Garuda - Garba Rujukan Digital

Decision Support System Assessing Feasibility Taekwondo Athlete (UPN “VETERAN” Yogyakarta) Nur Heri Cahyana; Fachrizal Herdiansyah; Rifki Indra Perwira
SENATIK STT Adisutjipto Vol 5 (2019): Peran Teknologi untuk Revitalisasi Bandara dan Transportasi Udara [ISBN 978-602-52742-
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/senatik.v5i0.341

Indonesian taekwondo athlete's achievements have improved because he managed to win several medals in international championships. Being a taekwondo athlete requires a willingness, discipline, good physical condition, experience, mental endurance, unyielding spirit, and proper posture. The assessment process is still done manually by asking taekwondo for their availability in the match; therefore, it requires a decision support system to measurement of participants (taekwondoin). Decision support is a way to provide problem-solving skills and be able to support the work of a coach in solving problems by giving suggestions towards certain decisions. The purpose of Simple Additive Weighting is to determine the feasibility of taekwondoin selection to become an athlete on the championship team. Dynamic criteria allow adding the criteria needed for coaches and managers. Coaches and managers also can refine taekwondo by adding the required criteria to the agreed additional criteria. The result of this paper is application can give the decision of athletes who deserve to enter the match team. To facilitate managers and coaches in screening the best athletes. The validation test results obtained 85% compatibility between the selection results in the application and manual calculations.

KEGIATAN PENDAMPINGAN PENERAPAN TIK PADA NEXT GEN’S PARTY KOI SHOW KE 2 Budi Suyanto; Mangaras Y F; Wilis Kaswidjanti; Dessyanto Boedi P; Nur Heri Cahyana
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 3 No. 2 (2023): Juli : Jurnal Informatika dan Teknologi Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v3i2.1377

Inspection and implementation of ICT in competition management at Next Gen's Party Koi Show #2. Training with two-way interaction methods, presentations and exercises on how to use the activity registration application and back office application to manage activity participants and provide support on activity days. Next Gen's Party Koi Show #2 Online Registration Application Install Next Gen's Party Koi Show #2 Back Office Online Application Install Next Gen's Party Koi Show #2 Participant Registration Support Activities Next Gen Support Committee Party Koi Show #2 activities in Participant management.

Transformasi Digital pada UMKM Luthfi Handcraft: Meningkatkan Daya Saing dan Branding Produk Melalui Pemasaran Digital Nur Heri Cahyana; Oliver Samuel Simanjuntak; Yudhy Widya Kusumo; Yenni Sri Utami; Agung Prabowo
IKRA-ITH ABDIMAS Vol. 9 No. 3 (2025): Jurnal IKRAITH-ABDIMAS Vol 9 No 3 November 2025
Publisher : Universitas Persada Indonesia YAI

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

Program Kemitraan Masyarakat (PKM) ini bertujuan untuk mengoptimalkan pemanfaatan kecerdasan buatan (Artificial Intelligence/AI) dalam mempercepat transformasi digital dan meningkatkan daya saing global pada UMKM Luthfi Handcraft di Desa Murtigading, Kabupaten Bantul. Permasalahan utama mitra meliputi rendahnya kualitas visual produk, lemahnya manajemen digital, dan belum optimalnya strategi pemasaran berbasis teknologi. Metode pelaksanaan dilakukan melalui lima tahapan, yakni sosialisasi, pelatihan, penerapan teknologi, pendampingan, dan evaluasi. Hasil kegiatan menunjukkan peningkatan signifikan dalam literasi digital mitra, kemampuan memproduksi konten visual profesional menggunakan AI, penyusunan SOP produksi, serta penguatan strategi digital marketing di marketplace dan media sosial. Program ini memberikan dampak positif berupa peningkatan kapasitas teknologi, kemandirian manajerial, dan perluasan jangkauan pasar. Kegiatan ini sejalan dengan tujuan Sustainable Development Goals (SDGs), sekaligus mendukung pengembangan UMKM berbasis teknologi yang berdaya saing global.

KEGIATAN PENDAMPINGAN PENERAPAN TIK PADA NEXT GEN’S PARTY KOI SHOW KE 2 Budi Suyanto; Mangaras Y F; Wilis Kaswidjanti; Dessyanto Boedi P; Nur Heri Cahyana
Jurnal Informatika Dan Tekonologi Komputer (JITEK) Vol. 3 No. 2 (2023): Juli : Jurnal Informatika dan Teknologi Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jitek.v3i2.1377

Inspection and implementation of ICT in competition management at Next Gen's Party Koi Show #2. Training with two-way interaction methods, presentations and exercises on how to use the activity registration application and back office application to manage activity participants and provide support on activity days. Next Gen's Party Koi Show #2 Online Registration Application Install Next Gen's Party Koi Show #2 Back Office Online Application Install Next Gen's Party Koi Show #2 Participant Registration Support Activities Next Gen Support Committee Party Koi Show #2 activities in Participant management.

EfficientNet B0 Feature Extraction with L2-SVM Classification for Robust Facial Expression Recognition Ahmad Taufiq Akbar; Shoffan Saifullah; Hari Prapcoyo; Heru Rustamadji; Nur Heri Cahyana
Journal of Information System and Informatics Vol 7 No 2 (2025): June
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v7i2.1071

Facial expression recognition (FER) remains a challenging task due to the subtle visual variations between emotional categories and the constraints of small, controlled datasets. Traditional deep learning approaches often require extensive training, large-scale datasets, and data augmentation to achieve robust generalization. To overcome these limitations, this paper proposes a hybrid FER framework that combines EfficientNet B0 as a deep feature extractor with an L2-regularized Support Vector Machine (L2-SVM) classifier. The model is designed to operate effectively on limited data without the need for end-to-end fine-tuning or augmentation, offering a lightweight and efficient solution for resource-constrained environments. Experimental results on the JAFFE and CK+ benchmark datasets demonstrate the proposed method’s strong performance, achieving up to 100% accuracy across various hold-out splits (90:10, 80:20, 70:30) and 99.8% accuracy under 5-fold cross-validation. Evaluation metrics including precision, recall, and F1-score consistently exceeded 95% across all emotion classes. Confusion matrix analysis revealed perfect classification of high-intensity emotions such as Happiness and Surprise, while minor misclassifications occurred in more ambiguous expressions like Fear and Sadness. These results validate the model’s generalization ability, efficiency, and suitability for real-time FER tasks. Future work will extend the framework to in-the-wild datasets and incorporate model explainability techniques to improve interpretability in practical deployment Keywords: Facial Expression Recognition, EfficientNet, SVM, Deep Features, Emotion Classification

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