Informatics student building full-stack web & mobile applications and applying artificial intelligence to real data. I've shipped a role-based POS system, classified Indonesian coins from raw images, and trained an SVM to read public sentiment from social media text.
I'm an Informatics Engineering student at Universitas Surabaya (UBAYA) with hands-on experience building web and mobile applications, designing relational databases, integrating third-party APIs, and implementing machine learning models in Python.
My work sits at the intersection of full-stack development and applied AI: on one side, PHP, Laravel, Angular, and Ionic for shipping usable software; on the other, Scikit-learn, TensorFlow, and OpenCV for turning raw data into working classifiers — from public sentiment on social media to coin recognition from images.
What I care about most is the full path from problem to result — collecting the right data, preprocessing it properly, choosing a model that fits, and being able to explain why it worked (or didn't) with actual evaluation numbers, not just a demo.
Grouped the way the work actually gets divided — building products, building for mobile, and building models.
Each card opens a short case study: the problem, the approach, the tech, and what came out of it.
A full NLP research pipeline measuring public sentiment toward OpenClaw from social media posts — crawling, preprocessing, VADER labeling, TF-IDF features, and SVM classification, evaluated with accuracy, precision, recall, and F1-score.
Classifies Rp100, Rp200, Rp500, and Rp1,000 coins from images using a custom preprocessing pipeline and a comparison of KNN, SVM, ANN, and CNN classifiers.
Mostly project-based so far — academic work, independent research, and self-directed builds rather than a formal employment history.
Looking for an internship or junior developer, and open to project-based work too. Feel free to reach out — I usually reply within a day or two.