Hi I'am

Marcel Kurniawan

a/an CS Student

I’m currently an undergraduate student at BINUS University majoring in Computer Science. Third-year students who are enthusiast in Data Science field and Software Quality Assurance especially in automation.



About Me

I'm Marcel, and I'm currently a third-year student at BINUS University, where I'm majoring in Computer Science. My passion lies in the world of data and its numerous facets, including Data Engineering (DE), Data Analysis (DA), Data Science (DS), Machine Learning (ML), Artificial Intelligence (AI), and Business Intelligence (BI).

Moreover, I have a keen interest in Software Quality Assurance and Automation Testing. It's fascinating to me how these areas contribute to the development of robust and reliable software systems. I enjoy exploring and learning about the best practices in testing and automation to ensure software quality and efficiency.

Education


SYNRGY Academy

Software Quality Assurance

2023 - Present

BINUS University

Computer and Data Science

GPA: 3.85/4

2021 - Present


Organization Experience


GDSC BINUS Bandung

Data Science Core Team

2023 - Present

Bina Nusantara Computer Club

Learning and Training Staff

2022 - Present

HIMTI Binus University

Creative and Design

2021 - Present

Publication

An Evaluation of the Effectiveness of OpenAI's ChatGPT for Automated Python Program Bug Fixing using QuixBugs | IEEE · Sep 16, 2023


Presented at iSemantic Conference 2023 held by UDINUS.
In recent years, the use of Artificial Intelligence (AI) has become increasingly common in various fields, including in software development. One such field is where AI can automatically detect and fix bugs in code. GPT-3.5 is a state-of-the-art language model developed by OpenAI that has been trained on a massive amount of text data to generate natural language responses to a wide range of prompts. One of the main challenges in software development is bug fixing, which can be a time- consuming and complicated process. QuixBugs is a framework for evaluating automatic program repair techniques, which can be used to test the effectiveness of GPT-3.5 and similar bug-fixing tools. This paper evaluates the effectiveness of GPT-3.5 in automatically fixing bugs in Python code using QuixBugs. Through testing with 40 different Python bugs, We discovered that GPT-3.5 was able to accurately fix 30 out of 40 bugs cases from QuixBugs benchmark. Compared with other tools like standard program repair and Codex, ChatGPT outperformed them significantly. These findings highlight the potential of ChatGPT as a powerful tool for enhancing code quality and reducing the burden of manual bug fixing.

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My Skills

Languages

Python

SQL

Java

R Programming

Javascript

Tools

Figma

Excel

Premiere Pro

Postman

Tableau

Jira

Trello

GitHub

SAP Analytics Cloud

Knowledge

Machine Learning

Deep Learning

Quality Assurance

Software Testing

Agile Scrum

STLC

Data Science

Data Analysis

Design

UI/UX

Microsoft Office

Test Cases

API Testing

Latest Project

Contact

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