I build production machine learning pipelines and full-stack web applications. Computer Science graduate from Universitas Ahmad Dahlan (3.92 GPA, Magna Cum Laude), focused on turning raw datasets and complex workflows into fast, reliable software.
I completed my Bachelor of Computer Science at Universitas Ahmad Dahlan in 3.5 years with a 3.92 GPA (Magna Cum Laude). My work sits at the intersection of applied machine learning and modern web engineering.
Before joining PT. IDStar Cipta Teknologi as an AI/ML Engineer, I spent over two years teaching programming, database systems, and machine learning labs to more than 100 undergraduate students, while supporting university-wide digital admission operations at PMB UAD.
Universitas Ahmad Dahlan, Yogyakarta
PT. IDStar Cipta Teknologi
Designing, training, and deploying machine learning models and automated data pipelines for enterprise client systems. Responsible for model evaluation, feature engineering, and production API integration.
Admission Committee (PMB) Universitas Ahmad Dahlan
Supported digital enrollment workflows, applicant data verification, and web portal administration during peak university admission cycles.
Informatics Lab, Universitas Ahmad Dahlan
Led weekly practical lab sessions across Basic Programming, Web Programming, Database Systems, and Machine Learning. Guided over 100 students through code reviews, debugging, and project assessments.
Office of International Affairs (OIA) UAD
Coordinated international student mobility programs, academic exchange events, and cross-cultural communication for visiting scholars and partner universities.
Four documented builds spanning full-stack school admission architecture, block-cipher visualization, exploratory data analytics, and convolutional neural networks.
Engineered a responsive web platform with online registration forms, document uploads, real-time admission status tracking, and a role-protected administrator dashboard backed by Supabase PostgreSQL.
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End-to-end digital student admission (PPDB) platform and content management system built with Next.js 15 and Supabase, replacing paper-based registration for parents and teachers.
Deep learning image classification pipeline built with TensorFlow and Keras to categorize tomato ripeness stages from RGB photographs.
Interactive cryptographic workbench that exposes every internal round of 128-bit Advanced Encryption Standard (AES-CBC with PKCS#7 padding) in real time.
Exploratory data analysis pipeline and interactive Streamlit dashboard uncovering how temperature, humidity, season, and commuting hours drive urban bike rental demand.
Grouped by the domains where I write and ship code in production and research environments, without arbitrary percentage bars.
End-to-end model training, computer vision, exploratory data analysis, and statistical modeling.
Primary language for ML pipelines, cryptography, & data processing
Deep learning & CNN computer vision training
Classical machine learning, feature engineering, & evaluation
Data wrangling, time-series aggregation, & statistical cleaning
Interactive analytical dashboards & algorithm visualizers
Component architecture, server-side rendering, responsive layouts, and choreographed GSAP motion.
App Router, server-rendered production web applications
Stateful client components & interactive UI architecture
Strict static typing across frontend and API boundaries
DOM orchestration, GSAP ScrollTrigger motion, & async runtime
Design token systems & responsive multi-breakpoint layouts
Relational database design, authentication, cloud deployment, and version-controlled workflows.
Authentication, Row-Level Security (RLS), & cloud storage
Relational schema design, indexing, & transactional queries
Relational database management & academic lab instruction
Backend runtime, REST API services, & build tooling
Version control, branch workflows, & collaborative code review
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