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All Journal Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JIKO (Jurnal Informatika dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vocatech : Vocational Education and Technology Journal TECHSI - Jurnal Teknik Informatika Lok Seva: Journal of Contemporary Community Service Journal Of Artificial Intelligence And Software Engineering Jurnal Pengabdian Sosial Journal of Deep Learning, Computer Vision and Digital Image Processing Journal of Advanced Computer Knowledge and Algorithms Seuraya Jurnal Pengabdian Kepada Masyarakat Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Jurnal Pengabdian Masyarakat Teknologi Informasi (PERANTI)
Hamdhana, Defry
Universitas Malikussaleh
Religion Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Pemberdayaan Masyarakat Tani Melalui Produksi Briket Jerami sebagai Energi Alternatif Ramah Lingkungan dan Sumber Pendapatan Baru di Gampong Reulet Timu Nailufar, Fanny; Sari, Cut Putri Mellita; Fadhilah, Fadhilah; Hamdhana, Defry; Arliansyah, Arliansyah; Yusra, Muhammad
Jurnal Pengabdian Sosial Vol. 2 No. 7 (2025): Mei
Publisher : PT. Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/6h6y9442

Abstract

Pengabdian kepada masyarakat ini dilakukan di Gampong Reulet Timu dengan tujuan memberdayakan masyarakat tani melalui pemanfaatan limbah jerami menjadi briket sebagai energi alternatif ramah lingkungan dan sumber pendapatan baru. Limbah jerami yang selama ini dibakar atau dibiarkan tanpa pengelolaan diolah menjadi briket yang memiliki nilai ekonomis dan fungsi praktis sebagai bahan bakar. Kegiatan dilaksanakan melalui tiga tahap utama, yaitu sosialisasi, pelatihan teknis, dan pendampingan produksi. Hasil kegiatan menunjukkan adanya peningkatan pemahaman dan keterampilan masyarakat dalam memproduksi briket jerami. Satu kelompok tani telah terbentuk dan mulai menjalankan produksi mandiri. Produk yang dihasilkan dinilai layak untuk digunakan sebagai bahan bakar rumah tangga serta berpotensi dikembangkan ke pasar lokal. Kegiatan ini tidak hanya mengurangi limbah pertanian tetapi juga membuka peluang ekonomi baru. Program ini diharapkan dapat menjadi model inovasi energi lokal berkelanjutan di wilayah pedesaan.
Few-Shot Learning for Classifying Genuine and Bot Comments on YouTube Using Transformer Models Fikriah Nst, Nahdah; Hamdhana, Defry; Qamal, Mukti
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.10023

Abstract

This study aims to develop a comment classification system on the YouTube platform to distinguish between real accounts and bot accounts, addressing the challenge of limited labeled data through a few-shot learning approach. The issue of bot accounts masquerading as real users in comment sections is becoming increasingly prevalent and has the potential to spread spam, misinformation, and influence public opinion. In this study, a Transformer-based model, DistilBERT, is used, which is known for its efficiency in understanding natural language context. The model is trained in a few-shot scenario (N5 to N50) using a very limited amount of training data. Testing results show that the model maintains high and stable performance even with minimal data (N5), achieving an F1-score above 0.90. In addition, this system is implemented into a web application using Flask to enable direct and interactive comment detection. The main contribution of this research is the proof that the combination of few-shot learning and the DistilBERT model can provide a practical and efficient solution for classifying YouTube bot account comments even with limited data conditions, as well as providing a replicable approach for similar problems on other digital platforms.
Implementation of Ant Colony Optimization (ACO) Algorithm for Route Optimization of Tourist Paths in Takengon Suryana, Fitra; Nurdin, Nurdin; Hamdhana, Defry
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9706

Abstract

This study aims to design and implement a system for determining the shortest route between tourist destinations in Takengon using the Ant Colony Optimization (ACO) algorithm. The system is developed to assist travelers in obtaining efficient visitation routes based on distance and travel time. Experiments were conducted on 20 tourist locations, resulting in an optimized route with a total travel distance of 40.40 km and an estimated travel time of 81 minutes. The computation process took only 0.024001 seconds with a memory usage of 20.23 KB. The ACO algorithm was executed using 10 ants with key parameters set to alpha (α) = 1, beta (β) = 2, and rho (ρ) = 0.5. ACO demonstrated high effectiveness in exploring route combinations and iteratively generating near-optimal solutions. The chosen parameters were determined through experimentation to balance solution quality and convergence speed. In addition to generating the optimal visitation sequence, the system also provides complete turn-by-turn navigation instructions, including major roads such as Jalan Lintas Tengah Sumatera and Jalan Lebe Kader. The actual estimated travel route based on the generated navigation covers a distance of 97.4 km with a travel duration of approximately 2 hours and 42 minutes. The results indicate that ACO is an effective and efficient approach for solving medium- to large-scale tourist route optimization problems. The developed system can serve as a practical tool in the tourism sector and has the potential to be adapted and implemented in other tourist regions with similar routing challenges.
Peningkatan Kompetensi Guru SLB dalam Pemanfaatan Teknologi Pembelajaran Digital di SLB YPAC Dewantara Aceh Utara Hamdhana, Defry; Yusra, Muhammad; Maghfirah, Fitri; Mulyati, Sri; Kembaren, Emmia Tambarta
Lok Seva: Journal of Contemporary Community Service Vol 4, No 2 (2025)
Publisher : Universitas Teuku Umar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35308/lokseva.v4i2.13515

Abstract

At SLB YPAC Dewantara, North Aceh, teachers' mastery of digital technology remains constrained in terms of the utilization of online applications and multimedia. The objective of this Community Service Program (PKM) is to enhance pedagogues' competencies through experiential learning, which is characterized by a participatory approach. The activity was conducted over the course of two days and involved 15 teachers. The materials covered the use of Zoom Meeting, Google Meet, Bitly, and the creation of simple animations using Canva and Powtoon. The evaluation results demonstrated a substantial increase in the utilization of digital tools, with the capacity to employ the fundamental functionalities of Zoom and Google Meet escalating from 27% to 87%, the application of Bitly rising from 13% to 80%, and the proficiency in generating animated media increasing from 7% to 73%. The challenges encountered by the participants included time constraints, variations in digital literacy, and internet infrastructure. This PKM fostered the establishment of an internal teacher learning community and underscored the significance of synergy among individual capacity, institutional support, and sustainable mentoring.
Classification Analysis of Single Tuition Fees Using the Random Forest Method with K-Fold Cross Validation Khaidar, Al; Nurdin, Nurdin; Fajriana, Fajriana; Taufiq, Taufiq; Hamdhana, Defry
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11798

Abstract

Classification is the process of grouping data into specific categories based on their characteristics or features, which plays a crucial role in the analysis, decision-making, and prediction of new data. In academic settings, classification is used to determine the Single Tuition Fee to place students according to their economic ability. Lhokseumawe State Polytechnic has implemented the UKT system since 2020 with eight categories, but some students are still placed in UKT groups that do not match the results of the manual process, which has limited accuracy. This study uses the Random Forest method as a technology-based solution to improve the accuracy and objectivity of UKT classification. The dataset used consists of 10,000 student data with 10 variables, covering economic and social information. The research process includes data preprocessing, Random Forest model training, performance evaluation using accuracy, precision, recall, and F1-score, and model stability testing through 10-fold K-Fold Cross Validation. The results show that Random Forest is able to classify most UKT classes well, especially classes 0–5 and 7. Class 6 has lower performance with a recall of 0.39 and an F1-score of 0.56 due to the limited number of samples. The overall accuracy of the model reaches 96%, while K-Fold Cross Validation produces an average accuracy of 95.50% with a standard deviation of 0.66%, indicating the model is stable and able to generalize to new data. This study proves that Random Forest is effective in UKT classification, producing an objective, fair, and efficient system. This implementation model supports data-driven decision-making in higher education and increases transparency in UKT determination.
Analysis of Winnowing Algorithms in The Title Selection System of Job Training Report, Faculty of Engineering, Universitas Malikussaleh Rizal; Defry Hamdhana
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 1 (2018): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

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

Abstract

The number of practical work reports that have been published by department makes a coordinator of on the job training have difficulty in determining the feasibility of the title of the on the job training report quickly. This happened because each report that was made must be unique in terms of the methods and objects that are examined in a particular institution/company. So that reports that have been published previously did not experience plagiarism. Winnowing algorithm is an algorithm used to detect the similarity of words/sentences in two or more texts that are compared. If there are two texts that are the same, a fingerprint will be formed. So that the practical work coordinator can determine the feasibility of the title of on the job training report quickly and the creation of an online-based on the job training report information system that can be accessed at any time.
Student Academic Consultation Chatbot Using Meta AI Large Language Models and Retrieval-Augmented Generation Pangestu, Aridho; Hamdhana, Defry; Suwanda, Rizki
Journal of Artificial Intelligence and Software Engineering Vol 6, No 1 (2026): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v6i1.8875

Abstract

Academic consultation is an important service for students in obtaining information related to academic regulations, procedures, and requirements. However, the consultation process, which is still carried out manually, often causes delays in the delivery of information and limited access, especially when students need answers quickly. Therefore, a system is needed that is capable of providing academic consultation services automatically and based on official documents. This study aims to design and build a student academic consultation chatbot using Large Language Model (LLM) technology and Retrieval Augmented Generation (RAG) architecture. The methods used include calling up Academic Guidelines documents, splitting text into several parts (text splitting), creating embeddings using the HuggingFace all-MiniLM-L12-v2 model, and storing embeddings in a vector database. Next, the system performs a relevant document search process using a retriever and utilizes the LLaMA 3.1-8B-Instant model to generate answers based on the context found. The chatbot's performance was evaluated using ROUGE metrics, including ROUGE-1, ROUGE-2, and ROUGE-L, with measurements of precision, recall, and F1-score. The evaluation results showed that the chatbot was able to provide relevant answers in accordance with academic documents. The average evaluation scores obtained were precision of 47,57%, recall of 67,85%, and F1-score of 53,36%. The higher recall score indicates that the system is quite good at covering reference information, although the accuracy of word selection can still be improved.
Traffic Accident Prediction Using Machine Learning Based on PT Jasa Raharja Data Utomo, Muhammad Fikri; Fikry, Muhammad; Hamdhana, Defry; Abdullah, Dahlan; Nurdin, Nurdin
Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer Vol 21, No 1 (2026): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jim.v21i1.25392

Abstract

Traffic accidents represent a critical issue that significantly affects public safety and generates substantial social and economic impacts, particularly within the operational area of PT. Jasa Raharja Lhokseumawe Branch. The lack of predictive information regarding accident occurrences often results in reactive policy making. This study aims to develop a machine learning–based forecasting model for traffic accident rates using a combination of K-Means Clustering and Recurrent Neural Network (RNN). The dataset consists of historical traffic accident records from 2022 to 2024, which were preprocessed and aggregated on a weekly basis at the district level. K-Means Clustering was employed to group districts according to weekly accident patterns, resulting in two optimal clusters based on silhouette score evaluation. Subsequently, separate RNN models were developed for each cluster to forecast weekly accident occurrences. Model performance was evaluated using Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). The results indicate that the RNN model achieved higher prediction accuracy for clusters with more stable accident patterns compared to clusters exhibiting higher fluctuation. Overall, the proposed combination of clustering and RNN demonstrates strong potential in producing accurate traffic accident forecasts
PKM PENGAJIAN KITAB SABILAL MUHTADIN MEMANFAATKAN TEKNOLOGI KOMPUTER Maizuar Maizuar; Taufiq Taufiq; Ar Razi; Defry Hamdhana; Hamzani Hamzani
Jurnal Pengabdian Masyarakat Teknologi Informasi (PERANTI) Vol 2 No 1 (2026): Jurnal Pengabdian Masyarakat Teknologi Informasi
Publisher : LPPM Unimal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.0330/peranti.v2i1.27455

Abstract

Peningkatan penerapan teknologi dan ditemukannya dengan minat masyarakat terhadap ilmu agama, telah memunculkan ide-ide baru terutama dalam membantu masyarakat meningkatkan penguasaannya akan ilmu yang bersumber dari kitab Sabilal Muhtadin dalam waktu yang singkat. Salah satu pendekatan alternatif tersebut adalah pemanfaatan teknologi yang tepat untuk membantu masyarakat agar mahir dan lancar dalam mentahqiq kitab Sabilal Muhtadin. Berdasarkan analisis situasi, untuk mewujudkan pemahaman ilmu fikih melalui kitab Sabilal Muhtadin dengan menggunakan alat bantu komputer, maka Tim pengabdian membangun dan memperkenalkan penggunaan alat bantu pemahaman kitab Sabilal Muhtadin berbasis komputer. Setelah dilakukan evaluasi terhadap para peserta, diperoleh adanya peningkatan minat dan percepatan masyarakat peserta dalam syarh kitab Sabilal Muhtadin. Hasil evaluasi menunjukkan bahwa 87,5% dari total peserta berhasil menyelesaikan syarh dan dianggap layak dan sisanya setelah pengujian tahap kedua. Kata kunci : Sabilal Muhtadin, Sistem
PENDATAAN KELUARGA KORBAN BANJIR BANDANG UNTUK MENDUKUNG PENYALURAN BANTUAN DI DESA MEUNASAH BARO Muhammad Yusra; Fitri Maghfirah; Sri Mulyati; Defry Hamdhana; Nur Afni Yunita
SEURAYA Jurnal Pengabdian Kepada Masyarakat Vol 4 No 1 (2026): SEURAYA: Jurnal Pengabdian kepada Masyarakat
Publisher : Fakultas Ekonomi dan Bisnis Islam Institut Agama Islam Negeri Langsa

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

Abstract

Banjir bandang merupakan bencana hidrometeorologi yang berdampak signifikan terhadap kehidupan sosial dan ekonomi masyarakat. Permasalahan utama yang sering muncul pascabencana adalah ketidaktepatan penyaluran bantuan akibat keterbatasan data korban yang akurat dan terverifikasi. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk melakukan pendataan keluarga korban banjir bandang di Desa Meunasah Baro sebagai dasar pendukung penyaluran bantuan yang tepat sasaran. Metode yang digunakan meliputi survei lapangan secara langsung, wawancara dengan kepala keluarga, observasi kondisi rumah, serta penyusunan basis data sederhana berbasis kebutuhan korban. Hasil kegiatan menunjukkan tersusunnya data keluarga terdampak yang memuat tingkat kerusakan dan kebutuhan prioritas, sehingga membantu pemerintah desa dan pemangku kepentingan dalam menyalurkan bantuan secara lebih efektif dan adil.
Co-Authors Ar Razi Ar Razi Arliansyah, Arliansyah Baharuddin Ismail Dahlan Abdullah Fadhilah Fadhilah Fadlisyah Fadlisyah Fajriana, Fajriana Fanny Nailufar Fikriah Nst, Nahdah Fitri Maghfirah Hamzani Hamzani indra firmansyah Juanda Pratama Kembaren, Emmia Tambarta Khaidar, Al Lailatul Husna Maizuar Maizuar Mardiaton, Mardiaton Martin Martin Martin Martin Maulidawati, Maulidawati Mauliza Mauliza Mauliza, Mauliza Muhammad Fikry Muhammad Iqbal Muhammad Johan Setiawan Mukti Qamal Mukti Qamal Munirul Ula Nada Syadzwina Nur Afni Yunita Nurdin Nurdin Pangestu, Aridho Putri, Rany Gesta Rio Pratomo Rizal Rizal Rizal Rizal Rizal Rizki Suwanda Safira Adani Sari, Cut Putri Mellita Sayed Fachrurrazi Sri Mulyati Sri Mulyati Suryana, Fitra Taufiq Taufiq Taufiq Taufiq Utomo, Muhammad Fikri Wahyu Fuadi Widyana Verawaty Siregar Yusra, Muhammad Zara Yunizar Zulfikar Aji Kusworo