Muhammad Qois Huzyan Octava

I completed my undergraduate studies in Software Engineering Technology at Vocational College UGM  and my Master’s degree in Information Engineering at Faculty of Engineering UGM . My academic experience focuses on data-driven technologies, including data mining, machine learning, and data engineering. During my master’s study, I also participated in an academic exchange program at Universiti Malaya, for a data analytics course.  As part of my graduation requirement at UGM, I conducted research related to feature and dataset engineering for AI model development and published the results in an academic paper. The research contributions include:

• Fine-Tuning Whisper for Domain-Specific ASR: Transcribing Indonesian YouTube Content on Local Wisdom in Disaster Mitigation — research on dataset engineering strategies to improve speech recognition performance for domain-specific content.

• Web-based Sentiment Analysis System Using SVM and TF-IDF with Statistical Feature — research on feture engineering strategies to enrich the features of TF-IDF for machine learning based text classification.

During my studies, I was also involved as a teaching and research assistant, supporting practical courses and research activities related to data analysis. When serving as a Teaching Assistant, I was responsible for preparing laboratory environments and facilitating hands-on practical sessions for students. I guided students in applying theoretical concepts through practical exercises, mostly in areas related to machine learning, data mining, and database systems. I also supported students in troubleshooting programming tasks and provided academic assistance during laboratory activities.

Subjects assisted:

• Game Development Lab. Work (2022)

• Artificial Intelligence Lab. Work (2023)

• Data Mining Lab. Work (2024; 2025)

• Distributed Administration and Information Systems Lab. Work (2024)

I was actively involved in several research projects led by Dr.Eng. Ir. Ganjar Alfian, S.T., M.Eng., whose work focuses on data science and its applications in industry. Through these collaborations, I gained valuable experience in conducting applied research, including data preparation, ] analysis, and data modeling. I also learned how to structure and write academic papers, from formulating research problems to presenting findings in a clear and systematic manner. Some of the research projects I contributed to include:

• Utilizing Random Forest with iForest-Based Outlier Detection and SMOTE to Detect Movement and Direction of RFID Tags (2023)

• Perancangan Federated Learning Berbasis Homomorphic Encryption untuk Perangkat Internet of Things (2023)

• Customer Shopping Behavior Analysis Using RFID and Machine Learning Models (2023)

• Web-based E-Commerce Customer Segmentation System Using RFM and K-Means Model (2023)
• Application of the outlier detection method for web-based blood glucose level monitoring system (2024)

Know more about me.. .

This page captures a part of my journey, but my work continues to evolve. To see what I’m currently working on, feel free to explore the platforms below:

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