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All Journal Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Info-Teknik JTERA (Jurnal Teknologi Rekayasa) AL-JAZARI JURNAL ILMIAH TEKNIK MESIN Jurnal Teknik Sipil Unika Soegijapranata : G-SMART (Geoteknik, Struktur, Manajemen Konstruksi, Sumber Daya Air, Transfortasi) Jurnal Manajerial International Journal of Applied Technology Research JITEL (Jurnal Ilmiah Telekomunikasi, Elektronika, dan Listrik Tenaga) Industrial Research Workshop and National Seminar Jurnal Pengabdian Teknik dan Ilmu Komputer (PETIK) International Journal of Engineering Continuity El-Mujtama: Jurnal Pengabdian Masyarakat Jurnal Sains Sistem Informasi
Budi Setiadi, Budi
Teknik Informatika, Universitas Islam Kalimantan MAAB, Banjarmasin
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Journal : International Journal of Engineering Continuity

 1 
A Fuzzy-Based Spatial Condition Detection System Using Square Area Mapping to Support The Mobility of Individuals with Visual Impairments Supriyadi, Tata; Solihin, Ridwan; Habinuddin, Endang; Sudrajat, Sudrajat; Utomo, TB; Setiadi, Budi; Nugraha, Ramdhan
International Journal of Engineering Continuity Vol. 4 No. 1 (2025): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v4i1.395

Abstract

This research developed, designed, and implemented a cane prototype with the ability to identify spatial conditions, which can help the mobility of blind people in the form of decision information on choosing a path that is free from obstacles. The electronic space sensing system uses ultrasonic-type non-contact/non-visual sensors. Ultrasonic sensors are installed at three points: left, front, and right (L, F, R) of the stick. When the stick swings left-right or vice versa, each sensor will produce an array of distance data and then average it. The average distance of each point is calculated by the Left Side Square Area (LSSA) and Right Side Square Area (RSSA). The LSSA and RSSA values ​​are used as fuzzy input, a fuzzy inference process is carried out using a rule base, and defuzzification is used for decision output on the microcontroller. The system translates the decision results into sound (beep) and vibration information for the user. The results of the second experiment with blind people in two different scenarios show that the system can be an effective support during mobility in the hall and is a feasible prototype for training blind people with new O&M techniques towards the use of travel aids.
A Hybrid Neural Network and Sugeno-Type Fuzzy Approach for Object Classification to Assist Navigation of Visually Impaired Individuals Using Ultrasonic Sensor Arrays Solihin, Ridwan; Hasanah, Rahmawati; Setiadi, Budi; Supriyadi, Tata; Sudrajat, Sudrajat; Tri Hartono, R Wahyu
International Journal of Engineering Continuity Vol. 4 No. 2 (2025): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v4i2.416

Abstract

This study proposes a hybrid neural network that integrates a multilayer perceptron (MLP) with optimised Sugeno-type fuzzy reasoning for object classification. The system employs a vertically mounted array of ultrasonic sensors arranged 10 cm apart at heights ranging from 80 cm to 180 cm. Each sensor measures the distance of passing objects, producing eleven readings that capture vertical distance patterns. These readings are processed by an MLP with a single hidden layer of 22 neurones to identify characteristic spatial signatures. A refined similarity-based classification is then performed using an optimised Sugeno-type fuzzy inference system configured with five linguistic variables: Very Low (VL), Low (L), Medium (M), High (H), and Very High (VH). Training and testing were conducted using datasets collected at SLBN-A Citeureup, Cimahi, comprising two object categories: human (visually impaired individuals) and nonhuman (inanimate objects). The model was trained for 100 epochs with a learning rate of 0.001. Experimental results show accuracy exceeding 90%, with the hybrid model outperforming the conventional MLP by 1.83%. This improvement reduces false positives and prevents erroneous obstacle warnings. The integration of fuzzy reasoning also enhances the system's robustness to uncertainty and stabilises decision-making when class boundaries overlap.  
Co-Authors Ashshidiqi, Hasbi Auliya Rahman Ayuliani, Indah Baisrum, Baisrum Bambang Lareno, Bambang Binarto, Agus Budi Utomo, Heri Dwi Retno Sari, Dwi Retno Dwi Retnosari Habinuddin, Endang Hasanah, Rahmawati Ilman, Sofyan M. IRPAN IRPAN, IRPAN Julhijah, Zenita Amalia khuzaini, Khuzaini Maria Wahyuni Meliana Meliana Messara, Hugo Muin, Agus Alim Nugroho, Hertog Octavia, Angelica Nenaputri Perkasa, Febry Candra Prasetyo Prasetyo Putri, Fahira Anindya Ramadhani, Nissa Azahra Ramdani, Gilang Ramdhan Nugraha Ridwan Solihin Rizqullah, Naufal Robi, Robi Setyaningtyas, Novi Ayu Siswoyo Siswoyo Sofian Yahya, Sofian Sudrajat Sudrajat Sunarto Sunarto Supriyadi, Tata Supriyanto Supriyanto Toto Tohir Tri Hartono, R Wahyu Utomo, T. B. Utomo, TB Weny, Niken Anjar Widianto, David Yudi Prana Hikmat