Data Analyst - Business AnalystData Analyst - Business AnalystData Analyst - Business AnalystData Analyst - Business Analyst
Data Scientist - Machine Learning EngineerData Scientist - Machine Learning EngineerData Scientist - Machine Learning EngineerData Scientist - Machine Learning Engineer
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Python

Python

Advanced
R

R

Advanced
Google Sheets

Google Sheets

Advanced
Excel

Excel

Advanced
Tableau

Tableau

Advanced
Looker Studio

Looker Studio

Advanced
SQL

SQL

Intermediate
HTML

HTML

Beginner
C/C++

C/C++

Beginner
Java

Java

Beginner
CSS

CSS

Beginner
Power BI

Power BI

Intermediate

Business Intelligence

Business Intelligence

Algoritma Data Science School

2023

Full Stack Data Science

Full Stack Data Science

Algoritma Data Science School

2022

Publication Author

Publication Author

ICCSCI

2023

Publication Author

Publication Author

ICICoS

2024

Customer Lifetime Value Prediction image 1

    • Customer Lifetime Value Prediction

    Developed machine learning models using both Random Forest and Deep Learning (MLP) to predict Customer Lifetime Value (CLV), specifically tailored for a Car Insurance Company. The solution was deployed via Streamlit to enable real-time insights for marketing and customer retention teams, helping the company make data-driven decisions on customer segmentation and value forecasting.

    Machine LearningPythonStreamlitCanvaDeep Learning
    Airbnb Analysis image 1

    • Airbnb Analysis

    Conducted an in-depth analysis of 5,790 properties without reviews to uncover key factors influencing listing activation rates. Designed and developed an interactive dashboard using Tableau to visualize insights, enabling stakeholders to identify property characteristics that impact activation and optimize listing strategies accordingly.

    Data AnalysisPythonTableauCanva
    Optimizing Concrete Strength Prediction (IEEE ICICoS) image 1

    • Optimizing Concrete Strength Prediction (IEEE ICICoS)

    Published research at IEEE ICICoS on optimizing concrete strength prediction using Random Forest with hyperparameter tuning (Random Search) in R, achieving MAE < 4 and R² > 90%, improving mix design accuracy and construction quality.

    Machine LearningRRandom Forest
    Polarity Prediction and Sentiment Analysis in IKN-related Posts image 1

    • Polarity Prediction and Sentiment Analysis in IKN-related Posts

    Conducted sentiment analysis on social media posts related to IKN (Ibu Kota Nusantara) on platform X (formerly Twitter), incorporating buzzer/bot identification to enhance data reliability. Leveraged a hybrid approach combining Convolutional Neural Networks (CNN) and Latent Dirichlet Allocation (LDA) to accurately predict text polarity scores and extract topic clusters. The analysis provided deeper insights into public discourse, engagement patterns, and the presence of coordinated opinion shaping behavior around the new capital development initiative.

    Machine LearningPythonSentiment AnalysisCanvaDeep Learning

    FAQ

    Frequently Asked Questions

    • What is your educational background?
    • What tools and platforms are you experienced with?
    • Where did you go to high school and junior high school?
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    • Have you completed any major projects?
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