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All Journal TEKNIK INFORMATIKA TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal TIMES International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) BIOLINK (Jurnal Biologi Lingkungan, Industri, Kesehatan) JURNAL MEDIA INFORMATIKA BUDIDARMA JTAM (Jurnal Teori dan Aplikasi Matematika) PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Mantik Indonesian Journal of Electrical Engineering and Computer Science Pelita Masyarakat Journal of Applied Data Sciences JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Science in Information Technology Letters Journal of Applied Computer Science and Technology (JACOST) International Journal of Engineering, Science and Information Technology EXPLORER Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Prioritas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Pada Masyarakat METHABDI Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Jurnal Pengabdian Masyarakat (Jubdimas)
Hartono Hartono
Department Of Magister Program In Informatics, Postgraduate School, Universitas Medan Area
Religion Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation

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An Integrated Linguistic and Metaheuristic-Optimized Elman Neural Network Framework for Cyberbullying Detection Siti Aisyah; Arnes Sembiring; Faadhil Faadhil; Hartono Hartono; Rahmad Syah; M. Khahfi Zuhanda
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1337

Abstract

The rapid growth of social media platforms has intensified the need for accurate cyberbullying detection systems capable of understanding contextual and linguistically complex expressions. Existing machine learning and deep learning approaches often suffer from limited interpretability, insufficient contextual understanding, and suboptimal parameter optimization, reducing their effectiveness in identifying harmful online content. This study proposes a novel cyberbullying detection framework that integrates Linguistic Rule-Based Feature Extraction, an Elman Neural Network (ENN), and the Local Search-Based Improved Bat Algorithm (LSBIA). The main contribution of this research lies in the synergistic combination of interpretable linguistic knowledge, contextual sequence modeling, and metaheuristic optimization within a unified classification framework. Linguistic rules are employed to capture negation patterns, intensifiers, and adjective–noun relationships, while ENN models contextual dependencies through recurrent memory structures. LSBIA is utilized to optimize network parameters and improve convergence stability. Experiments were conducted using textual data collected from Instagram, Twitter, and Facebook and evaluated using stratified 10-fold cross-validation. The proposed method achieved an accuracy of 99.12%, precision of 94.73%, recall of 97.45%, and F1-score of 93.91%, outperforming Support Vector Machine (91.20% accuracy), Naïve Bayes (89.75%), and Decision Tree (90.10%). Ablation experiments further demonstrated the importance of each component, where removing linguistic rules reduced accuracy to 94.90%, removing sentiment scoring reduced accuracy to 96.30%, and replacing ENN with LSTM, GRU, or Transformer architectures resulted in lower accuracies of 92.50%, 91.90%, and 93.20%, respectively. These findings confirm that integrating linguistic feature engineering, contextual neural modeling, and metaheuristic optimization significantly enhances cyberbullying detection performance while maintaining interpretability. The novelty of this study resides in the integration of linguistic rule-based representation with LSBIA-optimized ENN for context-aware cyberbullying classification.
PELATIHAN PENERAPAN SISTEM PENDUKUNG KEPUTUSAN PENENTUAN JUMLAH PEMBERIAN PAKAN IKAN DI DESA MARIENDAL II Muhammad Khahfi Zuhanda; Hartono Hartono; Sayuti Rahman; Arnes Sembiring; Rahmad Syah; Dadan Ramdan; Mendarissan Aritonang; Citra Rahmadhani; Suswati Suswati; Habib Satria; Erianto Ongko
JUBDIMAS ( Jurnal Pengabdian Masyarakat) Vol 5 No 1 (2026): Artikel Pengabdian Maret 2026
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jubdimas.v5i1.403

Abstract

This community service activity aims to improve the efficiency of fish feeding management through the implementation of a Decision Support System (DSS) using the Simple Additive Weighting (SAW) method in Mariendal II Village. The main problem faced by fish farmers is the manual feeding process based on estimation, leading to inefficiency and suboptimal fish growth. The method used in this activity is a participatory approach consisting of socialization, training, technology implementation, and evaluation. The developed system considers several criteria, including fish biomass, age, population, water quality, feeding time, and feed type. The results show that participants experienced significant improvements in knowledge and skills in using the DSS. The system successfully provided optimal feeding recommendations and was integrated with an automatic feeder, resulting in more consistent and efficient feeding practices. This activity also increased farmers’ awareness of technology adoption in aquaculture. Overall, the implementation of DSS contributes to reducing feed waste, improving productivity, and supporting sustainable fish farming practices.
Metaheuristic nurse scheduling with hospital clustering using flower pollination algorithm Muhammad Khahfi Zuhanda; Hartono Hartono; Sayuti Rahman; Prana Ugiana Gio; Erianto Ongko
Bulletin of Electrical Engineering and Informatics Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i3.11243

Abstract

Effective nurse scheduling is essential to ensure balanced workloads, reduce fatigue, and maintain healthcare service quality. However, the nurse scheduling problem (NSP) is complex due to constraints related to nurse skills, task requirements, and legal working-hour limits. This study proposes an integrated framework combining a mathematical optimization model with metaheuristic algorithms to generate optimal daily nurse activity schedules. Genetic algorithm (GA) and simulated annealing (SA) are employed to produce near-optimal solutions for nurse populations ranging from 3 to 50 individuals, considering skill-level compatibility, workload balance, and maximum working hours. Experimental results using real scheduling data from 30 nurses across three skill levels demonstrate that all generated schedules satisfy the imposed constraints, with no nurse exceeding the 12hour daily working limit. Comparative analysis shows that GA achieves lower scheduling costs for larger nurse populations, while SA consistently requires significantly shorter computation times, making it suitable for time-sensitive applications. In addition, the flower pollination algorithm (FPA) is used to cluster 3,155 hospitals based on bed capacity, service variety, and workforce size, supporting data-driven workforce distribution analysis. The proposed framework integrates operational scheduling optimization with hospital-level clustering, providing practical decision support for healthcare workforce planning.
Kelas Tenda Bencana (Kedana): Penerapan Model Pembelajaran Aktif Bagi Siswa Yang Terdampak Banjir bagi Sekolah-sekolah Di Kabupaten Deli Serdang Dan Kabupaten Langkat Dedi Sahputra; Nadra Ideyani Vita; Ria Wuri Andary; Mulkan Andika Situmorang; Hartono Hartono; Habib Satria; Zulkarnain Lubis; Retna Astuti Kuswardani
Pelita Masyarakat Vol. 7 No. 2 (2026): Pelita Masyarakat Maret
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/pelitamasyarakat.v7i2.17222

Abstract

The implementation of Community Service for Disaster Emergency Response (DPPM 2025) is themed "Disaster Tent Class (KENDANA)". This activity is a quick response to the impact of floods and landslides that disrupt the learning process in the Deli Serdang Regency and Langkat Regency areas. The implementation refers to the administrative and technical guidelines of the DPPM. The scope of activities includes: (1) coordination and mapping of needs with partners (schools and local governments), (2) survey of the condition of affected educational facilities, (3) implementation of emergency learning through "tent classes" and training for educators in Deli Serdang and Langkat, (4) monitoring, documentation, and handover of outputs (5) grants of emergency learning tents, study supplies and school uniforms to students (6) grants of complete drilled well packages (7) basic food assistance to the people of Sekoci Village, Besitang District, Langkat Regency. The educational materials applied are based on active and adaptive learning (ice breaking, educational games, strengthening literacy and basic numeracy) and are outlined in emergency learning modules. The activities were carried out at five schools across three districts in Deli Serdang and at one school in Sekoci Village, Besitang District, Langkat. A total of 187 students affected by the floods participated in the activities. The administrative and technical outputs submitted include emergency learning modules, participant attendance lists per location, photo and video documentation, and implementation reports per location. In substance, this program has succeeded in facilitating the return of structured learning activities at the primary and secondary levels at several locations and increasing the capacity of teachers in managing post-disaster learning.
Co-Authors Aditya Pratama, Bayu Ammar Yasir Nasution Andi Rahmadsyah Andik Bintoro Andre Hasudungan Lubis Andriasan Sudarso Arnes Sembiring Asmah Indrawati B. Herawan Hayadi B. Herawan Hayadi Brilliant Handyman Manalu Citra Rahmadhani Cut Ita Erliana Dadan Ramdan Dahlan Abdullah Dedi Sahputra Desniarti Dian Maya Sari Elvie Maria Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erianto Ongko Erna Budhiarti Nababan Faadhil, Faadhil Finta Aramita Firman Syahputra Firman Syahputra Gio, Prana Ugiana Habib Satria Imelda Maelani Iqbal Giffari Ritonga Irwan Daniel Jaka Kusuma Jaka Kusuma Khairul Fadhli Margolang Limas, Agus Fahmi Maricha Elveny Marischa Elveny, Marischa Martini, Dewi Meli Handayani Mendarissan Aritonang Muhammad Ikhwani Muhammad Khahfi Zuhanda Muhammad Sadikin Muhammad Zarlis Muhammad Zulkarnain Lubis Mulkan Andika Situmorang N. Nazaruddin Nadapdap, Kristanty M. N. Nadra Ideyani Vita Nasution, Mahyuddin K.M Nos Sutrisno Nur Anzelina Nur Azelina Harahap Nursie, Aly Nurwijayanti Opim Salim Sitompul Prana Ugi Rachmat Aulia, Rachmat Rahmad B.Y Syah Rahmad Syah, Rahmad Rahman, Sayuti Rana Fathinah Ananda Retna Astuti Kuswardani Rezzy Eko Caraka Ria Wuri Andary Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly Rika Rosnelly, Rika Rohima Rohima Rubianto Sabina Krisdayanti Samsul A Rahman Sidik Hasibuan Sembiring, Arnes Silvia Lestari Silvia Lestari Siti Aisyah Sitorus, Peniel Sam Putra Sugeng Riyadi Suswati Suswati suswati suswati Syah, Rahmad B.Y Tulus Tulus Wanayumini Wulan Dari Yeni Risyani Yudi Gebri Foenna Zakarias Situmorang