Fresh Graduate from Institut Teknologi Sepuluh Nopember in Mathematics, certified as a Data Scientist Associate, with additional certifications and independent study experience that strengthen my expertise in data science and machine learning. Highly motivated to apply analytical and data-driven decision-making skills in a dynamic professional environment. Fast learner with a passion for continuous learning, growing, and contributing to a forward-thinking team in the industry.
Python
JavaScript
PHP
MySQL
Java
HTML
CSS
Mathematics and Computer Science
2020 - 2024
Mathematics and Natural Science
2017 - 2020
Data Analytics and Software Engineering
Feb 2024 - Jun 2024
Mathematics and Computer Science
2020 - 2024
Mathematics and Natural Science
2017 - 2020
Data Analytics and Software Engineering
Feb 2024 - Jun 2024
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This project is my thesis that implements a model for image captioning specifically designed to identify and describe traffic violations. The main goal is to assist in the automatic detection and description of traffic violations recorded by CCTV cameras. The model is built using the X-Linear Attention Networks (X-LAN) architecture, which excels in generating descriptive captions by effectively exploiting high-level interactions between visual and textual features.
This project demonstrates face detection using Haar Cascade classifiers with OpenCV. The provided script utilizes pre-trained Haar Cascade models to detect faces in images.
This repository contains a comprehensive analysis of power consumption data for the city of Delhi, India. The analysis involves data preprocessing, time series decomposition, and modeling using ARIMA and SARIMA models.
This project involves a comprehensive data analytics process, focusing on vending machine sales data from four distinct locations in Central New Jersey, USA, covering the period from January 1 to December 31, 2022. The project progresses through dataset preparation, data cleaning, in-depth analysis, and visualization, culminating in the creation of a final dashboard website. The analysis aims to address specific business problems derived from the sales data, providing actionable insights for optimizing vending machine operations.
This project involves building a machine learning model using Support Vector Machines (SVM) to detect smoke based on various environmental and chemical sensor readings. The dataset used for this project contains attributes like temperature, humidity, volatile organic compounds, and particulate matter, which can indicate the presence of smoke.
This project performs an exploratory data analysis (EDA) on a dataset from the Google Play Store. The goal of this project is to analyze the Google Play Store dataset to uncover insights related to app categories, ratings, user reviews, and other key features. Through this analysis, we aim to understand patterns and trends that may provide value to developers, marketers, or data enthusiasts.
A web-based application designed to streamline the parking process by providing real-time information on parking availability and allowing users to reserve parking spots. The system offers a user-friendly interface for viewing available spaces and managing reservations.