respons positif terhadap kemudahan penggunaan dan relevansi fitur. Sistem yang dirancang berpotensi meningkatkan efisiensi layanan publik di tingkat desa. Diperlukan implementasi penuh dan evaluasi dampak jangka panjang pada tahap pengabdian berikutnya.

Comparing K-Means and Fuzzy C-Means for Student Academic Risk Mapping and Early Warning in a Basic Mathematics Course Hendy Prasetyo; Wildan; Afifah Farhanah Akadji; Andi Sitti Dwi Auliyani; Rahmad Hidayat Dongka
Jurnal MEKOM (Media Komunikasi Pendidikan Kejuruan) Volume 13, Issue 1, February 2026
Publisher : Fakultas Teknik, Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/mekom.v13i1.261

Purpose – This study compares the K-Means and Fuzzy C-Means (FCM) algorithms for mapping student academic risk using in-course academic performance data. Methods – The dataset consisted of 35 students and included assignment scores, quiz scores, midterm examination scores, attendance, learning participation, employment status, and language variables. The data were preprocessed through cleaning, identity anonymization, and min-max normalization to ensure that all attributes were measured on a comparable scale. The experiments were conducted under two clustering scenarios, namely K=2 and K=3. Findings – In the K=2 scenario, both methods produced the same separation between low-risk and high-risk student groups. After the clustering results were mapped to the actual Pass/Fail labels using a majority-vote approach, 27 students who passed and 7 students who failed were correctly identified, with no false positives and 1 false negative. These results yielded 97.14% accuracy, 100% precision, 96.43% recall, and a 98.18% F1-score. In the K=3 scenario, K-Means formed three distinct groups containing 27, 4, and 4 students, whereas FCM produced a more gradual distribution of 13, 14, and 8 students. Research implications – These findings indicate that K-Means is suitable as a fast baseline for binary risk screening, whereas FCM is more informative for gradual risk interpretation in academic early warning systems. Originality – This study contributes by showing the different practical value of hard and soft clustering for identifying clearly at-risk and borderline students using routinely available in-course academic indicators.

Sosialisasi Cyber Security Awareness: Mitigasi Phishing dan Pengamanan Akun Digital bagi Siswa SMA/SMK Hendy Prasetyo; Kameliani Kameliani; Wildan Wildan; Andi Rasya; Argiyo Prasetyo Tutu
Empiris Jurnal Pengabdian Pada Masyarakat Vol. 4 No. 1 (2026): April 2026
Publisher : Fakultas Ilmu Sosial dan Ilmu Politik Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59713/fh9by653

The widespread internet access in Indonesia has positioned senior high school and vocational students as the most active digital users while simultaneously making them the most vulnerable group to phishing attacks and digital account hijacking. The gap between technical proficiency and digital security awareness among adolescents has become an urgent issue requiring structured intervention. This community service activity aimed to enhance the cyber security awareness of students at SMAN 1 Limboto, Gorontalo Regency, through socialization focusing on three main aspects: phishing identification and mitigation, digital account security through Two-Factor Authentication (2FA), and data privacy principles in daily online activities. The activity employed an interactive lecture method based on real-life case studies relevant to adolescents' digital lives, complemented by live demonstrations and question-and-answer sessions. Evaluation through an interactive quiz revealed an average increase of 58 percentage points across all comprehension indicators, from 33% before to 91% after the socialization, with the highest increase recorded on the 2FA knowledge indicator at 63 percentage points. This activity demonstrates that a context-based socialization approach grounded in adolescents' real digital experiences is more effective in building cyber security awareness than generic technical approaches, while contributing to shaping a generation that is not only digitally proficient but also digitally safe.

Studi Pembeban Transformator Distribusi Pada PT. PLN (Persero) Rayon Sungguminahasa Wildan Wildan; Rahmat Rahmat; Hendy Prasetyo; Sulfikar Sulfikar
EEICT (Electric, Electronic, Instrumentation, Control, Telecommunication) Vol 9 No 1 (2026)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/eeict.v9i1.23092

Jenis Penelitian ini merupakan jenis penelitian deskriptif kuantitatif yaitu memberikan gambaran dan menganalisis tentang pembebanan transformator distribusi pada PT. PLN (Persero) Rayon Sungguminasa. Pada kondisi ideal, transformator tiga fasa memiliki besaran yang sama pada setiap fasanya; perbedaannya hanya terletak pada sudut fasa yang seharusnya berjarak 120°. Namun, dalam praktiknya kondisi ideal ini sulit tercapai karena masing-masing fasa pada sisi sekunder umumnya menyalurkan daya ke beban yang berbeda-beda. Akibatnya, terjadi ketidakseimbangan beban pada setiap fasa. Hasil analisa data yang diperoleh menunjukkan bahwa pembebanan pada transformator distribusi di wilayah kerja PT. PLN (Persero) Rayon Sungguminasa masih menunjukkan adanya beberapa transformator distribusi yang melebih batas maksimum 80%, dan untuk hasil analisa data ketidakseimbangan beban juga menunjukkan adanya beberapa transformator distribusi yang melebihi batas maksimum 25%.

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