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All Journal International Journal of Electrical and Computer Engineering Mechatronics, Electrical Power, and Vehicular Technology Jurnal Otomasi Kontrol dan Instrumentasi
Salim, Taufik Ibnu
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Privacy-preserving reservation model for public facilities based on public Blockchain Basuki, Akbari Indra; Rosiyadi, Didi; Susanto, Hadi; Setiawan, Iwan; Salim, Taufik Ibnu
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4418-4429

Abstract

Ensuring fairness in the utilization of government-funded public facilities, such as co-working spaces, sports fields, and meeting rooms, is imperative to accommodate all citizens. However, meeting these requirements poses a significant challenge due to the high costs associated with maintaining digital infrastructure, employee wages, and cybersecurity expenses. Fortunately, Blockchain smart contracts present an economical and secure solution for managing digital infrastructure. They offer a pay-per-transaction schema, immutable transaction records, and role-based data updates. Despite these advantages, public blockchains raise concerns about data privacy since records are publicly readable. To address this issue, this study proposes a privacy-preserving mechanism for public facilities' reservation systems. The approach involves encrypting the reservation table with fully-homomorphic encryption (FHE). By employing FHE with binary masking and polynomial evaluation, the reservation table can be updated without decrypting the data. Consequently, citizens can discreetly book facilities without revealing their identities and eliminating the risk of overlapping schedules. The proposed system allows anyone to verify reservations without disclosing requested data and table contents. Moreover, the system operates autonomously without the need for human administration, ensuring enhanced user privacy.
Electric wheelchair navigation based on hand gestures prediction using the k-Nearest Neighbor method Anam, Khairul; Nahela, Safri; Sasono, Muchamad Arif Hana; Rizal, Naufal Ainur; Putra, Aviq Nurdiansyah; Wahono, Bambang; Putrasari, Yanuandri; Wardana, Muhammad Khristamto Aditya; Salim, Taufik Ibnu
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 16, No 1 (2025)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2025.1229

Abstract

The advancement of technology in the medical field has led to innovations in assistive devices, including wheelchairs, to enhance the mobility and independence of individuals with disabilities. This study investigates the use of electromyography (EMG) signals from hand muscles to control a wheelchair using the k-Nearest Neighbor (kNN) classification method. kNN is a classification algorithm that identifies objects based on the proximity of similar objects in the feature space. The wheelchair control process begins with the development of a kNN model trained on EMG signal data collected from five respondents over 30 seconds. The data was processed using feature extraction techniques, namely Mean Absolute Value (MAV) and Root Mean Square (RMS), to identify motion characteristics corresponding to five types of movement: forward, backward, right, left, and stop. The extracted features were classified using the kNN algorithm implemented on a Raspberry Pi 3. The classification results were then used to control the wheelchair through an Arduino UNO microcontroller connected to a BTS7960 motor driver. The study achieved an average accuracy of 96% with the MAV feature and ? = 3. Furthermore, combining MAV and RMS features significantly improved classification accuracy. The highest accuracy was obtained using the combination of MAV and RMS features with ? = 3, demonstrating the effectiveness of feature selection and parameter tuning in enhancing the system's performance.
Simulasi Kontrol Penjejak Lintasan pada Traktor Roda Dua untuk Lintasan Multi Segmen Salim, Taufik Ibnu; Putri, Yurixa Sakhinatul; Widyotriatmo, Augie
Jurnal Otomasi Kontrol dan Instrumentasi Vol 12 No 1 (2020): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2020.12.1.5

Abstract

AbstrakSebagian besar mata pencaharian penduduk Indonesia adalah petani. Pada umumnya petani di Indonesia masih menggunakan traktor roda dua atau traktor tangan untuk mengolah lahan pertanian. Hadirnya mesin otonom khususnya traktor roda dua menjadi solusi dalam meningkatkan produktivitas pertanian. Traktor otonom roda dua memerlukan keakuratan menyetir dalam mengolah lahan pertanian agar dapat mengikuti lintasan.Tujuan penelitian adalah untuk mensimulasikan pengontrolan penjejak lintasan pada traktor roda dua dengan sinyal kontrol kecepatan (v) dan kecepatan sudut(ω). Parameter kontrol dicari dengan melakukan tuning terhadap parameter gain kontrol kecepatan (Kv), gain kontrol kecepatan sudut (Kω)dan jarak titik pusat ke referensi (b). Penelitian ini juga mengajukan metode untuk membuat lintasan traktor multisegmen secara otomatis berdasarkan masukan data panjang dan lebar lahan pertanian serta jarak atau interval setiap alur. Hasil tuningmemberikan nilai IAE (integral absolute error) minimal 9,7971 dengan nilai parameterb = 0,1, Kv = 10 dan Kω = 10.Penerapan nilai parameter pada simulasi multi segmen menunjukkan hasiltrayectori tracking yang cukup baik yaitu tercapainya errorkeseluruhan yang cukup kecil. 
Co-Authors Anam, M. Khairul Bambang Wahono Basuki, Akbari Indra Hadi Susanto Iwan Setiawan Nahela, Safri Putra, Aviq Nurdiansyah Putri, Yurixa Sakhinatul Rizal, Naufal Ainur Rosiyadi, Didi Sasono, Muchamad Arif Hana Wardana, Muhammad Khristamto Aditya Widyotriatmo, Augie Yanuandri Putrasari