Muhammad Qois Huzyan Octava

I completed my undergraduate studies in Software Engineering Technology at Vocational College UGM  and am currently in the final stage of 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:

LinkedIn

ORCiD

Personal Page

explore my latest works in this site ➣