I am a fresh graduate of Informatics Engineering from Institut Teknologi Adhi Tama Surabaya, specializing in data analysis and web development. With a strong technical foundation and hands-on experience, I have worked on various web development projects, leveraging frameworks such as Laravel, Tailwind, and Bootstrap to build intuitive and user-friendly applications.
During my academic journey, I actively contributed as a web developer in both academic and community service projects, focusing on creating impactful digital solutions. My role as a laboratory and teaching assistant for Structured Programming and Data Structures enhanced my ability to guide others while solidifying my expertise in programming concepts. Additionally, I developed leadership and financial management skills as the treasurer of the Programming Language Laboratory.
I also expanded my data analysis proficiency through the MIKTI MSIB Batch 6 program, where I honed my skills in data processing, visualization, and insights generation, preparing me for a competitive career in the tech industry.
Now, as I embark on my professional journey, I am eager to apply my skills in data-driven decision-making, software development, and AI-driven solutions, while continuously learning and growing in the field of technology and innovation.
Institution | Status | Details |
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Contract | Coding Teacher [July 2025 - Present] | |
Freelance |
Trainer
[June 2025 - Present]
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Freelance | Writer [November 2024 - Present] | |
Part-time |
Laboratory Assistant
[September 2022 - August 2024]
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Part-time |
Laboratory Assistant - Treasurer
[September 2023 - August 2024]
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Internships:
Institution | Details |
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Associate Data Scientist Professional [May 2025 - Present] | |
Machine Learning Intern [March 2025 - April 2025] | |
Web Developer
[March 2024 - February 2025]
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Independent Study - Kampus Merdeka [February 2024 - June 2024] | |
Junior Web Developer [April 2023 - May 2023] |
Formal Education:
Institutions | Program Details |
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Bachelor of Computer Engineering, Informatics Engineering [September 2021 - February 2025]
Graduated from Bachelor of Computer Science by Institut Teknologi Adhi Tama Surabaya, an Informatics Engineering Learning Program, with a focus on programming, data analysis, and software engineering. Participated in practical labs, assistantships, seminars, internships, community service, and thesis research. Proficient in C++, Python, Laravel, SQL, Machine Learning, and various tools like Figma, Tableau, GitHub, and TensorFlow. Ready to contribute to the field of technology and data analytics. |
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High School Graduate in Natural Sciences [July 2017 - July 2020]
Graduated from SMAN 15 Surabaya, majoring in Mathematics and Natural Sciences (MIPA/MIA). Actively engaged in both academic and extracurricular activities, including teaching and learning programs, practical exams, and various student organizations. Participated in Paskibra, Scout (Pramuka), and the English Learning Club (ELC). Contributed to the Islamic Spiritual Section (Sie Kerohanian Islam/SKI), organizing and taking part in events such as Maulid Nabi, Pondok Ramadhan, religious trainings (Diklat), Banjari music, Islamic music band, and Istighasah. Also involved in Karate and school-wide events, demonstrating discipline, teamwork, and leadership. |
Non-Formal Education:
📁 Project | 🗓️ Date | 💻 Tech | 🔗 Link |
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DigiTalent Fundamental Data Science - Self-Practice Project Description: This project comprises a collection of structured self-practice exercises aimed at reinforcing foundational concepts in data science as outlined in the DigiTalent training program. It systematically addresses key areas including data acquisition, exploratory data analysis, data cleansing, and data annotation. The exercises utilize real-world datasets and industry-standard tools to provide comprehensive hands-on experience, supporting the development of practical skills essential for data science proficiency. |
June 2025 - June 2025 | Python, Pandas, Requests, Beautifulsoup4, Seaborn, Matplotlib, Jupyter Notebook, Scikit-Learn | 🔗 GitHub |
Submission - Our Story App Submission (2025) Description: OurStoryApp is a Single Page Application (SPA) web app developed to fulfill the submission requirements for the Learn Intermediate Web Development course from Dicoding. This application allows users to share stories through photos, descriptions, and locations. It integrates with the Dicoding Story API, uses Leaflet.js for maps, Web Notification API, and is optimized to meet WCAG accessibility standards. |
April 2025 - June 2025 | HTML, CSS, Javascript, Webpack, Vite, API, Microsoft Visual Studio Code |
🔗 GitHub 🌐 Live Demo |
Machine Learning Task Implementation - Codveda Internship Description: As part of the internship program at Codveda Technologies, I worked on various Machine Learning tasks divided into three levels: Basic, Intermediate, and Advanced. Each level involves implementing ML algorithms using Python and libraries such as Scikit-Learn, TensorFlow, Keras, and Matplotlib. 💡 Highlights:
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March 2025 - April 2025 | Python, Pandas, Scikit-Learn, OS, Plotly, NumPy, Matplotlib, Seaborn, Mplcursors, Scipy, Mlxtend, Datetime, Imblearn, TensorFlow/Keras, Microsoft Visual Studio Code | 🔗 GitHub |
Submission - Final Assessment Submission (2024) Description: This project is submission for the Dicoding course about "Belajar Dasar Pemrograman JavaScript (Learn Basic JavaScript Programming)". |
September 2024 - October 2024 | JavaScript, Microsoft Visual Studio Code | 🔗 GitHub |
Submission - Web Book Collection Submission (2024) Description: This project is submission for the Dicoding course about "Belajar Dasar Pemrograman Web (Learn Basic Web Programming)". The Web Book Collection allows users to see book collection. |
September 2024 - October 2024 | HTML, CSS, Javascript, Microsoft Visual Studio Code |
🔗 GitHub 🌐 Live Demo |
Submission - BookShelf App Submission (2024) Description: This project is submission for the Dicoding course about "Belajar Membuat Front-End Web untuk Pemula". The Bookshelf App allows users to add, remove, search, and list books, demonstrating fundamental front-end web development skills. |
September 2024 - September 2024 | HTML, CSS, Javascript, Microsoft Visual Studio Code |
🔗 GitHub 🌐 Live Demo |
Analisis Sentimen Perbandingan Brand Laptop Menggunakan Metode Random Forest Description: This project aims to classify user sentiment toward various laptop brands based on YouTube comments. Data is collected through web scraping and processed using tokenization, filtering, stemming, and transformed using TF-IDF. A Random Forest model is employed for sentiment classification, evaluated using a Confusion Matrix and K-Fold Cross-Validation. The model achieves over 92% accuracy, with the majority of comments being positive. However, data imbalance slightly affects the detection of negative sentiments. This project offers valuable insights for laptop manufacturers to better understand user opinions and improve marketing strategies and product quality through sentiment analysis. |
August 2024 - February 2025 | HTML, CSS, Laravel, Bootstrap, Tailwind CSS, Microsoft Visual Studio Code |
🔗 GitHub 📄 Journal |
Rancang Bangun Sistem Informasi Penelitian dan Pengabdian kepada Masyarakat ITATS Menggunakan Model Prototyping Description: The Research and Community Service Information System website at ITATS is designed to streamline the management of activities within the Research and Community Service Institute (LPPM). Built using the prototyping model, this platform allows students and lecturers to submit research and community service proposals online, simplifying the review and evaluation process. Additionally, the website offers access to schedules, guidelines, and important announcements related to LPPM activities. The primary goal of this system is to enhance efficiency, transparency, and accountability in managing LPPM programs, while also making it easier for students and lecturers to engage with and follow the offered programs. |
August 2024 - February 2025 | HTML, CSS, Laravel, Bootstrap, Tailwind CSS, Microsoft Visual Studio Code |
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MySkill Short Class Task Monthly Description: Enrolled in a multidisciplinary training program covering various fields of expertise, such as Human Resources, Digital Marketing, English & Postgraduate Scholarship Preparation, Product & Project Management, Microsoft Excel, Finance & Accounting, Software Engineering, Graphic Design, Sales & Business Development, Data Analysis, and UI/UX Research & Design. |
May 2024 - March 2025 | Powerpoint, Excel, Figma, Python, Jupyter Notebook, Canva, Microsoft Visual Studio Code, HTML, CSS, Javascript | 📂 GDrive |
Rancang Bangun Sistem Informasi Manajemen Penilaian Pondok Pesantren Ribath Daruttauhid Ta'lim-Tahfidh Description: Community Service Program / Field Work (KKN) building a website for report card assessment management at Pondok Pesantren Ribath Daruttauhid (Ta'lim-Tahfidh). |
May 2024 - July 2024 | HTML, CSS, Bootstrap, Laravel, Microsoft Visual Studio Code |
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Rancang Bangun Sistem Informasi Profil Perusahaan Pondok Pesantren Ribath Daruttauhid Ta'lim-Tahfidh Description: Community Service Program / Field Work (KKN) building a website for company profiles at Pondok Pesantren Ribath Daruttauhid (Ta'lim-Tahfidh). |
May 2024 - July 2024 | Wordpress |
🌍 Website |
Rancang Bangun Sistem Informasi Manajemen Pengumpulan Dokumen Skripsi Mahasiswa dengan Menggunakan Model Waterfall Description: As part of my Practical Work (KP), I developed a Thesis Document Management Information System for the Informatics Engineering Study Program at Adhi Tama Institute of Technology (ITATS). This system is designed to streamline the collection and management of graduation data, as well as thesis documents, improving the efficiency of the administrative process. Built using the Waterfall model, the system follows a structured development approach, ensuring clear and systematic progress from requirement analysis to implementation. The primary goal of this system is to enhance administrative efficiency, simplify thesis document collection, and provide faster and more accurate access to graduation data for both students and administrative staff. |
March 2024 - July 2024 | HTML, CSS, Laravel, Bootstrap, Tailwind CSS, Microsoft Visual Studio Code | 📄 Proceeding |
Analysis of Flight Delays and Airline Performance (Capstone Project) - MIKTI Independent Study Batch 6 Program - Capstone Project Description: Case Study will be shown Troubleshooting Flight Delays and Airline related Case analysis with Python Programming on Google Collaboratory and visualized using Bar Chart, Line Chart, and Scatter Plot. |
May 2024 - June 2024 | Google Colaboratory, Jupyter Notebook, Powerpoint |
🖥️ Presentation 📊 Tableau |
Impact Analysis Covid-19 (Case Study Project) - MIKTI Independent Study Batch 6 Program - Case Study Project Description: Case Study will be shown Troubleshooting COVID-19 related Case analysis with Python Programming on Google Collaboratory and visualized using line chart and line chart interactive. |
May 2024 - May 2024 | Google Colaboratory, Jupyter Notebook, Powerpoint | 🖥️ Presentation |
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Banner Titles Introduction to Programming for Beginners with Python
A beginner-friendly introduction to programming using Python. Learn core concepts like variables, data types, conditional logic, and functions. Includes a simple interactive mini-project and quiz.
Scraping Book Data from “Books to Scrape” with Python Using BeautifulSoup: Advanced Version (V2)
This tutorial covers how to scrape book data and images from the "Books to Scrape" website using Python & BeautifulSoup. Learn the Advanced of web scraping techniques and automate data extraction.
Scraping Book Data from “Books to Scrape” with Python Using BeautifulSoup: Basic Version (V1)
This tutorial covers how to scrape book data from the "Books to Scrape" website using Python & BeautifulSoup. Learn the basics of web scraping techniques and automate data extraction.
Cloud-Based Python Notebook: How to Use Google Colab with Free GPU/TPU Access
This article explains how to utilize Google Colab for cloud-based Python notebooks, offering free access to powerful GPU/TPU resources for better performance and productivity.
Want to read more articles? Visit my Medium page for more publications!
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Proceedings
Publications Titles SEMTIK (Seminar Implementasi Teknologi Informasi dan Komunikasi)
22 Agustus 2024Rancang Bangun Sistem Informasi Manajemen Pengumpulan Dokumen Skripsi Mahasiswa dengan Menggunakan Model Waterfall
Makalah ini menyajikan pengembangan Sistem Informasi Manajemen untuk pengumpulan dokumen skripsi mahasiswa menggunakan model Waterfall. Sistem ini bertujuan untuk memperlancar proses manajemen dan pengorganisasian pengajuan skripsi mahasiswa, memastikan penyimpanan dan pengambilan dokumen yang efisien. Model Waterfall dipilih karena pendekatannya yang terstruktur, yang memungkinkan pengembangan sistematis dan dokumentasi yang jelas di setiap tahap. Proses pengembangan meliputi analisis kebutuhan, desain sistem, implementasi, pengujian, dan pemeliharaan. Keefektifan sistem dievaluasi melalui pengujian black-box, mencapai tingkat keberhasilan rata-rata sebesar 89%. Hal ini menunjukkan bahwa sistem memenuhi persyaratan fungsional dan berfungsi sesuai yang diharapkan. Selain itu, sistem ini juga mendapat umpan balik positif dari pengguna akhir, yang menyatakan bahwa sistem ini mudah digunakan dan sangat membantu dalam manajemen dokumen skripsi. Hasil penelitian menunjukkan bahwa sistem yang diimplementasikan dapat secara signifikan meningkatkan manajemen dokumen skripsi, menyediakan solusi yang andal dan ramah pengguna bagi institusi akademik. Pengembangan lebih lanjut dapat mencakup penambahan fitur tambahan seperti integrasi dengan sistem informasi akademik lainnya dan peningkatan keamanan data. Studi ini menunjukkan potensi metodologi pengembangan sistem terstruktur seperti Waterfall dalam menciptakan sistem manajemen yang efektif dan efisien untuk institusi pendidikan.
SNESTIK (Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika)
25 April 2025Klasifikasi Bangunan secara Otomatis Menggunakan Pembelajaran Mendalam dari Gambar Street-View (DOI: 10.31284/p.snestik.2025.6874)
Urban population density mapping or urban utility planning requires a classification map based on individual buildings that are considered much more informative. The goal of this research is to determine how to extract the fine-grained boundaries of individual buildings from a street-view dataset. This paper proposes a general framework for classifying individual building functionality using a deep learning approach. The proposed method is based on a Convolutional Neural Network (CNN) that classifies facade structures from street view images, such as Street-View images. From the experiments conducted, the CNN classifier with the ResNet architecture was able to classify the Street-View data group with an accuracy value of 86.79%. We construct a dataset to train and evaluate the CNN classifier. Furthermore, the method is applied to generate a building classification map at the urban area scale.
If the DOI is not accessible, use this alternative link .JournalsPublications Titles JITET (Jurnal Teknik Informatika dan Teknik Elektro Terapan)
7 Agustus 2024Sistem Deteksi Penyakit Pada Otak dengan Pendekatan Klasifikasi CNN dan Preprocessing Image Generator (DOI: 10.23960/jitet.v12i3.4371)
In today's digital era, artificial intelligence technology has become an important part of various human activities, including in the healthcare sector. One of its focal points is the detection of brain diseases, which have significant implications for health and medical expenses. This study addresses the issue of accuracy in brain disease detection through the utilization of Convolutional Neural Network (CNN) methodology and preprocessing Image Generator. Previous research suggests that CNN with preprocessing Image Generator has the potential to enhance detection accuracy. The research employs the Computed Tomography (CT) of the Brain dataset from Kaggle, comprising 259 data points categorized into three classes: aneurysm, tumor, and cancer. Experimental findings indicate that the CNN method with preprocessing Image Generator yields higher accuracy in both training and testing phases, with reduced complexity. In conclusion, this method holds promise for more effective detection of brain diseases.
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