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Hisyam Fadhila Rahman

Electronics Engineering student focused on control systems, robotics, instrumentation, embedded systems, computer vision, and IoT monitoring.

ROLE
ELECTRONICS ENG.
FOCUS
ROBOTICS · CONTROL
BASE
YOGYAKARTA, ID
Hisyam Fadhila Rahman professional headshot
0.00
Cumulative GPA
#0
KRTI 2024 Rank
0+
Engineering Projects
01About

About Me

I am a D4 Electronics Engineering student at Universitas Negeri Yogyakarta with interests in control systems, robotics, and instrumentation. I have experience integrating sensors, developing embedded systems, and implementing computer vision and IoT-based monitoring systems across technical projects. I am also active in Robotika UNY, contributing to national robotics competitions such as KRTI through mechanical design, fabrication, assembly, and hardware-software integration.

Control Systems

Robotics

Instrumentation

Computer Vision

02Education

Education

Universitas Negeri Yogyakarta

D4 Electronics Engineering (2023-Present)

GPA: 3.82 / 4.0 (Semester 5)
Universitas Negeri Yogyakarta logo

SMA Negeri 1 Karangmojo

Natural Sciences Major

Major: Science
SMA Negeri 1 Karangmojo logo
03Skills

Technical Skills

Programming

PythonC/C++

Computer Vision

OpenCVYOLO

Embedded & Automation

ArduinoESP32ROS2ProteusFactory I/OCX-Programmer
04Projects

Selected Projects

KRTI 2024 UAV aircraft preview
KRTIUAVMechanical Division

KRTI UAV Technology Development

Contributed to Robotika UNY's mechanical team for the KRTI Technology Development division by designing and developing UAV mechanical structures, selecting materials and components, carrying out precise fabrication and assembly, and collaborating with electronics and programming teams for system integration. The team achieved 4th place at KRTI 2024 in Yogyakarta.

Music Genre Classification upload interface preview
CNNEfficientNetB2MFCC

Music Genre Classification with EfficientNetB2

Built a music genre classification system using a CNN EfficientNetB2 model, extracted audio features with MFCC preprocessing, trained on more than 1,000 audio samples across 10 genres, and achieved 89% validation accuracy.

Self-Balancing Robot with Fuzzy Logic and Kalman Filter preview
Fuzzy LogicKalman FilterControl Systems

Self-Balancing Robot with Fuzzy Logic and Kalman Filter

Developed an adaptive control system using Fuzzy Logic and PID, implemented a Kalman Filter to improve IMU sensor accuracy, reduced sensor noise, and tested stability under multiple robot motion conditions.

05Certificates

Certificates

06Contact

Let's Connect

I'm currently looking for new opportunities and collaborations. Whether you have a question or just want to say hi, I'll try my best to get back to you!