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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JURNAL MEDIA INFORMATIKA BUDIDARMA J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Majalah Ilmiah Bijak Building of Informatics, Technology and Science Jurnal Teknologi Dan Sistem Informasi Bisnis JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Community Development Journal: Jurnal Pengabdian Masyarakat Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH Computer Science (CO-SCIENCE) J-SAKTI (Jurnal Sains Komputer dan Informatika) EXPLORER CHIPSET (Journal on Computer Hardware, Signal Processing, Embedded System and Networking) Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Innovative: Journal Of Social Science Research Jurnal Pengabdian Masyarakat Bangsa Jurnal Pengabdian Sosial Jurnal Pengabdian Kepada Masyarakat Radisi Jurnal KALANDRA Aksi Kita: Jurnal Pengabdian Kepada Masyarakat Journal of Computer Science Artificial Intelligence and Communications Etanic : Journal Of English Language Teaching And Applied Linguistics Jurnal Ilmu Komputer dan Teknik Informatika Proceedings of The International Conference on Computer Science, Engineering, Social Sciences, and Multidisciplinary Studies MURAKOM
Muhammad Noor Hasan Siregar
Universitas Graha Nusantara, Padangsidimpuan, Sumatera Utara - Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Improving Students' Artificial Intelligence Literacy through Hybrid Training in Supporting the Competency of the Society 5.0 Era Supiyandi Supiyandi; Chairul Rizal; Irman Efendi; Muhammad Noor Hasan Siregar; Arief Wibowo
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 1 (2026): Juli 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i1.1038

Abstract

This community service program aimed to improve university students’ Artificial Intelligence (AI) literacy through hybrid training that supports the competencies required in the Society 5.0 era. The rapid advancement of digital technology has increased the need for students to understand, utilize, and critically evaluate AI technologies in academic and professional contexts. The program was implemented using a hybrid learning approach that combined face-to-face and online learning activities through educational counseling, workshops, interactive discussions, and practical simulations of AI applications. The participants were university students who received training in basic AI concepts, ethical use of AI, digital literacy, and the implementation of AI technologies to support academic activities and twenty-first-century competencies. The instruments used in this activity included training modules, digital presentation media, observation sheets, and pre-test and post-test evaluations to assess participants’ understanding before and after the training sessions. The findings indicated that the hybrid training successfully improved students’ understanding of Artificial Intelligence, enhanced their ability to use AI technologies in academic activities, and increased their awareness of ethical and responsible AI use. Furthermore, the hybrid learning model provided flexible, interactive learning experiences that promoted active participation and strengthened students’ adaptability to the digital transformation in the Society 5.0 era. The program also demonstrated that AI literacy plays a significant role in supporting students’ readiness for technology-driven educational and professional environments. Therefore, hybrid AI literacy training can serve as an effective and relevant model for developing digital competencies in higher education and supporting the transformation of education in the Society 5.0 era.
Sosialisasi Kiat Sukses Promosi Pariwisata Digital Bagi Konten Kreator, Duta Pariwisata, dan Pegawai Dinas Pemuda, Olahraga, dan Pariwisata Kota Padangsidimpuan Yuswin Harputra; Abdul Rahman Suleman; Azhar Harahap; Kasmawati; Muhammad Noor Hasan Siregar
KALANDRA Jurnal Pengabdian Kepada Masyarakat Vol 5 No 4 (2026): Juli
Publisher : Yayasan Kajian Riset Dan Pengembangan Radisi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55266/kalandra.v5i4.677

Abstract

Kegiatan pengabdian kepada masyarakat ini dilatarbelakangi oleh besarnya potensi pariwisata Kota Padangsidimpuan yang belum diimbangi dengan kemampuan promosi digital yang optimal di kalangan konten kreator, duta pariwisata, dan pegawai Dinas Pemuda, Olahraga, dan Pariwisata (Dispora) setempat. Tim dosen Universitas Graha Nusantara (UGN) bekerja sama dengan Dispora Kota Padangsidimpuan menyelenggarakan sosialisasi bertajuk “Kiat Sukses Promosi Pariwisata” pada Selasa, 23 Juni 2026, bertempat di Aula Dinas Pemuda, Olahraga, dan Pariwisata Kota Padangsidimpuan. Metode pelaksanaan berupa ceramah, diskusi, dan tanya jawab dengan materi meliputi pemasaran berbasis media sosial dan konten visual, kolaborasi dengan influencer dan komunitas lokal, optimasi kehadiran digital (SEO dan Google My Business), pemanfaatan user-generated content (UGC) dan pengelolaan ulasan, serta penyusunan paket wisata tematik. Hasil kegiatan menunjukkan peningkatan pemahaman peserta terhadap strategi promosi pariwisata digital serta munculnya komitmen untuk menerapkan materi yang diperoleh dalam pengelolaan destinasi dan konten pariwisata di Kota Padangsidimpuan. Kegiatan ini diharapkan dapat mendorong peningkatan kunjungan wisatawan melalui promosi digital yang lebih efektif dan berkelanjutan.
Market Opportunity and Consumer Preferences Analysis for Sawo (Manilkara zapota L.) Product Diversification as a Local Agribusiness in Angkola Muaratais District Abdul Rahman Suleman; Siti Hardianti Wahyuni; Muhammad Noor Hasan Siregar
Majalah Ilmiah Bijak Vol. 22 No. 2: September 2025
Publisher : Institut Ilmu Sosial dan Manajemen STIAMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31334/bijak.v22i2.4706

Abstract

This study aims to identify the potential for diversification of products from sapodilla fruit (Manilkara zapota L) that need optimally utilized and have high market opportunities in Angkola Muaratais District. Using a descriptive qualitative approach supported by quantitative analysis, this research involved 42 respondents: farmers, workers, SME entrepreneurs, and consumers. Data were collected through in-depth interviews, structured questionnaires, and participatory observation, followed by mixed-method analysis, including product evaluation matrix and market feasibility analysis. Results show three main potential products with significant development opportunities. Premium sapodilla syrup shows the highest potential (score 4.24/5.0), followed by variant sapodilla chips (4.08/5.0) and natural sapodilla jam (3.92/5.0). Market segmentation analysis identifies three main consumer segments: health-conscious (35%), convenience seekers (40%), and traditional value seekers (25%). Digital market penetration projections indicate significant growth potential, reaching 85% through social media and e-commerce channels within six months. Product evaluation reveals that premium sapodilla syrup excels in raw material availability (4.5/5.0) and shelf life (4.5/5.0), while variant sapodilla chips show highest market interest (4.5/5.0) and value addition potential (4.5/5.0). The study indicates substantial market potential with a Total Available Market of 150,000 consumers and a Serviceable Obtainable Market of 15,000 consumers, projecting 15-20% annual market growth. The findings contribute to understanding critical factors in local resource-based product development and support the Green Economy theory regarding sustainable value addition in local economic development. This research provides practical implications for product development strategies and policy recommendations for supporting the sapodilla processing industry at the regional level.
Design and Development of IdentifiKu: A Web-Based Diagnostic Model for Differentiated Learning Muhammad Noor Hasan Siregar; Yulia Rizki Ramadhani; Yusra Fadhillah; Yoviansyah Rizki Pratama
Computer Science (CO-SCIENCE) Vol. 6 No. 1 (2026): January 2026
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/co-science.v6i1.9762

Abstract

This study aims to develop and evaluate IdentifiKu, a web-based diagnostic assessment platform designed to support differentiated learning within the Kurikulum Merdeka framework in Indonesia. Specifically, the research seeks to bridge the gap in existing assessment platforms that predominantly focus on cognitive dimensions by integrating cognitive and non-cognitive domains—learning styles, personality traits, and multiple intelligences—into a unified scoring model. The platform was developed using a Design and Development Research (DDR) approach combined with the Waterfall Software Development Life Cycle (SDLC), encompassing requirements analysis, system design, implementation, testing, and deployment. The architecture adopts a three-tier client–server model, with a Laravel-based application layer and a MySQL database optimized to the third normal form. Performance evaluation involved functional testing and user feedback from twelve teachers across diverse subject areas. Quantitative results indicated that the system met or exceeded all operational benchmarks, including an average page load time of 2.4 seconds, 99.8% uptime, 100% scoring accuracy, and a System Usability Scale (SUS) score of 85.3. Teachers reported that the platform’s comprehensive learner profiles facilitated targeted instructional strategies, improved student engagement, and streamlined assessment processes. This research contributes a scalable, pedagogically aligned model for integrating multidimensional diagnostics into differentiated learning practices, which may be adapted to other educational contexts to enhance data-driven instruction.
Analisis Sentimen Pelanggan terhadap Produk UMKM pada Marketplace Menggunakan Algoritma Naïve Bayes Akhiruddin Pulungan; Muhammad Noor Hasan Siregar; Hery Dia Anata Batubara
MUARA KOMPUTER : Jurnal Ilmiah Ilmu Komputer & Elektronika Vol. 2 No. 3 (2026): MUARA KOMPUTER : Jurnal Ilmiah Ilmu Komputer & Elektronika
Publisher : CV MUARA EDUKASI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64365/murakom.v2i3.484

Abstract

The rapid growth of online marketplaces has provided significant opportunities for Micro, Small, and Medium Enterprises (MSMEs) to market their products to a broader audience. Customer reviews posted on marketplaces contain valuable information regarding customer satisfaction, experiences, and perceptions of the products and services offered. However, the increasing volume of reviews makes manual analysis inefficient and time-consuming. Therefore, an automated method is needed to process and analyze review data effectively. This study aims to analyze the sentiment of MSME reviews on marketplaces using the Naïve Bayes algorithm and Natural Language Processing (NLP) techniques. This research employs a text mining approach consisting of data collection, preprocessing stages including case folding, tokenization, stopword removal, and stemming, followed by term weighting using the Term Frequency-Inverse Document Frequency (TF-IDF) method. The processed data are then classified into three sentiment categories: positive, negative, and neutral, using the Naïve Bayes algorithm. Model performance is evaluated using a confusion matrix as well as accuracy, precision, recall, and F1-score metrics. The results indicate that the Naïve Bayes model performs well in classifying sentiment from marketplace reviews. Based on the confusion matrix, the model correctly classified 176 out of 200 testing data instances. The evaluation results show an accuracy of 88.00%, precision of 87.25%, recall of 86.80%, and F1-score of 87.02%. The best performance was achieved in the positive sentiment class, with a precision of 92.96%, recall of 94.29%, and F1-score of 93.62%. These findings demonstrate that the Naïve Bayes method combined with NLP techniques is effective for conducting sentiment analysis of MSME reviews on marketplaces. This study is expected to assist MSME owners in understanding customer opinions more quickly and accurately, thereby providing valuable insights for improving product quality and service performance.
Perancangan Aplikasi Data Mining Untuk Menentukan Pasien Menderita Tifoid Dengan Metode Algoritma C4.5 Yusra Fadhillah; Muhammad Noor Hasan Siregar; Oberlin Siagian
Explorer Vol 1 No 2 (2021): Juli 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v1i2.92

Abstract

Data mining adalah suatu istilah yang digunakan untuk menguraikan penemuan pengetahuan didalam database. Proses data minig ini akan diimplementasikan dengan menggunakan algoritma C.45. Algoritma C.45 dapat digunakan dalam pembentukan pohon keputusan tetapi lebih mengarah pada perhitungan probabilitas dari tiap-tiap record terhadap kategori-kategori tersebut atau untuk mengklarifikasi record dengan mengelompokan ke dalam satu kelas. Setelah sebuah pohon keputusan dibangun maka dapat digunakan untuk mengklarifikasi record yang beulm ada kelasnya. Dimulai dari node root menggunakan tes terhadap atribut dari record yang belum ada kelasnya, kemudian mengikuti cabang sesuai dengan proses pohon keputusan yanitu mengubah bentuk data (table) menjadi pohon (tree) kemudian merubah model pohon tersebut menjadi aturan. Berdasarkan penelitian yang telah dilakukan yang telah dibangun dapat menentukan pasien yang menderita penyakit tipes.
Utilization of Sales Data Analysis for Product Recommendation Systems in E-Commerce Using the Apriori Algorithm Muhammad Noor Hasan Siregar; Furqan Khalidy; Rismayanti; Khairunnisa
Journal of Computer Science, Artificial Intelligence and Communications Vol 1 No 2 (2024): November 2024
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v1i2.17

Abstract

The rapid development of e-commerce has significantly increased the volume of sales transactions and customer interaction data. This presents an opportunity for businesses to leverage data mining techniques to extract valuable insights that support decision-making processes. One such application is the development of product recommendation systems, which play a crucial role in enhancing customer satisfaction and driving sales. This research focuses on utilizing sales transaction data to build a product recommendation system using the Apriori algorithm, a well-known method for association rule mining. The study begins with the collection and preprocessing of transaction data from an e-commerce platform. Through the application of the Apriori algorithm, frequent itemsets are identified, and association rules are generated based on specified support and confidence thresholds. These rules reveal purchasing patterns and relationships between products that are frequently bought together. The system then uses these patterns to recommend relevant products to users, aiming to improve cross-selling opportunities and personalize the shopping experience. The results demonstrate that the Apriori-based recommendation model is effective in identifying meaningful product combinations and can be implemented as a lightweight, interpretable alternative to more complex machine learning methods. Furthermore, the system helps e-commerce businesses optimize inventory management and marketing strategies by understanding customer buying behavior. This research concludes that the integration of the Apriori algorithm into recommendation systems provides tangible benefits for e-commerce platforms seeking data-driven personalization solutions.
Evaluating the Impact of Knowledge Management Systems on Organizational Performance: A Technology Company Case Amru Yasir; Deni Apriadi; Muhammad Noor Hasan Siregar; Divi Handoko; M. Arif Rahman
Journal of Computer Science, Artificial Intelligence and Communications Vol 2 No 1 (2025): May 2025
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/jocsaic.v2i1.27

Abstract

This study aims to evaluate the impact of Knowledge Management Systems (KMS) on organizational performance within a technology company. In the digital era, knowledge has become a critical asset that drives innovation, efficiency, and competitive advantage. By leveraging a case study approach, the research examines how the implementation of KMS influences various performance indicators, including productivity, decision-making quality, employee collaboration, and knowledge retention. Data were collected through interviews, observations, and internal documents, and analyzed using a mixed-method approach. The findings suggest that effective use of KMS significantly improves organizational agility and innovation capabilities. However, the study also identifies challenges such as resistance to change, lack of user training, and insufficient integration with existing workflows. To maximize the benefits of KMS, organizations must foster a knowledge-sharing culture, provide ongoing support, and align KMS strategies with business objectives. The insights from this research are expected to contribute to the development of more effective knowledge management practices in technology-based organizations.
Co-Authors , Eka Putra AA Sudharmawan, AA Abdul Rahman Suleman Ade Ismail Abdul Kodir Agus Perdana Windarto Akhiruddin Pulungan Alfiarini Alkhairi, Putrama Amru Yasir Anata, Hery Dia Arief Wibowo Aswan, Novita Azhar Harahap Badawi, Masrof Chairul Rizal Deni Apriadi Deni Apriadi Divi Handoko Edi Suharto Eka Putra Fachri, Barany Fadhillah , Yusra Fadhillah, Yusra Ferawati Artauli Hasibuan Ferawati Artauli Hasibuan Furqan Khalidy Harahap, Angelia Utari Harputra, Yuswin Hasibuan, Ferawati Artauli Hendry Hendry . HERY DIA ANATA BATUBARA Indra Prasetia, Indra Indra Riyana Rahadjeng Indra Riyana Rahadjeng Irman Efendi Jumaria Nasution Kasmawati Khairunnisa, Khairunnisa Lubis, Fitri Romaito M. Arif Rahman Mardiah Meiliana Friska Muhammad Eka Muhammad Hasanuddin, Muhammad Muhammad Iqbal Muhammad Iqbal Muhammad Yasin Simargolang Muhammad Zen Munadi Munadi Nuranisah Nurkhasanah Rina Puspita Oberlin Siagian Putra, Randi Rian Raharjo, Mokhamad Ramdhani Ramadhani, Cerah Fitri Ramadhani, Yulia Rizki Rismayanti Rismayanti Rismayanti Rizki, Cindy Atika Rusmin Saragih, Rusmin Setiawan, Yudika Dwi Siti Hajar Siti Hardianti Wahyuni Siti Khodijah Suleman, Abdul Rahman Supiyandi Supiyandi Surya Handayani Toga Mahaji Yoviansyah Rizki Pratama Yuhandri Yuhandri, Yuhandri Yulia Rizki Ramadhani Yusra Fadhillah Yusra Fadhillah Yuswin Harputra