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All Journal International Journal of Electrical and Computer Engineering Techno.Com: Jurnal Teknologi Informasi Teika JSI: Jurnal Sistem Informasi (E-Journal) DINAMIKA DOTCOM TEKNOLOGI INFORMASI Jurnal Informatika Sisforma: Journal of Information Systems ANDHARUPA Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Jurnal Ilmiah KOMPUTASI Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Petir QARDHUL HASAN: MEDIA PENGABDIAN KEPADA MASYARAKAT J-SAKTI (Jurnal Sains Komputer dan Informatika) Multitek Indonesia : Jurnal Ilmiah Jurnal Riset Informatika Jurnal Teknologi Terapan Antivirus : Jurnal Ilmiah Teknik Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Abdi Dosen : Jurnal Pengabdian Pada Masyarakat Generation Journal Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Jurnal Abdimas Berdaya : Jurnal Pembelajaran, Pemberdayaan dan Pengabdian Masyarakat J-SAKTI (Jurnal Sains Komputer dan Informatika) International Conference on Industrial Revolution for Polytechnic Education Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Brilliance: Research of Artificial Intelligence MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Software Development Digital Business Intelligence and Computer Engineering Kohesi: Jurnal Sains dan Teknologi Jurnal Informatika Polinema (JIP) Pengabdian Pendidikan Indonesia (PPI) International Journal of English Language and Pedagogy Jurnal Pengabdian Kepada Masyarakat
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Automated Synthesis Of Product Return Recommendations Via Groq And Large Language Models Dian Hanifudin Subhi; usman nurhasan; Ibnu Tsalis Assalam
MULTITEK INDONESIA Vol 20 No 1 (2026): July
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/mtkind.v20i1.13659

Abstract

Industrial economic resilience depends on the efficiency of after-sales service provisioning, which is often hindered by semantic ambiguity in customer reports and latency constraints of conventional computing infrastructures. This study examines the integration of a Language Processing Unit (LPU) with a Large Language Model (LLM) under a Deterministic Reasoning Architecture (DRA) framework to address these limitations. Experiments were conducted on a heterogeneous dataset (N = 27.500) consisting of operational service records from PT Rekaindo Global Jasa and a Southeast Asian manufacturing entity over the period 2021–2025. Semantic complexity analysis based on Shannon Entropy indicates that the Repair category exhibits the highest information density (5.2 bits), corresponding to an increased risk of logical failure. Performance benchmarking demonstrates that the proposed LPU-based architecture achieves deterministic inference with a Risk Priority Number (RPN) of 42 significantly lower than stochastic GPU-based baselines (RPN > 120). Predictive integrity evaluation yields an AUC–ROC of 0.988 and an inter-rater agreement of 0.81 (Fleiss Kappa), indicating substantial alignment between automated recommendations and expert assessments. Economic robustness is validated through Monte Carlo simulations, showing a 94.2 % probability of achieving Return on Investment within 20 months, even under high-volatility scenarios. Furthermore, the framework complies with ISO/IEC 42001:2023 and the EU AI Act, achieving a Fairness Ratio above 0.94. Overall, the results demonstrate that the LPU–LLM synergy enables fast, reliable, and responsible generative AI deployment in industrial settings.
Bahasa Inggris Usman Nurhasan; Dian Hanifudin Subhi; Anugrah Nur Rahmanto; Endah Septa Sintiya; Deddy Kusbianto Purwoko Aji
MULTITEK INDONESIA Vol 20 No 1 (2026): July
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/mtkind.v20i1.13681

Abstract

Automated evaluation of flowchart representations is essential for the facilitation of the acquisition of basic programming concepts. Nevertheless, traditional evaluation systems that rely exclusively on structural matching demonstrate some of their most fundamental limitations. The false negative misclassification rates of such systems are frequently high when students create visually distinct structures for algorithmic logic that are semantically equivalent. A hybrid assessment framework is introduced in this study to improve the reliability and efficacy of code evaluation in order to address this challenge. The model that has been proposed combines the probabilistic feature extraction capabilities of Graph Convolutional Networks (GCNs) with mathematical logic verification through symbolic execution of an SMT Solver. While the SMT Solver deterministically establishes functional equivalence, the GCN module adaptively manages graph topological variations. Use of a real-world dataset consisting of 3.600 flowcharts generated by novice students was implemented to assess the hybrid system's functionality. According to quantitative experimental results, the proposed framework obtained a peak F1 Score of 0.88, which is a substantial improvement over conventional Abstract Syntax Tree (AST) methods (F1 Score 0.75). Additionally, the 77.4% reduction in false negative rates was achieved by incorporating the SMT Solver in comparison to a pure GCN configuration. Finally, the semantic equivalence and structural divergence issues that arise during algorithm assessment are effectively resolved by this dual architectural integration. By implementing the proposed system, higher education institutions are equipped with a more dependable mechanism for reducing human error, thereby improving the impartiality, accuracy, and efficiency of the evaluation process.
Evaluasi Usabilitas Aplikasi DLU Ferry Pasca-Optimalisasi Menggunakan System Usability Scale (SUS) dan A/B Testing: Studi Kasus dengan Pendekatan Design Thinking Fablo Aimar; Anugrah Nur Rahmanto; Usman Nurhasan
TeIKa Vol 15 No 2 (2025): Jurnal
Publisher : Fakultas Teknologi Informasi - Universitas Advent Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36342/09mavq33

Abstract

The DLU Ferry application has not fully met user expectations in terms of ease of understanding information on schedules, fares, and supporting features, and often experiences data synchronization issues that can undermine user confidence. This study aims to optimize the user interface of the DLU Ferry application to meet user needs for clear, accessible, and real-time information. The Design Thinking approach (Empathize, Define, Ideate, Prototyping, Testing) was chosen because it prioritizes user-centricity, facilitates a deep understanding of user needs and challenges, and enables the creation of sustainable and iterative solutions. Quantitative testing was conducted using the System Usability Scale (SUS) and A/B Testing. The final iteration of the SUS testing yielded an average score of 86, indicating the “Excellent” or “Best Imaginable” category in terms of usability, proving the success of the optimization efforts. However, there are areas for continuous improvement based on respondent feedback, including enhancing application performance and stability, refining the user interface, adding features, improving information quality and accessibility, and strengthening customer service and integration.
Pelatihan Penggunaan AI untuk Peningkatan Kinerja Perangkat Kelurahan Tasikmadu, Kota Malang Satrio Binusa Suryadi; Muhammad Unggul Pamenang; Galih Putra Riatma; Usman Nurhasan; Anugrah Nur Rahmanto; Moch. Zawaruddin Abdullah
Pengabdian Pendidikan Indonesia Vol. 2 No. 02 (2024): Artikel Periode Agustus 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ppi.v2i02.4802

Abstract

Kegiatan pengabdian masyarakat ini mencakup pelatihan dan praktek langsung tentang pemanfaatan kecerdasan buatan (Artificial Intelligence) untuk staf di Kelurahan Tasikmadu, Kota Malang. Pelatihan ini merupakan lanjutan dari kegiatan pengabdian masyarakat di tahun sebelumnya tentang peningkatan informasi layanan pada masyarakat melalui media Canva. Pelatihan dan praktek langsung ini bertujuan untuk meningkatkan performa staf Kelurahan Tasikmadu kota Malang dalam memberikan pelayanan pada masyarakat. Artificial Intelligence (AI) memiliki beberapa kelebihan, salah satunya efisiensi pekerjaan yang dilakukan semisal menyusun draft proposal, mengedit dan merubah foto menjadi video, atau membuat video singkat yang atraktif untuk sarana sosialisasi kegiatan dan acara di lingkungan kelurahan Tasikmadu. Pelatihan dilaksanakan selama 2 minggu, dengan agenda pembekalan materi di minggu pertama dan praktek menggunakan AI di minggu kedua. Kegiatan ini juga sejalan dengan misi peningkatan sumber daya manusia di lingkungan kelurahan Tasikmadu untuk mengintegrasikan teknologi yang mendukung dan memudahkan pekerjaan administrasi staf. Sehingga pelatihan pemanfaatan kecerdasan buatan (AI) ini bisa meningkatkan pengetahuan staf kelurahan Tasikmadu untuk meningkatkan performa kerja mereka.
MOBILE MEDIA LITERATURE APPLICATION FOR IDENTIFICATION OF STUDENT'S READING INTEREST Usman Nurhasan; Erninda Ristiani; Samsul Islam Baddrisshofa
Jurnal Riset Informatika Vol. 3 No. 4 (2021): September 2021 Edition
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (615.861 KB) | DOI: 10.34288/jri.v3i4.105

Abstract

The School Literacy Movement (GLS) aims to foster youth character through a culture of literacy (reading and writing). However, in the presence of the Covid-19 outbreak, Indonesian education needs to use online media to keep learning going. Many types of platforms are used for online learning media, but all of these media do not support school literacy activities, so school literacy activities do not run as usual. Based on these problems, a solution was created, namely an application that makes it easy for literacy activities to take place online. Students can access this application to do online literacy via a laptop or smartphone. This application makes it easier for teachers to monitor the course of online literacy programs. The results of this study are indicated by functional testing on all features obtaining a 100% valid percentage. Tests on users get an average percentage of more than 80%. The test results prove that this application can be accepted by students, teachers and admins at State High School 1 Geger Madiun to make literacy activities more effective and efficient.
Analisis Gamifikasi Fill-in-the-Blank dengan Evaluasi Otomatis Abstract Syntax Tree Pada Pembelajaran Python Margaretha Violina Putri; Usman Nurhasan; Hendra Pradibta
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3250

Abstract

This study develops and implements a Fill-in-the-Blank (FIB)-based learning system with gamification and automatic evaluation using Abstract Syntax Tree (AST) in Basic Python Programming learning. The applied methodology combines Research and Development (R&D) to design a prototype and Quasi-Experiment with a pre-test, post-test design on the experimental group (n=26) and control group (n=25). Needs analysis through literature, lecturer interviews, and classroom observations resulted in an interactive system with points, levels, and badges mechanisms. Measurement instruments include AST evaluators, concept understanding tests, motivation questionnaires, and student activity logs. The System Usability Scale (SUS) results averaged 76.47, indicating the system is easy to use and well-accepted. Blackbox testing confirmed that all features function as designed. Quasi-Experiment analysis showed a significant improvement in the experimental group, from Pre-Test 27.45 to Post-Test 92.92 (Paired Sample T-Test, p = 0.000) with stable retention in the Delay-Test 81.84 (p = 0.087), while the control group only improved limitedly. Independent Sample T-Test also proved a significant difference between the experimental and control groups. These findings demonstrate the effectiveness of the FIB system in improving learning outcomes, comprehension retention, and interactive learning experiences.Keywords: Abstract Syntax Tree; Fill-in-the-Blank; Gamification; Python Programming; Learning SystemAbstrakStudi ini mengembangkan sistem pembelajaran Fill-in-the-Blank (FIB) berbasis gamifikasi dan evaluasi otomatis Abstract Syntax Tree (AST) untuk pembelajaran Python dasar. Metode yang digunakan menggabungkan Research and Development (R&D) dalam perancangan prototipe dan Quasi-Experiment dengan desain pre-test dan post-test pada kelompok eksperimen (n=26) dan kontrol (n=25). Analisis kebutuhan menghasilkan sistem interaktif dengan fitur poin, level, dan lencana. Instrumen evaluasi meliputi AST evaluator, tes konsep, kuesioner motivasi, dan log aktivitas. Hasil System Usability Scale (SUS) mencapai 76,47, menunjukkan sistem mudah digunakan. Uji blackbox memastikan seluruh fitur berfungsi sesuai rancangan. Hasil eksperimen menunjukkan peningkatan signifikan pada kelompok eksperimen dari 27,45 ke 92,92 (p = 0,000) dan retensi stabil 81,84 (p = 0,087), sementara kelompok kontrol hanya meningkat terbatas. Secara keseluruhan, sistem FIB terbukti efektif meningkatkan hasil belajar, retensi pemahaman, dan pengalaman belajar interaktif. 
Implementation of multimarker augmented reality on solar system simulations Hendra Pradibta; Usman Nurhasan; Muhammad Dwi Aldi Rizaldi
Matrix : Jurnal Manajemen Teknologi dan Informatika Vol. 11 No. 3 (2021): Matrix: Jurnal Manajemen Teknologi dan Informatika
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/matrix.v11i3.130-139

Abstract

The solar system is one of the natural phenomena taught at school. However, delivering the material is still text-based. One of the current technology-based learning uses technology Augmented Reality as a support for learning aid. Augmented Reality is an integrated two worlds, the real and the virtual. Augmented Reality for the solar system learning application was developed by applying the concept of the Rule-Based System algorithm as a simple artificial intelligence that aims to help augmented reality systems in simulating knowledge and experience from humans with several rules prepared. The existence of Augmented Reality facilitates the process of learning on specific topics such as the solar system more attractive and interactive, with aims to inspire students to learn the solar system. Based on the testing results at SDN Purwantoro 2 Malang, Indonesia 95% of respondents are interested and captivated by learning media applications using Augmented Reality technology.
Co-Authors Aflah Rahman Maulidiyah Al Huda, Muhammad Iqbaluddin Alwy Abdullah Ananta, Ahmadi Yuli Andre Asmara, Rossa Anisa Dyah Fatmawati Anugrah Nur Rahmanto Anugrah Nur Rahmantyo Arief Prasetyo Arief Prasetyo Atiqah Nurul Asri Bagas Setya Dian Nugraha Banni Satria Andoko Betlian Fajrin Budi Harijanto, Budi Cahyana, Cahyana Cahyana, Yuanita Hendra Candra Bella Vista Deddy Kusbianto Purwoko Aji Defandy Fanny Abdillah Dian Hanifudin Subhi Didik Dwi Prasetya Dika Rizky Yunianto Efita Tria Wardani Eka Larasati Amalia Elly Setyo Astuti Embriani Dewi Lestari Endah Septa Sintiya Erfan Rohadi Erninda Ristiani Fablo Aimar Faiz Ushbah Mubarok Fakhris Khusnu Reza Mahfud Fredo Vale Yuda Ughay Galih Putra Riatma Gilang Lazuardi Hakimah, Rafidah Putri Hartati, Kirana Hendra Pradibta Hilmy Setya Purnama Putra Ibnu Tsalis Assalam Imam Fahrur Rozi Indra Dharma Wijaya Indra Dharma Wijaya, Indra Dharma Kurnia, Alwan Ghozi Lazuardi, Gilang Lisuardi, Dina Lumintang, Galur Arasy Margaretha Violina Putri Maulidiyah, Aflah Rahman Melani, Erlin Mita Kartina Sari Moch Hafiz Nasirrudin Moch Zawaruddin Abdullah Muhammad Dwi Aldi Rizaldi Muhammad Mujahid Muhammad Rizki Oktaviansyah Muhammad Shulhan Khairy Mula Agung Barata Mustika Mentari Nasirrudin, Moch Hafiz Ningtyas, Noviana Nugraha, Bagas Setya Dian Nur Rahmanto, Anugrah Nur Wijayaningrum, Vivi Nurindrasari, Diana Oktaviansyah, Muhammad Rizki Pamenang, Muhammad Unggul Pramana Yoga Pramana Yoga Saputra Pramudhita, Agung Nugroho Pratama Putra Marhendra Prihatmanda, Ryan Akbar Purnomo, Bagus Putra Prima Arhandi, Putra Prima Qori, Elsa Lusiana Rafandi, Hanif Naufal Rafidah Putri Hakimah Rahma Sabita, Almira Rahmanto, Anugrah Nur Rahmantyo, Anugrah Nur Rakhmat Arianto Retno Damayanti Retno Damayanti Retno Damayanti Soejoedono Riatma, Galih Putra Risa Juliadilla Rizky Alifian Rokhimatul Wakhidah Rosa Andrie Asmara Rozan, Naufal Rudy Ariyanto Rudy Ariyanto Ryan Akbar Prihatmanda Samsul Islam Baddrisshofa Saputro, Halim Teguh Satrio Binusa Suryadi Satrio Binusa Suryadi Sukmadewi, Ferina Sumiadji Suryadi, Satrio Binusa Suryani, Debhys Syaad Patmanthara Syalwa, Laduni Estu Tresna, Esa Luh Tresna, Tresna Triswidrananta, Odhitya Desta Ulfa, Farida Vivin Ayu Lestari Wardani, Efita Tria Wijanarko, Eko Setio Yoga, Pramana Zainal Abdul Haris Zainal Abidin