I am passionate about Artificial Intelligence, Machine Learning, Data Science, and modern web development. With strong problem-solving skills and a deep interest in business and technology, I transform innovative ideas into impactful digital solutions.
A passionate Information Systems graduate who combines technical skills in AI, Machine Learning, Data Science, and Web Development with strong business insight and problem-solving abilities.
Nothing is impossible, as long as we are willing to try and make the most of every opportunity.
I'm a passionate developer with a strong background in Information Systems, focusing on Artificial Intelligence, Machine Learning, Data Science, and modern web development using Laravel. I enjoy solving real-world problems through technology and transforming ideas into meaningful digital solutions that create impact.
Some of My Project Works
An integrated student admission and child development assessment system equipped with early growth-delay detection using a Random Forest model. Designed to streamline administrative workflows while supporting data-driven evaluation for educators.
A mobile-friendly hotel virtual assistant that helps guests book rooms, find directions, and access essential information instantly. The system delivers a smooth conversational experience optimized for real-time guidance and customer support.
A multivariate time series forecasting model designed to predict weather conditions using multiple environmental variables. This project applies advanced deep learning techniques to improve accuracy and short-term prediction reliability.
A deep learning–based time series forecasting model built to predict temperature patterns using historical observations. The system leverages sequence-learning architectures to enhance accuracy and capture temporal dependencies effectively.
An image colorization system that transforms black-and-white photos into realistic color images using OpenCV and deep learning–based colorization models. The pipeline enhances grayscale inputs by predicting rich and natural color tones automatically.
A loan repayment prediction model built using ensemble learning techniques to classify whether applicants are likely to repay their loans. This project explores multiple models—from Decision Trees to Random Forests—to improve accuracy and support data-driven lending decisions.
Selected Publications & Scientific Writings
This system integrates student admission, child development assessment, and early growth delay detection to improve administrative efficiency and enhance the accuracy of child monitoring at TK Marhamah Hasanah 2.
This research builds a Random Forest–based early prediction model using longitudinal child development data, achieving high accuracy in detecting growth delays for practical use in early childhood monitoring.
This study designs a 10-step Knowledge Management Roadmap for PT Oba Bersama Abadi to improve knowledge documentation, employee training, and digital knowledge-sharing processes.
Leadership, Collaboration, & Community Impact
Designed and managed youth and sports programs, led PHBI and Ramadan event planning including team coordination and fundraising, increasing youth participation by 40% and hosting events with 150+ attendees receiving positive feedback.
Identified low youth engagement and established the first official mosque youth organization in the region, developed vision and mission, recruited 20+ members, launched initial programs such as religious studies and social services, boosting youth participation by 50% within 6 months.
I led the creation and implementation of school regulations and student discipline programs, initiated charity activities for orphans and disaster victims, and served on the Public Relations division to seek, establish, and negotiate with sponsors
Professional Roles & Industry Contributions
Conducted research on 10+ potential B2B partners through online surveys and industry databases, prepared contact lists and sales proposals, successfully attracting interest from 2 prospective partners during internship.
Processed 3 years of sales data using Python to identify monthly trends, cleaned and visualized data, and developed Random Forest and Linear Regression models to forecast sales for the next 6 months, enabling more accurate stock adjustment decisions.
Conducted user research via interviews with 10+ distributors, documented feature ideas, assisted in creating initial wireframes, and provided inputs that shaped the core features of the salt ordering app’s first release.
Let’s Connect and Collaborate
liemhartono21@gmail.com
linkedin.com/in/hartono10
@liem.hartono_