Braincore.id

Hello everyone! I am very excited to share that I have successfully completed a TabNet analysis project using the Credit Card Fraud Detection dataset. TabNet is a deep learning architecture specifically designed for analyzing tabular data. This architecture processes raw data without requiring preprocessing and trains the model using gradient-based optimization techniques. In this project, I also implemented metaheuristic feature selection methods to enhance the performance and accuracy of the TabNet model. The model output uses binary numbers, namely 0 and 1, to indicate fraud occurrences. The number 0 represents non-fraud, while 1 represents fraud. This binary format makes it easier to identify the number of fraud cases that occur. I would like to express my deepest gratitude to Braincore.id, Kak Ida Sri Afiqah, and my amazing team members Nofita Nur Aini and Akmal Ihab Syauqi for their exceptional support and contributions throughout this project.

[Project Showcase] Introducing Automatic Plate Number Recognition (APNR) – an intelligent system designed to automatically detect and recognize vehicle license plates from images and videos. This system streamlines the process of collecting vehicle data, including plate numbers, regions, and vehicle types, with high accuracy. By leveraging this technology, we aim to replace time-consuming manual processes while supporting efficiency across various sectors, such as transportation, security, and parking management. APNR is built in compliance with official regulations, including proper classification of plate types and regional codes. This project would not have been possible without the hard work and dedication of my incredible team. Huge thanks to everyone who contributed their expertise and effort to make this a success Dian Alhusari, Iksan Wijaya, Patricia Ho, Fachri Rozan, Yosriko Rahmat Karoni Sabelekake, Muhammad Kemal Fasya, Hanif Fadillah Setyadi, Fauzan Ihza Fajar, Eric Julianto, and Dinar Ayu Pratiwi ! #AutomaticLicensePlateRecognition #MachineLearning #ComputerVision #APNR #Automation #SmartTechnology #DataDrivenSolutions #AIApplications #TransportInnovation #DigitalTransformation

[Project Showcase] Introducing Automatic Plate Number Recognition (APNR) – an intelligent system designed to automatically detect and recognize vehicle license plates from images and videos. This system streamlines the process of collecting vehicle data, including plate numbers, regions, and vehicle types, with high accuracy. By leveraging this technology, we aim to replace time-consuming manual processes while supporting efficiency across various sectors, such as transportation, security, and parking management. APNR is built in compliance with official regulations, including proper classification of plate types and regional codes. This project would not have been possible without the hard work and dedication of my incredible team. Huge thanks to everyone who contributed their expertise and effort to make this a success Dian Alhusari, Iksan Wijaya, Patricia Ho, Fachri Rozan, Yosriko Rahmat Karoni Sabelekake, Muhammad Kemal Fasya, Hanif Fadillah Setyadi, Fauzan Ihza Fajar, Eric Julianto, and Dinar Ayu Pratiwi ! #AutomaticLicensePlateRecognition #MachineLearning #ComputerVision #APNR #Automation #SmartTechnology #DataDrivenSolutions #AIApplications #TransportInnovation #DigitalTransformation

🚗💡 The implementation of the APNR project in the parking system.💡🚗 We are excited to showcase our Automated Parking System project—an innovative solution combining IoT, Machine Learning, and seamless integration to enhance parking management. This project was built as part of our internship at Braincore.id, guided by our amazing mentors, Kak Eric Julianto,Kak Dian Alhusari and Kak Fauzan Ihza Fajar. Our team—Muhammad Rafael Setyadin, Iksan Wijaya, and Luthfia Khairunnisa Salma—designed and implemented a miniature automated parking system using: 👉 IoT components (Arduino and servo motors) for gate automation 👉 Machine Learning-APNR (Automatic Plate Number Recognition) for vehicle identification 👉 Midtrans for secure QR-based payment integration 👉 WebSocket for real-time communication between the user and the system 👉 Web-based interfaces for user interaction and system monitoring Key Features: 1️⃣ Automated Entry and Exit: Real-time license plate recognition triggers gate operations, streamlining the parking process. 2️⃣ QR Code Payments: A hassle-free payment process that ensures transparency and efficiency. 3️⃣ Error Handling and Monitoring: Alerts and admin interventions ensure smooth operations even during unexpected errors. 4️⃣ Data-Driven Insights: A web admin panel for analytics, visitor tracking, and reporting. This project builds upon the APNR system that we integrated into our parking system. APNR automatically detects and recognizes vehicle license plates with high accuracy, making it an ideal solution for transportation and parking challenges. We're incredibly proud to share this achievement, complete with a demo video showing the system in action and a presentation detailing our journey. 🎥 📄 View our presentation here: https://lnkd.in/g3yhSmB2 A huge thank you to our mentors and the Braincore.id team for their guidance and support throughout this journey. Let’s continue innovating and shaping the future of technology together! 🌟 #ParkingSystem #IoT #MachineLearning #BraincoreID #Innovation

My Final Project Capstone at Bangkit Academy led by Google, Tokopedia, Gojek, & Traveloka as a Mobile Developer. 🚀 Unveiling DuitOnlen: Enhancing Security with Liveness Detection During my capstone project at Bangkit, I focused on developing DuitOnlen, a dummy application showcasing the implementation of liveness detection to enhance the security of face detection. 🔍 Our DuitOnlen App leverages Machine Learning Model Implementation to verify user authenticity in real-time, even if they are using a mask or a photo, mitigating the risk of fraud and unauthorized access. This involved: ✅ Developing a robust liveness detection model. ✅ Integrating the model into a user-friendly interface. ✅ Conducting rigorous testing to ensure accuracy and reliability. In addition to the technical aspects, this project provided invaluable hands-on experience in: ✅ Computer Vision ✅ Machine Learning I would like to express my sincere gratitude to my teammates: - Ubeid Brimbi Sentiaki as a Machine Learning Developer - Ariel Lembong as a Machine Learning Developer - Muhammad Rizq Ramadhan as a Cloud Computing Developer - Mahadika Nafiz Luqman as a Cloud Computing Developer - Ihsanul Hadi Alghifari as a Mobile Developer I am incredibly grateful for the opportunity to contribute to this innovative project that Braincore.id has provided and the invaluable mentorship received at Bangkit Academy led by Google, Tokopedia, Gojek, & Traveloka and Braincore.id. Special thanks to Kak Eric Julianto (Machine Learning advisor), Kak Abadi Suryo (Mobile Developer advisor), and Kak Inez Lowis (Project Manager advisor) for their guidance and support throughout this project. Link to the full presentation video app: https://lnkd.in/g9xET4xf #Bangkit #CapstoneProject #LivenessDetection #Fintech #Cybersecurity #Innovation

[Project Showcase] Liver fibrosis is a critical condition caused by the accumulation of scar tissue in the liver, often resulting from chronic injury or inflammation. If left unaddressed, fibrosis can progress to cirrhosis, significantly impairing liver function and overall health. Why It Matters Liver fibrosis develops silently in its early stages, making early detection and intervention vital. This condition can arise from various causes, including: - Chronic alcohol consumption - Viral hepatitis (Hepatitis B & C) - Non-Alcoholic Fatty Liver Disease (NAFLD) Key Highlights About Fibrosis: - It progresses through distinct stages, from no fibrosis (F0) to cirrhosis (F4). - Symptoms like fatigue, abdominal discomfort, jaundice, and edema often appear only in advanced stages. - Tools such as blood tests, imaging techniques, and liver biopsies play a crucial role in diagnosis. With advanced technologies like AI, machine learning, and imaging techniques, we have the opportunity to: ✅ Detect fibrosis earlier ✅ Improve diagnostic accuracy ✅ Support healthcare professionals in providing timely and targeted care This aligns perfectly with our recent project to develop an AI-powered Liver Fibrosis Classification System, which aims to make an impactful contribution to this field. By classifying fibrosis into precise stages, it can enhance diagnostic capabilities and pave the way for better patient outcomes. Let’s work together to explore how innovation can transform healthcare! Reach out if you’re interested in collaboration or learning more. #HealthcareInnovation #LiverHealth #ArtificialIntelligence #DeepLearning #MedicalResearch #ProjectShowcase

[Project Showcase] Introducing Braincore’s latest innovation: a Route Optimization application powered by Teaching-Learning-Based Optimization (TLBO) algorithm. This cutting-edge tool is designed to revolutionize logistics and transportation planning by finding the most efficient routes, reducing travel time, and minimizing costs. The application leverages TLBO's intelligent approach to optimize paths, balancing speed and computational efficiency. It supports real-time input and adapts dynamically to changing conditions, making it perfect for urban logistics, delivery services, and beyond. This project addresses a critical need in route planning, where traditional methods often struggle with scalability and adaptability. By integrating advanced optimization techniques, we provide a smarter, faster, and more effective solution for route management. This project would not have been possible without the hard work and dedication of my incredible team. Huge thanks to everyone who contributed their expertise and effort to make this a success: Denis Setiawan, Muhammad Rafael Setyadin, Elisa Bunga Daniar, Muhammad Luqman, and Rhaditya! Check out the results in the attached showcase, demonstrating its performance in real-world scenarios! [https://lnkd.in/gp9vyA6U] #RouteOptimization #TeachingLearningOptimization #SmartSolutions #Innovation #Teamwork

We are thrilled to share the results of our collaborative project Supermarket Sales Analysis Dashboard, conducted by our amazing team: Yusrina Hirzi Nur Izza, Nur Azizah, Zafira Dea Natasari, and Auryn Devi Sagita, during our internship program at Braincore.id. This project focused on analyzing and visualizing key sales data to uncover insights that drive strategic business decisions.  In this project, we developed a comprehensive dashboard that highlights sales performance across various dimensions, including branch contributions, customer segments, product line analysis, and tax distributions. By leveraging advanced data visualization techniques, we also explored correlations between unit prices and purchase quantities to understand customer purchasing behavior. The dashboard serves as a valuable tool for identifying trends, pinpointing areas for improvement, and supporting effective decision-making processes.  You can find a detailed explanation of this project in the link below: https://lnkd.in/gJ7pK2Re Dashboard Link: https://lnkd.in/gm2gB_t5 This project has been a fantastic learning experience, and we are incredibly grateful for the mentorship and guidance provided by Braincore.id, Kak Eric Julianto, and the head of the Data Science and Analytics division, Kak Ida Sri Afiqah. This opportunity has significantly enhanced our skills in data analysis and visualization, and we are excited to apply these insights in future projects.  #SupermarketSalesAnalysis #Braincore #DataVisualization #DataAnalytics #SalesDashboard #BusinessInsights

We are delighted to share the results of our collaborative project, Graph Neural Network (GNN) Relational Dataset, conducted by Yusrina Hirzi Nur Izza, Nur Azizah, Zafira Dea Natasari, and Auryn Devi Sagita, during our internship program at Braincore.id. This project focused on leveraging the power of Graph Neural Networks to analyze relational data, uncovering meaningful patterns and insights.  In this project, we implemented GNN models designed to process graph-structured data, such as social networks or molecular structures, by propagating and combining information across nodes and edges. Using preprocessing techniques to clean and prepare the dataset, we applied clustering methods like KMeans and evaluated them using the Elbow and Silhouette Scores to identify optimal cluster groupings. The results provided clear visualizations of data distribution and cluster characteristics. Through rigorous training, our model achieved an outstanding accuracy of 100%, with cross-validation scores averaging 98%. The consistency between training loss and validation loss across multiple epochs further confirmed the reliability and robustness of our model.  You can find a detailed explanation of this project in the link below: https://lnkd.in/grjUmkMc This project has been a great learning experience, and we are incredibly grateful for the guidance and support from Braincore.id, Kak Eric Julianto, and the head of the Data Science and Analytics division, Kak Ida Sri Afiqah. This experience has been incredibly valuable, deepening our understanding of GNNs and their applications in solving real-world problems. We are ready to apply these skills in future projects and are excited to continue exploring innovative solutions in the future!  #GraphNeuralNetwork #Braincore #DataScience #MachineLearning #RelationalData #Clustering

We are excited to share the results of our internship project at Braincore.id! As a team consisting of Vidi Marpaung, Muhammad Dzaky Nashshar, Zafira Dea Natasari, and Auryn Devi Sagita, we have successfully completed a project on LangChain integration and implementation. In this project, we explored the functionalities of LangChain to build AI applications utilizing powerful tools like Tavily and Groq APIs. LangChain is a versatile framework for AI application development that integrates large language models (LLMs) with external data sources such as databases and APIs. By leveraging Tavily, a search engine for AI agents, and Groq, a platform for computational acceleration, we enhanced the automation and intelligence of our project. Through this experience, we successfully developed a chatbot capable of interacting with users, retrieving up-to-date information from the internet, and managing conversational context efficiently. This hands-on implementation helped us understand the potential of LangChain in streamlining workflows through features like memory handling, multi-agent coordination, and human-in-the-loop automation. You can find a detailed explanation of this project in the PowerPoint presentation below: https://lnkd.in/g_KHJHwV We are deeply grateful for the support from Braincore.id, and the guidance provided by Kak Eric Julianto and Kak Ida Sri Afiqah. Looking forward to contributing even more in the world of AI! #LangChain #AIApplications #Tavily #Groq #BraincoreID