Januari 2026

Institut Teknologi Sepuluh Nopember

S1 • Electrical Engineering • IPK 3.34

Februari 2023 - Agustus 2023

PT PLN Indonesia Power • Magang

Activities during internship for 7 months:
● Practiced DCS and PLC systems through job shadowing in maintenance and engineering departments.
● Developed a machine learning-based Decision Support System prototype for coal feeder calibration.
● Developed a sensor data acquisition system from PI Vision to a Python server.
● Created machine learning systems for optimizing power plant operations.

Impact for company:
I have developed a machine learning-based Decision Support System prototype for coal feeder calibration, which is currently being trialed at PLTU Banten 3 Lontar. By implementing this system, the calibration process, previously conducted manually every three months based solely on the operator's intuition and experience, can now rely on this DSS as a more reliable and structured reference tool.

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Agustus 2024

IBM Data Science Professional

IBM • PI9MGVEM0KNJ

Through this IBM Professional Certificate program, I developed and honed hands-on skills in Data Science and Machine Learning. I began by understanding the fundamentals of Data Science and its methodology, explored and utilized various data science tools, and gained proficiency in Python and SQL. I also performed data visualization and analysis and built machine learning models. Throughout the program, I completed multiple labs and assignments on the cloud, culminating in a Capstone Project where I applied and demonstrated my knowledge and skills.

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Agustus 2024

Machine Learning with Python

IBM • W5XDA5TWRP70

Course content:
• Describe the various types of Machine Learning algorithms and when to use them
• Write Python code that implements various classification techniques including K-Nearest neighbors (KNN),
decision trees, and regression trees
• Compare and contrast linear classification methods including multiclass prediction, support vector
machines, and logistic regression.
• Evaluate the results from simple linear, non-linear, and multiple regression on a data set using evaluation
metrics

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Agustus 2024

Data Analysis with Python

IBM • TPT8GW257D55

Course content:
• Develop Python code for cleaning and preparing data for analysis - including handling missing values,
formatting, normalizing, and binning data
• Manipulate data using dataframes, summarize data, understand data distribution, perform correlation and
create data pipelines
• Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such
as Pandas, Numpy and Scipy
• Build and evaluate regression models using machine learning scikit-learn library and use them for
prediction and decision making

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Juli 2024

Databases and SQL for Data Science with Python

IBM • N9CQ9ZC3SVX5

Course content:
• Analyze data within a database using SQL and Python.
• Construct basic to intermediate level SQL queries using DML commands.
• Create a relational database and work with multiple tables using DDL commands.
• Compose more powerful queries with advanced SQL techniques like views, transactions, stored procedures,
and joins.

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