Hi, my name is
Fakhridanish Mirza
Priyoyuwono
I'm a student at SMA Negeri 1 Waru exploring how engineering and data science can create real impact. I've built projects such as an machine-learning-based non-invasive glucometer and a IoT attendance tracker, with focus on improving accessibility and comfort through technology.
PROJECTS
A collection of my recent work, blending code, design,
and hardware built to solve real-world problems.
Multi-Analysis Medical Device
- Developed a child-friendly device integrating non-invasive glucose monitoring and cuffless blood pressure measurement using machine learning algorithms.
- Addresses Indonesia's high prevalence of diabetes and hypertension: WHO 2019 reports 51.3 million Indonesians affected by hypertension (2nd in ASEAN) (WHO 2019), IDF reports 73.7% of diabetes cases go undiagnosed (IDF), and Handayani et al., 2019 shows 76.3% of hypertension cases are undiagnosed (Handayani et al., 2019).
- Aims to improve early detection and management, preventing Intrauterine Growth Restriction (IUGR) and Small for Gestational Age (SGA) outcomes in children, early indicators of stunting.
Non-Invasive Glucometer with Machine Learning
- Created a non-invasive glucometer for children and pregnant women, integrating machine learning for accurate monitoring without needles.
- Addresses fear of needles among children, high undiagnosed diabetes rates, and limited access to pediatric endocrinologists (PB PERKENI), (2025 study), (2023 study).
- Monitoring maternal blood pressure and glucose reduces risks of IUGR and SGA, mitigating early stunting, especially in high-risk pregnancy environments.
RFID-Based Presence System for SMA Negeri 1 Waru
- Smart attendance tracking solution using RFID scanning.
- Streamlines recording of student attendance and assists teachers and student leaders in managing logs.
- Identifies behavioral trends and improves classroom discipline efficiently.
ACHIEVEMENTS
A few highlights of awards and recognitions I'tve received along my project journey.
BEPRO - Biomedical Engineering Annual Contest
1st Place & Favorite Award | 2025
Organizer: Institut Teknologi Sepuluh Nopember (FTEIC, BME)
Project: Multi-Analysis Medical Device
Awarded 1st place for developing a child-friendly medical device integrating non-invasive glucose monitoring and cuffless blood pressure measurement with machine learning. The device addresses Indonesia's high prevalence of diabetes and hypertension and targets early detection to prevent IUGR and SGA outcomes (Handayani et al., 2019), (WHO 2019), (IDF).
Biomedical Engineering Annual Contest - Bepro
2nd Place | 2024
Organizer: Institut Teknologi Sepuluh Nopember (FTEIC, BME)
Project: Non-Invasive Glucometer with Machine Learning
Recognized for creating a non-invasive glucometer that reduces fear of needles, addresses high undiagnosed diabetes rates, and supports early maternal health interventions to prevent IUGR and SGA outcomes (PB PERKENI), (2025 study), (2023 study).
Inspire - KRPY X UGM
3rd Place | 2024
Organizer: Taman Pintar Yogyakarta & Universitas Gajah Mada
Project: Non-Invasive Glucometer with Machine Learning
Placed 3rd for designing a system predicting stunting risk in infants by analyzing maternal glucose and blood pressure metrics, facilitating early intervention for high-risk pregnancies (PB PERKENI), (2025 study).
BEPRO - Biomedical Engineering Annual Contest
Favourite Champion | 2025
Organizer: Institut Teknologi Sepuluh Nopember (FTEIC, BME)
Project: Multi-Analysis Medical Device
Recognized as favourite champion for the innovative device combining non-invasive glucose and cuffless blood pressure monitoring, leveraging machine learning to improve pediatric health management (Handayani et al., 2019), (IDF).
Biomedical Engineering Annual Contest - Bepro
Favourite Champion | 2024
Organizer: Institut Teknologi Sepuluh Nopember (FTEIC, BME)
Project: Non-Invasive Glucometer with Machine Learning
Acknowledged for a project improving maternal and infant health by monitoring blood pressure and glucose without needles, supporting early detection and intervention to reduce stunting risks (PB PERKENI), (2023 study).
Deployed IoT Attendance System
SMA Negeri 1 Waru | 2025
Organizer: Actively used by students and teachers
Project: RFID-Based Presence System
Developed a practical IoT solution to automate attendance using RFID technology, simplifying management of classroom presence.