Software Engineer & AI Enthusiast
Building Intelligent Systems & Scalable Web Solutions
I am a Software Engineer experienced in building enterprise applications using ASP.NET Core and Spring Boot, with a strong focus on scalable and efficient backend architecture.
A software engineer focused on backend development and machine learning — always learning and building solutions that create real impact.
I am a Software Engineer experienced in building enterprise applications using ASP.NET Core and Spring Boot, with a strong focus on scalable and efficient backend architecture.
I also have a deep passion for Artificial Intelligence and Data Science particularly machine learning for text analysis and predictive modeling. My research covers a comparative study of Naive Bayes and Random Forest algorithms for hoax content classification on social media.
I believe great technology is technology that solves real problems with elegant, high-performance solutions.
Focus Areas
Location
Indonesia
Current Role
Software Engineer
Specialization
Software Engineering & AI
Experience
5+ Years Professional
Tools and technologies I use to build scalable, intelligent products.
Categories
6 technologies
All Technologies
My career journey building impactful technology solutions.
2 positions · Currently employed
Technologies
Technologies
A collection of projects reflecting my engineering and research capabilities.
A text classification system leveraging Natural Language Processing (NLP) to analyze and predict whether news content is hoax or non-hoax. The research benchmarks two major machine learning algorithms to determine the best-performing model.
An Entity Management System that centralizes subsidiary data management and provides consolidated reporting, enabling better visibility, governance, and decision-making across the entire organization.
A Project Management Portal that centralizes project planning, tracking, and approval workflows, enabling teams to manage project data efficiently and ensure timely decision-making.
ERP application for managing sample requests, stock requests, and delivery orders in a centralized workflow.
Warehouse Management System with dashboard reporting, barcode-based inventory tracking, stock transfers, and inbound/outbound transactions.
Centralized platform for subsidiary management and enterprise-wide reporting.
Project Management Portal for managing project data, workflows, and approval processes.
Research contributing to the advancement of knowledge in AI and Machine Learning.
Abstract
This research analyzes and compares the performance of two machine learning algorithms — Naive Bayes and Random Forest — in classifying hoax and non-hoax news content circulating on social media. Using an Indonesian-language news dataset, the study evaluates accuracy, precision, recall, and F1-Score for both algorithms.
To compare the effectiveness of Naive Bayes and Random Forest algorithms in classifying hoax news content, with the goal of identifying the more optimal algorithm for detecting misinformation on social media.
The study employs a supervised learning approach with the following pipeline: dataset collection, text preprocessing (tokenization, stopword removal, stemming), TF-IDF feature extraction, model training, and performance evaluation using confusion matrix and cross-validation.
The dataset consists of Indonesian-language news articles collected from various social media platforms and fact-checking websites, comprising over 1,000 labeled news samples (hoax / non-hoax).
Random Forest demonstrated superior performance compared to Naive Bayes across all evaluation metrics, achieving 96% accuracy versus 91%. This indicates that ensemble methods are more effective at handling text feature complexity for hoax classification on social media.
Accuracy metrics for all evaluated algorithms
Random Forest achieved the highest accuracy of 96%, outperforming Naive Bayes in all evaluation metrics.
By The Numbers
Numbers that represent my professional journey so far.
Professional experience in software engineering
Web and AI projects successfully delivered
Published machine learning research paper
Technologies and frameworks proficiently used
Interested in collaborating, discussing opportunities, or just want to say hello? I'd love to hear from you.
I'm currently open to full-time positions, freelance, and consulting opportunities.