ML Competition Platform (ARISE)
Kaggle-style ML competition platform for BINUS students — self-hosted on a $5 VPS.
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portfolio
Interactive Teaching Tools
Visual, interactive tools that make abstract ML concepts click: the backpropagation teaching tool and its 4-beat story.
Build Diary
An automated public log of what I ship, committed truthfully week by week.
Course Quiz Portals
Weekly quiz portals for ML courses: practice-mode, NIM-gated submissions with instant feedback.
publications
Illness Prediction from Oral Symptoms Using Machine Learning with Small Dataset
Published in Undergraduate thesis, Universitas Katolik Soegijapranata, Semarang, 2022
Undergraduate thesis on predicting illness from oral symptoms using machine learning with small datasets.
Recommended citation: Tarigan, G. A. (2022). "Illness Prediction from Oral Symptoms Using Machine Learning with Small Dataset." Undergraduate thesis, Universitas Katolik Soegijapranata, Semarang.
Enhancing node classification: Integrating particle swarm optimization with graph convolutional networks
Published in 2024 International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA), IEEE, pp. 1239-1243, 2024
Particle swarm optimization integrated with graph convolutional networks to improve node classification performance.
Recommended citation: Nasari, M., Pradana, R. C., Tarigan, G. A., Masaling, N. A. P., & Tedjasulaksana, J. J. (2024). "Enhancing node classification: Integrating particle swarm optimization with graph convolutional networks." 2024 International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA), pp. 1239-1243.
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Parallelization of LSTM-GRU Architectures for Multivariate Prediction of Stock Prices
Published in 2024 International Conference on Information Management and Technology (ICIMTech), IEEE, pp. 311-315, 2024
Hybrid LSTM-GRU architectures, parallelized for multivariate stock price prediction and benchmarked against transformer-based comparators.
Recommended citation: Tarigan, G. A., Hermawan, E. S., & Girsang, A. S. (2024). "Parallelization of LSTM-GRU Architectures for Multivariate Prediction of Stock Prices." 2024 International Conference on Information Management and Technology (ICIMTech), pp. 311-315.
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Ablation study: Calibrated adaptive learning ensemble methodology
Published in Procedia Computer Science, 269, 993-1001, 2025
An ablation study of the Calibrated Adaptive Learning Ensemble Methodology (CALEM).
Recommended citation: Perdana, G. A., Wijaya, I. I., Fahreza, K. A., & Tarigan, G. A. (2025). "Ablation study: Calibrated adaptive learning ensemble methodology." Procedia Computer Science, 269, 993-1001.
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Indonesian Food Detection with YOLO and Calorie Estimation Using Lightweight LLMs
Published in 2025 8th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), IEEE, pp. 784-789, 2025
Indonesian food detection with YOLO combined with calorie estimation using lightweight large language models.
Recommended citation: Nasari, M., Tarigan, G. A., Masaling, N. A. P., Joddy, S., & Minor, K. A. (2025). "Indonesian Food Detection with YOLO and Calorie Estimation Using Lightweight LLMs." 2025 8th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), pp. 784-789.
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InterQ: a Job Interview Training Platform Using Facial Expression Detection and Answer Scoring
Published in 2025 8th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), IEEE, pp. 841-846, 2025
A job interview training platform using facial expression detection and automated answer scoring.
Recommended citation: Boer, Y., Permatasari, A. C., Kevin, K., Tarigan, G. A., & Suhartono, D. (2025). "InterQ: a Job Interview Training Platform Using Facial Expression Detection and Answer Scoring." 2025 8th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), pp. 841-846.
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Lighter student engagement recognition in a classroom environment using skeletal keypoints
Published in IAENG International Journal of Computer Science, 52(6), 1997, 2025
A lightweight computer vision approach to student engagement recognition in classrooms, based on skeletal keypoints.
Recommended citation: Tarigan, G. A., Elwirehardja, G. N., Nugroho, K. S., & Pardamean, B. (2025). "Lighter student engagement recognition in a classroom environment using skeletal keypoints." IAENG International Journal of Computer Science, 52(6), 1997.
Analyzing Indonesian political hoax detection system on social media using deep learning and natural language processing
Published in Procedia Computer Science, 269, 1742-1751, 2025
Deep learning and NLP methods for detecting political hoaxes on Indonesian social media.
Recommended citation: Prastyapradipta, B., Naoko, K., Himawan, R. A. B., Ibrahim, M. A., & Tarigan, G. A. (2025). "Analyzing Indonesian political hoax detection system on social media using deep learning and natural language processing." Procedia Computer Science, 269, 1742-1751.
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Computer Vision-Based Pose Estimation for Student Engagement Detection: Trends and Challenges
Published in 2025 7th International Conference on Cybernetics and Intelligent System (ICORIS), IEEE, pp. 1-5, 2025
A review of computer vision-based pose estimation approaches for student engagement detection, covering trends and open challenges.
Recommended citation: Tarigan, G. A., Elwirehardja, G. N., Nugroho, K. S., & Pardamean, B. (2025). "Computer Vision-Based Pose Estimation for Student Engagement Detection: Trends and Challenges." 2025 7th International Conference on Cybernetics and Intelligent System (ICORIS), pp. 1-5.
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Product sales recommendation system using item-based collaborative and content-based filtering
Published in Procedia Computer Science, 269, 1643-1653, 2025
A hybrid product sales recommendation system combining item-based collaborative filtering and content-based filtering.
Recommended citation: Harun, J., Yulianto, D., Andrywinata, C., Hermawan, E. S., Pranoto, H., et al. (2025). "Product sales recommendation system using item-based collaborative and content-based filtering." Procedia Computer Science, 269, 1643-1653.
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Skeletal keypoint-based pipeline as a computer vision-based approaches
Published in Communications in Mathematical Biology and Neuroscience, 2026, 2026
A skeletal keypoint-based computer vision pipeline for human behavior analysis, applied to classroom engagement.
Recommended citation: Tarigan, G. A., Nugroho, K. S., & Pardamean, B. (2026). "Skeletal keypoint-based pipeline as a computer vision-based approaches." Communications in Mathematical Biology and Neuroscience, 2026.
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Fake Review Detection on E-Commerce Platforms Using a Hybrid Anomaly Detection Approach: Combining Autoencoder and Isolation Forest
Published in Research Square (preprint), 2026
A hybrid anomaly detection approach combining autoencoders and Isolation Forest to detect fake reviews on e-commerce platforms.
Recommended citation: Laychi, S., Karuntu, S. P. A., Sihombing, D. H., Sutoyo, R., & Tarigan, G. A. (2026). "Fake Review Detection on E-Commerce Platforms Using a Hybrid Anomaly Detection Approach: Combining Autoencoder and Isolation Forest." Research Square (preprint).
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talks
teaching
Machine Learning (COMP6577001)
Undergraduate course, BINUS University, Computer Science program, 2024
Foundations of machine learning: supervised and unsupervised methods, from data analysis and regression to clustering and dimensionality reduction.
Artificial Intelligence Solution (COMP6986001)
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
How AI creates measurable business value: strategy, data readiness, ethics, and leading AI-driven initiatives.
Applied Computer Vision (COMP6966001)
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
Computer vision with PyTorch: from neural network fundamentals to CNNs, object detection, segmentation, and generative vision.
Applied Natural Language Processing (COMP6965001)
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
LLM-centric NLP: language models, tokens and embeddings, transformers, prompt engineering, retrieval-augmented generation, and fine-tuning.
Deep Learning Foundations (AI3DL001)
Undergraduate course, BINUS University, Artificial Intelligence Program (Semester 3), 2026
Theoretical and probabilistic foundations of deep learning: probability, distributions, neural architectures, and generative models.
First Year Program
Workshop series, BINUS University, 2026
Preparation workshops for final year project students: algorithms, C programming, Python and machine learning, and computational thinking.
Internet of Things and Robotics (COMP6967001)
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
From sensors and ESP32 to cloud platforms and edge AI: building end-to-end intelligent IoT ecosystems.
Machine Learning Operations (COMP6984001)
Graduate course, BINUS University, 2026
Building and operating ML systems end-to-end: experimentation, model serving, monitoring, and production discipline.
Research Methodology
Course, BINUS University, 2026
Guiding research methodology: research group formation, proposal development, and weekly progress tracking.
Signal Processing (COMP6987001)
Undergraduate course, BINUS University, Artificial Intelligence Program, 2026
Digital signal processing in Python: acquisition, filtering, spectral and time-frequency analysis, and machine learning for signal data.