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All Journal Jurnal 'Aisyiyah Medika Babul Ilmi Jurnal Ilmiah Multi Science Kesehatan Journal of Intelligent Decision Support System (IDSS) Jurnal Mandiri IT Journal of Information Systems and Technology Research Agrikan: Jurnal Agribisnis Perikanan Journal of Artificial Intelligence and Digital Business Jurnal Perjuangan dan Pengabdian Masyarkat: JPPM Journal of Tecnologia Quantica
Suherwin, Suherwin
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary

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Pembangunan Sistem AI Berdasarkan Analisis Aktivitas Digital Untuk Mengidentifikasi Gaya Belajar Siswa Suherwin, Suherwin; Rachmat, Rachmat; Said, Irfan; Asia, Siti Nur
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 2 (2025): Mei - Juli
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i2.991

Abstract

Studi ini menyarankan untuk membangun sistem berbasis AI untuk mengidentifikasi gaya belajar siswa dengan menganalisis aktivitas digital mereka dalam sistem manajemen pembelajaran (LMS) atau platform pendidikan online lainnya. Sistem ini menggunakan algoritma pembelajaran mesin untuk memproses data seperti frekuensi login, pola interaksi konten, waktu yang dihabiskan untuk aktivitas, dan perilaku navigasi. Dengan memetakan perilaku ini ke dalam kerangka gaya belajar yang telah ditetapkan (misalnya, visual, auditori, kinestetik), sistem AI memberikan wawasan waktu nyata tentang preferensi masing-masing siswa. Efektivitas hasil pendidikan sangat dipengaruhi oleh keberagaman gaya belajar siswa, dan metode tradisional untuk mengidentifikasi gaya belajar sering kali bergantung pada kuesioner atau observasi manual, keduanya memakan waktu dan dapat dipengaruhi oleh bias.
Deep Learning-Based Sentiment and Emotion Analysis of Social Media Data to Identify Factors Affecting Healthy Food Choices in Urban Communities Rasyid, Rachmat; Rafli R, Muh; Faisal, Faisal; Suherwin, Suherwin; Asia, Siti Nur; Karimi, Amir
Journal of Information Systems and Technology Research Vol. 4 No. 3 (2025): September 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i3.1288

Abstract

The increasing influence of social media on public perception has made it a powerful driver of dietary behavior in urban communities. Nevertheless, the abundance of unverified health information often obscures individuals’ ability to make informed food choices. This study proposes a deep learning-based framework to analyze sentiment and emotion from social media discourse in order to uncover the key factors affecting healthy food decisions in urban settings. By applying Natural Language Processing (NLP) techniques and advanced deep learning models to a large corpus of user-generated content, the research identifies significant patterns linking emotional expression with food-related decision-making. The results indicate that positive emotions, such as pride and satisfaction, are strongly associated with healthy food promotion, while negative emotions, including frustration, are predominantly tied to affordability, accessibility, and convenience issues. Among these, price and food quality emerge as the most critical determinants shaping consumer preferences. These findings underscore the importance of integrating emotional and socio-economic considerations into public health strategies. Beyond offering empirical insights, this study demonstrates the scalability and effectiveness of deep learning in extracting nuanced perspectives from unstructured social media data, thereby contributing a robust methodological approach for real-time public health monitoring and intervention design.  
Real-Time IoT Integration for Coal Production And Distribution Management Sani , Hendra; Rasyid, Rachmat; Asia, Siti Nur; Syamsuddin, Syamsuddin; Suherwin, Suherwin; Șerban, Răzvan
Journal of Information Systems and Technology Research Vol. 4 No. 3 (2025): September 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i3.1295

Abstract

The coal production and distribution industry faces persistent challenges in data management, operational coordination, and decision-making efficiency. Conventional monitoring methods often result in delayed reporting, low data accuracy, and limited adaptability to dynamic market demands. This study addresses the lack of an intelligent and integrated information system by designing and developing a real-time IoT-based solution for coal production and distribution management. The system was built using the Software Development Life Cycle (SDLC) with the Waterfall model and integrates IoT sensors to automatically capture critical parameters such as pressure, temperature, and coal quality indicators. Artificial Intelligence (AI) components were incorporated to enhance data analysis and support predictive decision-making. System evaluation through simulation with dummy data demonstrated notable improvements, including a 40% reduction in reporting response time and a 95% increase in operational data accuracy. The system also enabled faster production monitoring, streamlined distribution processes, and provided decision-makers with reliable real-time insights. User feedback confirmed the system’s effectiveness in improving accessibility, monitoring efficiency, and overall operational performance in coal production and distribution management.
Human-AI Interaction dengan Antarmuka Suara dalam Bahasa Lokal/Dialek Nusantara Suherwin, Suherwin; Asia, Siti Nur; Rachmat, Rachmat
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 3 (2025): Agustus - October
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i3.3113

Abstract

Penelitian ini mengeksplorasi kemampuan kecerdasan buatan (AI) dalam memahami perintah suara yang diucapkan dalam bahasa lokal atau dialek Nusantara, yang memiliki keragaman fonetik, intonasi, dan kosakata khas daerah. Tujuan utama dari penelitian ini adalah untuk mengembangkan model pengenalan suara berbasis deep learning yang mampu mengenali perintah suara dalam berbagai dialek lokal Indonesia dengan akurasi tinggi. Penelitian ini melibatkan tahapan pengumpulan data audio dari penutur asli berbagai daerah, yang mencakup berbagai dialek dan aksen lokal. Selanjutnya, data yang terkumpul menjalani proses pra-pemrosesan untuk membersihkan noise dan menormalkan variasi suara. Model pengenalan suara dilatih menggunakan pendekatan transfer learning, memanfaatkan model pretrained yang kemudian disesuaikan dengan data lokal melalui teknik fine-tuning. Evaluasi dilakukan menggunakan metrik Word Error Rate (WER) dan Command Accuracy untuk mengukur tingkat kesalahan dan akurasi model dalam mengenali perintah suara. Hasil penelitian menunjukkan bahwa akurasi pengenalan suara dalam dialek lokal lebih rendah dibandingkan dengan Bahasa Indonesia baku, namun teknik data augmentation dan fine-tuning model pretrained dapat menurunkan tingkat kesalahan hingga 15–20%. Selain itu, uji pengguna menunjukkan bahwa teknologi AI yang mendukung dialek lokal meningkatkan tingkat kenyamanan, kepercayaan, dan penerimaan pengguna. Penelitian ini menekankan pentingnya pengembangan dataset suara daerah yang lebih beragam dan desain antarmuka suara yang adaptif, guna memastikan teknologi AI yang lebih inklusif secara linguistik dan kultural.
Pengembangan DSS Berbasis Geospatial Topsis untuk Prioritas Distribusi Bantuan Sosial di Sulawesi Selatan Suherwin, Suherwin
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.3482

Abstract

Dalam penyaluran bantuan sosial, bencana alam dan krisis sosial selalu memerlukan respons yang cepat. Distribusi yang tidak tepat sasaran atau terlambat dapat menyebabkan kondisi masyarakat umum semakin memburuk. Tujuan dari penelitian ini adalah untuk mengembangkan Sistem Pendukung Keputusan (DSS) berbasis Geospasial dan metode Teknik Preferensi Urutan dengan Kesamaan terhadap Solusi Ideal (TOPSIS) untuk menentukan prioritas distribusi modal sosial di Sulawesi Selatan. DSS ini mengintegrasikan data geografis, seperti kepadatan penduduk, infrastruktur jalan, lokasi fasilitas kesehatan, dan kerentanan wilayah tingkat, dengan kriteria yang relevan untuk distribusi dana. Metode TOPSIS digunakan untuk merangking lokasi atau wilayah alternatif berdasarkan keselarasan mereka dengan solusi positif ideal dan deviasi dari solusi negatif ideal, meningkatkan jumlah kriteria yang ditentukan oleh pakar atau analisis hirarki. Data geospasial dianalisis dan dianalisis menggunakan Sistem Informasi Geografis (SIG) untuk memvisualisasikan hasil prioritisasi dan mendukung pengambilan keputusan yang lebih informatif. hasil yang memprioritaskan dan mendorong penulisan keputusan yang lebih informatif. Hasil penelitian menunjukkan bahwa DSS ini dapat memberikan rekomendasi untuk distribusi modal sosial secara objektif dan spasial. Seiring dengan meningkatnya V, demikian pula tingkat prioritas untuk memperoleh distribusi sosial dari pemerintah Sulawesi Selatan, seperti di Makassar (0,75), Gowa (0,48), Maros (0,45), Bone (0,29), dan Wajo. (0,25). Ini membantu pemerintah dan organisasi kemanusiaan di daerah tersebut mengelola sumber daya dengan cara yang lebih efisien dan efektif. Diharapkan bahwa implementasi DSS ini akan meningkatkan akurasi dan kecepatan penyaluran bantuan, mengurangi dampak negatif bencana, dan memaksimalkan penggunaan anggaran bantuan sosial di Sulawesi Selatan.
The Effectiveness of Interactive Learning Media Based on Augmented Reality in Enhancing Elementary School Students’ Learning Motivation Faisal, Faisal; Rachmat, Rachmat; Asia, Siti Nur; Suherwin, Suherwin; Ibrahim, Abdul
Journal of Tecnologia Quantica Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i3.2443

Abstract

This study aims to analyze the effectiveness of using augmented reality (AR) based learning media in enhancing the learning motivation of elementary school students. By employing a multiple linear regression approach on simulated data, this research evaluates the influence of several key factors, namely AR visualization quality, teacher support, ease of use, and supporting infrastructure. The analysis results show that AR visualization quality, teacher support, and ease of use significantly affect the improvement of learning motivation. The developed model has a coefficient of determination (R² ? 0.77), indicating that 77% of the variation in learning motivation can be explained by the independent variables, with a relatively small prediction error (RMSE ? 0.53). The F-test also confirmed that the model is overall significant. These findings indicate that the integration of AR in learning not only increases visual appeal but also strengthens the role of teachers and enhances students’ ease of interaction with the material. Nevertheless, this study is still based on simulated data, so further research with broader and more realistic empirical data is required to validate the results.
Videography Training: Improving the Soft Skills of the Young Generation Through Digital Content Rachmat, Rachmat; Yusuf, Muhammad; Faisal, Faisal; Asia, Siti Nur; Suherwin, Suherwin; Basmar, Muh. Fahmi
Jurnal Perjuangan dan Pengabdian Masyarakat : JPPM Vol. 1 No. 2 (2025): 31 Mei 2025
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Pejuang Republik Indonesia

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

Abstract

The development of digital technology and social media has created great opportunities for young people to develop videography skills as valuable soft skills. This community service activity aims to improve the videography skills of young people in East Luwu Regency through digital content creation training. The implementation method includes theoretical training on the basics of videography, hands-on practice using equipment, and video editing workshops. The activity was carried out for 3 days involving 30 participants from youth and students in East Luwu Regency. The results of the activity showed a significant increase in participants' understanding of shooting techniques, video composition, and basic editing. Pre-test and post-test showed an increase in average scores from 45.2 to 78.6. Participants successfully produced 15 quality short videos showcasing the tourism and cultural potential of East Luwu. This activity has a positive impact in developing creativity and digital capabilities of young people, and has the potential to open creative economy opportunities in the region. Follow-up activities are needed to maintain and develop the abilities that participants have acquired.
Co-Authors Abdul Ibrahim, Abdul Asia, Siti Nur Bainani, Bainani Basmar, Muh. Fahmi Faisal Faisal Febriyanti, Arly Hipson, Meita Irfan Said Iskandar, Syamsul Bhahri Karimi, Amir Kasmawaru, Kasmawaru Khoirin, Khoiirn Kurniawaty Kurniawaty Muhammad Yusuf Nonta, Cindy NOPIANTI, NOPIANTI Oktapioni, Nandita P. Alhabsyi, Gina Audina Rachmat , Rachmat RACHMAT RACHMAT Rafli R, Muh Rasyid, Rachmat Sani , Hendra Serban, Razvan SITI MAHMUDAH Sry Putri, Nilam Syamsuddin Syamsuddin Widya Arisandy Zulkifli, Kifayatul Khair Masyhuda