Experience.

Responsible for designing, developing, integrating, and maintaining end-to-end software solutions that streamline business operations, automate workflows, and improve operational efficiency, particularly within the vehicle financing and debt collection industry.

Key Responsibilities & Contributions:

• Designed and developed full-stack web applications and Progressive Web Apps (PWAs), covering system architecture, frontend and backend development, database design, testing, and deployment.

• Built business management systems for vehicle financing operations, including financing records, field agent assignments, document verification, operational monitoring, and reporting.

• Developed and integrated RESTful APIs and third-party services to automate data synchronization and connect internal business systems.

• Implemented WhatsApp Gateway integrations and automated notification workflows to support operational communication and customer service processes.

• Developed AI-powered customer service automation solutions to streamline customer interactions and reduce repetitive manual tasks.

• Built financial and accounting modules, including invoicing, receivables management, transaction journals, general ledgers, and financial reporting.

• Implemented authentication, role-based access control (RBAC), and permission management for enterprise applications.

• Designed and optimized PostgreSQL and MySQL databases to support reliable data processing, operational reporting, and application performance.

• Managed application deployment and backend services using Docker and self-hosted cloud infrastructure.

• Collaborated with stakeholders to translate complex business requirements into practical, maintainable, and scalable technical solutions.

Tech Stack: JavaScript, TypeScript, Python, React.js, Next.js, Node.js, PostgreSQL, MySQL, REST APIs, Webhooks, Docker, Git, and WhatsApp Gateway.

Training Experience

• Completed an intensive Data Science training program focused on Python programming, data analysis, data visualization, and Machine Learning applications.

• Practiced essential data processing techniques, including data cleaning, Exploratory Data Analysis (EDA), and dataset preparation for predictive modeling.

• Studied and applied Machine Learning concepts to identify patterns, generate predictions, and support data-driven decision-making.

• Performed data analysis and visualization to extract meaningful insights and interpret analytical results.

• Worked on a Customer Churn Prediction case study to explore how Machine Learning can help predict customer attrition and support business decision-making.

• Strengthened analytical thinking, problem-solving, and practical skills in applying data-driven approaches to business challenges.

Key Achievements

• Successfully completed the Data Science training program and earned a certification issued by Binar Academy x Komdigi.

• Completed a Customer Churn Prediction case study involving data analysis and Machine Learning concepts.

• Developed practical skills in Python programming, data preprocessing, visualization, and predictive modeling.

Technical Skills: Python, Data Science, Data Analysis, Data Cleaning, Exploratory Data Analysis (EDA), Data Visualization, Machine Learning, Predictive Modeling, and Statistical Analysis.

Job Description

• Designed, developed, and integrated Internet of Things (IoT) solutions for environmental monitoring, agricultural applications, industrial automation, and real-time data acquisition.

• Developed IoT-based NPK Monitoring Systems for measuring and monitoring soil nutrient parameters to support agricultural analysis and data-driven decision-making.

• Designed and developed Early Warning Systems (EWS) using sensors, microcontrollers, and automated alert mechanisms to detect environmental changes and potential hazards.

• Developed Water Monitoring Systems integrating sensors, microcontrollers, backend services, and web-based dashboards for real-time monitoring, data visualization, and remote access.

• Worked on AquaSense, an IoT-based water monitoring solution focused on sensor data acquisition, environmental parameter monitoring, and system integration.

• Developed IoT-based CCTV monitoring systems featuring motion detection and automated Android notifications.

• Integrated hardware and software components, including ESP32/ESP8266 microcontrollers, sensors, communication protocols, APIs, and cloud-based platforms.

• Developed firmware, backend services, and monitoring interfaces to support reliable communication between IoT devices and centralized applications.

• Performed hardware prototyping, sensor integration, system testing, troubleshooting, and performance optimization.

• Collaborated with clients to analyze technical requirements and deliver customized IoT and automation solutions.

Key Achievements

• Successfully developed and contributed to multiple IoT projects, including NPK Monitoring, Early Warning Systems (EWS), Water Monitoring Systems, AquaSense, and motion-detection CCTV solutions.

• Built integrated hardware–software solutions combining sensor technology, embedded programming, data communication, and web-based monitoring.

• Contributed to improved monitoring efficiency by enabling remote access to sensor measurements, automated data collection, and centralized visualization.

• Demonstrated end-to-end engineering capabilities, from hardware prototyping and firmware development to backend integration and monitoring dashboards.

Technical Skills: Internet of Things (IoT), Embedded Systems, ESP32, ESP8266, Arduino, C/C++, Python, Sensor Integration, MQTT, REST APIs, Node.js, Real-Time Monitoring, Data Acquisition, Web Dashboards, and Hardware–Software Integration.