Article Per Year (5 Year)
p-Index From 2021 - 2026
0.659
P-Index
This Author published in this journals
All Journal Frontiers in Community Service and Empowerment Jurnal Teknokes
Forra Wakidi, Levana
Unknown Affiliation
Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Electrical & Electronics Engineering Engineering Environmental Science Nursing Other

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Empowering Economic Growth in Balongdowo Village, Sidoarjo, East Java: Pioneering a Digital Tourism and Marketing Initiative Triwiyanto, Triwiyanto; Luthfiyah, Sari; Utomo, Bedjo; Forra Wakidi, Levana
Frontiers in Community Service and Empowerment Vol. 3 No. 3 (2024): September
Publisher : Forum Ilmiah Teknologi dan Ilmu Kesehatan (FORITIKES)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ficse.v3i3.76

Abstract

Balongdowo Village, recognized as the largest producer of Kupang in Sidoarjo Regency, has significant potential for economic development through its local seafood products. This community service program aims to enhance the economic sustainability of the village by empowering local businesses and introducing digital marketing strategies. The program focuses on promoting Kupang-based products through e-commerce platforms such as Tokopedia, Shopee, and Bukalapak, expanding market reach beyond the local area. Additionally, the initiative supports the development of a village information system portal to highlight the village’s profile, potential, and services. By integrating digital tools into marketing and village management, the project seeks to transform Balongdowo into a self-sufficient digital village. The program includes training sessions for local business owners and village officials on e-commerce usage, product presentation, and website management. The result is the successful establishment of online shops for local businesses and the launch of the Balongdowo village website, creating new opportunities for economic growth and improved public services.
Design and Implementation of a Low-Cost and Functional Prosthetic Hand Using 3D Printing Technology for a Member of the Association of Physical Disabilities Indonesia Triwiyanto, Triwiyanto; Luthfiyah, Sari; Forra Wakidi, Levana; Utomo, Bedjo
Frontiers in Community Service and Empowerment Vol. 2 No. 3 (2023): September
Publisher : Forum Ilmiah Teknologi dan Ilmu Kesehatan (FORITIKES)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ficse.v2i3.51

Abstract

Many people with physical disabilities, especially transradial amputees, face difficulties in performing daily activities and have low self-esteem due to the lack of affordable and functional prosthetic hands. The aim of this community service program is to apply 3D printing technology in making prosthetic hands for the members of the Indonesian Physical Disability Association (PPDFI) branch in Surabaya. The method consists of four steps: (1) measuring the physical parameters of the amputees, such as the circumference and length of the residual limb, (2) designing and printing the prosthetic hand using 3D software and printer, (3) testing the mechanical and functional performance of the prosthetic hand, such as the ability to open and close, and (4) providing counseling and mentoring to the amputees to restore their confidence and evaluate their usage. Result: The result of this program is the availability of a low-cost and open-source prosthetic hand for the transradial amputees, which can help them to perform basic activities such as driving, holding a phone, and grabbing a bottle. The prosthetic hand can also be customized according to the needs and preferences of the amputees, such as the color or design. Conclusion: The conclusion of this program is that 3D printing technology can be used to create a functional and affordable prosthetic hand for the transradial amputees, which can improve their quality of life and self-esteem. The program also provides education and guidance to the amputees and the community about the benefits and risks of using prosthetic hands.
Embedded Machine Learning on ESP32 for Upper-Limb Exoskeletons Based on EMG Triwiyanto, Triwiyanto; Maghfiroh, Anita Miftahul; Forra Wakidi, Levana; Dita Musvika, Syevana; Utomo, Bedjo; Sumber, Sumber; Caesarendra, Wahyu
Jurnal Teknokes Vol. 18 No. 4 (2025): Desember
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jteknokes.v18i4.134

Abstract

Stroke remains one of the primary causes of long-term disability worldwide and frequently results in persistent impairment of upper limb motor function. To support more effective and intensive rehabilitation, there is a need for wearable devices that can interpret muscle activity and autonomously assist limb movement without relying on an external computer. This study aims to design and implement an upper-limb rehabilitation exoskeleton that is driven by electromyography (EMG) signal classification using machine learning and by real-time elbow angle monitoring, with all models deployed directly on an ESP32 microcontroller. The proposed exoskeleton is built from lightweight, ergonomic 3D-printed components and operates in both unilateral and bilateral modes. Its main contributions include: (1) embedding real-time EMG classification models on the ESP32 so that the device can function independently, (2) integrating EMG-based motor control with elbow angle feedback from an MPU6050 inertial measurement unit, and (3) incorporating a load cell to estimate biceps force during training. EMG signals from the forearm flexor muscles are processed to extract statistical features such as variance (VAR), waveform length (WL), integrated EMG (IEMG), and root mean square (RMS). These features are used to train Random Forest, Decision Tree, Support Vector Machine (SVM), and XGBoost classifiers. The trained models are converted to C code using the micromlgen library for execution on the ESP32. System evaluation involved thirty male participants aged 20–25 years with body weights between 50–85 kg. All tested models achieved 100% accuracy in distinguishing relaxed versus grasping muscle contractions, while the correlation of elbow angles between unilateral and bilateral ESP32 systems reached 0.9469, indicating highly consistent motion detection. The Decision Tree model was selected for deployment due to its superior memory efficiency on the microcontroller. These results demonstrate that the developed ESP32-based exoskeleton provides a practical, efficient, and easily integrable solution for wearable stroke rehabilitation
Co-Authors Anita Miftahul Maghfiroh Dita Musvika, Syevana Luthfiyah, Sari Sumber, Sumber Utomo, Bedjo Wahyu Caesarendra