"Depriving oneself of

Learning

Equates having life without

Breathing"

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About me

A deeply passionate individual in Applied Computational Science and Engineering, Bioinformatics, Data Science & Analytics, Artificial Intelligence, and Automation, and Quantitatively driven problem-solving. With a strong foundation in computational modeling and algorithmic thinking, I am dedicated to leveraging technology to drive innovation and create impactful solutions in interdisciplinary fields.

Specialize in transforming complex data into actionable insights, particularly in the intersection of Biotechnology, Artificial Intelligence, and Quantitative Analysis. My experience includes working with machine learning models, statistical analysis, and automation tools to optimize workflows and enhance decision-making processes.

With a mindset of continuous learning and adaptability, I aim to contribute to cutting-edge innovations that integrate AI-driven solutions in scientific-reasoning research and industry applications.

Resume

SkillS

What I can Utilize

PYTHON

Big Data processing & Intelligent Models Training

ANACONDA

Depedencies & Environments

GOOGLE COLAB

All in One

MY SQL

Reliable Relational Database Solution

SCIKIT LEARN

Train, Test, Triumph.

TENSORFLOW

High-Performance Backend for AI & APIs

BLAST

Rapid Sequence Search & Alignment

RAPIDMINER

Quick Insights from Complex Data

TABLEAU

Data Storytelling

GO

High-Performance Backend for AI & APIs

LARAVEL

Old but Gold

JAVA

Write Once, Run Anywhere

C

Best Starter Pack there is

Projects

Ticketing program using C

System Development to Digitalize the managing ticket sales with features such as Entry Data, Sorting Data, Searching Data, and List of Ticket and Sales using C Programming language, File Processing in CSV as data, and CMD as ouput terminal.


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AR Application for Room Furniture Arrangement

Intuitive AR app built with Unity and ARCore SDK to help users visualize and arrange furniture in real-world spaces. Featuring a simple UI, it allows easy placement, movement, and resizing of high-quality ArtStation assets, enabling users to experiment with layouts effortlessly and enhance their interior design experience.


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Kindergarten Monitoring

A simple web application developed using Laravel and MySQL, designed to streamline the oversight of kindergarten activities and child development. The system features an authorization mechanism that distinguishes three primary user roles: Admin, Teacher, and Student. With its user-friendly interface, the application enhances communication within the school community and supports a transparent and organized learning process.


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Augmented Reality of Historical Relics in the British Museum

An AR application designed to bring historical artifacts to life through immersive digital interaction. Developed using Unity for AR functionality and Blender for 3D asset creation, this project enables users to explore detailed virtual representations of historical relics by scanning markers or using surface tracking.


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Breast Cancer Detection using Logistic Regression

Built breast cancer prediction model using Logistic Regression based on a dataset containing tumor cell characteristics. The model was trained to classify tumors as Benign or Malignant, and then evaluated using Confusion matrix, Cross-validation, and ROC curve. The results show the accuracy obtained, the distribution of correct and incorrect predictions, and the ability of the model to distinguish the classes with the AUC-ROC score, which gives an idea of the effectiveness of the model in breast cancer detection.


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Youtube Scrapper

A NLP Project, Built using YouTube Data API v3, this tool collects comment data, channel statistics, and related video information to provide content creators with valuable insights into how their audience reacts to their work. The project employs mainly NLTK library, retrieved by TextBlob for simple sentiment analysis based on polarity and BERT for a more advanced contextual understanding of user emotions. The data undergoes preprocessing, including the removal of unnecessary elements like hyperlinks and special characters, to ensure accurate sentiment classification. By leveraging both qualitative and quantitative analysis, this tool helps creators refine their content strategy, enhance engagement, and foster stronger connections with their audience.


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HealthMate

A Mobile App designed to help users stay active, connect with like-minded fitness enthusiasts, and achieve their health goals. Built with Kotlin and Base XML, it offers an intuitive interface for tracking workouts, finding training partners, and sharing progress. To enhance user experience, HealthMate features an AI-powered chatbot integrated with API usage from Brainshop.ai, providing instant answers to health and fitness queries. Whether you're looking for workout recommendations, nutritional tips, or motivation, HealthMate is the perfect all-in-one solution for a healthier lifestyle.


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Performance Dashboard

A Data Visualization Project, that transforms workforce data from HRMS, employee surveys, and performance records into interactive visual insights. HR Managers can track employee satisfaction, turnover rates, and skill gaps to enhance workforce planning. Executives (CEO, CTO, CMO, CFO) gain a high-level view of workforce costs, productivity trends, and organizational growth, ensuring HR strategies align with business goals. By integrating multiple data sources and leveraging Tableau’s powerful visualization tools, this dashboard simplifies complex HR data, enabling real-time analysis, predictive insights, and strategic workforce optimization to drive organizational success.


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Stock Price Movement Prediction

Utilizes LSTM, a Deep Learning Neural Networks to forecast NVIDIA stock movements based on historical data and technical indicators like RSI and EMA. The data undergoes preprocessing, scaling, and time-series transformation with 10 & 70-day window. Built, optimized using Adam Algorithm, and trained over 30 epochs. The model predicts future price trends, with results visualized using Matplotlib, offering valuable insights for market analysis and trading strategies.


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Q&A ChatBot

This project designs a QnA chatbot that runs on Google Colab, using LangChain to build a retrieval-augmented generation (RAG) flow while managing the document processing pipeline, while OpenRouter, a flexible gateway to various cutting-edge language models by utilizing its API. The system begins with the data ingestion stage—files are chunked, embedded, and stored in a vector store—then LangChain coordinates how user questions are processed, contextualized against documents, and directed to the selected model via OpenRouter. Which in this case specifically opting a theme about Tableau.


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Contact info

Phone

+62 813 5185 1414

Email

stevensademi88@gmail.com

Address

Surabaya, East Java, Indonesia