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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science Journal of Engineering and Technological Sciences
Shamsudin, Nur Hazahsha
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering

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The evolution of smart sprayer system for agricultural sector in Malaysia Shamsudin, Nur Hazahsha; Noheng, Norman Koliah Anak; Chachuli, Siti Amaniah Mohd; Selamat, Nur Asmiza; Tawai, Hrithik; Raof, Nurliyana Abdul
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6122-6128

Abstract

This study presents the development of a smart sprayer system featuring a microcontroller, ultrasonic sensors, and a Wi-Fi module for agriculture. This system enables 360° movement capabilities and facilitates the activation and deactivation of the sprayer pump remotely. The system offers remote control functionality through smartphone integration, effectively mitigating the need for direct physical contact with hazardous chemicals during the spraying operation. The results demonstrate the efficient operation of the smart sprayer system. The average spraying efficacy is estimated to be 95%, surpassing that of conventional spraying methods, as evidenced by prior research studies. The system is accessible for remote operation via a user-friendly interface, facilitated by the integrated internet of things (IoT) and microcontroller. As anticipated, it successfully executed 360° movements, obstacle detection, water level indication, and remote control of the sprayer pump.
Hybrid feature selection of microarray prostate cancer diagnostic system Ali, Nursabillilah Mohd; Hanafi, Ainain Nur; Karis, Mohd Safirin; Shamsudin, Nur Hazahsha; Shair, Ezreen Farina; Abdul Aziz, Nor Hidayati
Indonesian Journal of Electrical Engineering and Computer Science Vol 36, No 3: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v36.i3.pp1884-1894

Abstract

DNA microarray prostate cancer diagnosis systems are widely used, and hybrid feature selection methods are applied to select optimal features to address the high dimensionality of the dataset. This work proposes a new hybrid feature selection method, namely the relief-F (RF)-genetic algorithm (GA) with support vector machine (SVM) classification method. The aim is to evaluate the performance of the proposed method in terms of accuracy, computation time, and the number of selected features. The method is implemented using Python in PyCharm and is evaluated on a DNA microarray prostate cancer. The outcome of this work is a performance comparison table for the proposed methods on the dataset. The performance of GA, particle swarm optimization (PSO), and whale optimization algorithm (WOA) is compared in terms of accuracy, computation time, and the number of selected features. Results show that GA has the highest average accuracy (91.17%) compared to PSO (90.52%) and WOA (85.74%). GA outperforms PSO and WOA due to its superior convergence properties and better alignment with complex problems.
Investigation on TiO2/graphene as resistance-based gas sensor for volatile organic compound gases detection Mohd Chachuli, Siti Amaniah; Nor Azmi, Muhammad Haziq; Coban, Omer; Shamsudin, Nur Hazahsha
Indonesian Journal of Electrical Engineering and Computer Science Vol 38, No 2: May 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v38.i2.pp774-782

Abstract

Volatile organic compound (VOC) gases are usually produced from industrial activities. Short-term exposure to VOC gases can cause dizziness, headaches, nausea, and throat irritation. Years to a long time exposure to VOC gases can cause cancer and system damage in the human body. With the growth of gas sensor technology, a resistance-based gas sensor based on various structures of resistance-based gas sensors using Titanium dioxide/graphene (TiO2/graphene) were investigated as a sensing material for detecting volatile organic compound gases, which are acetone and ethanol. The TiO2/graphene gas sensor was deposited on a Kapton film using a screen printing technique. All TiO2/graphene gas sensors were exposed to acetone and ethanol at room operating temperature. The results revealed that the highest response values to acetone and ethanol were produced by T99_G1_2 and T98_G2_1, respectively. It can be concluded that design 1 generated the most consistent response to acetone, while design 2 generated the most consistent response to ethanol.
Real-time Monitoring of Carbon Dioxide with IoT ThingSpeak using TiO2 Thick Film Gas Sensor Chachuli, Siti Amaniah Mohd; Ying, Wong Hui; Shamsudin, Nur Hazahsha; Coban, Omer
Journal of Engineering and Technological Sciences Vol. 56 No. 5 (2024)
Publisher : Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2024.56.5.4

Abstract

Carbon dioxide is a colorless, odorless, and non-flammable gas and is claimed to be the fourth most abundant in the earth's atmosphere. Carbon dioxide emission is mainly generated by human and animal exhalation, decomposition of organic matter, and forest fires. Moreover, human activities in the industrial sector emit high levels of carbon dioxide gas, such as through fossil fuel burning, transportation, and deforestation. It is also an asphyxiant and high exposure to it may lead to health effects in humans such as headaches, breathing difficulty, tiredness, coma, and elevated blood pressure. Therefore, in this paper, a carbon dioxide gas sensor with IoT using TiO2 is proposed to observe varying concentrations of carbon dioxide gas at room temperature. Three similar gas sensors were fabricated via screen-printing technology to compare their performance towards carbon dioxide. The hardware development consisted of an Arduino Uno R3 with ESP 8266 Wi-Fi module, wires, LCD display, red and green LEDs, and a 5V power supply. The ThingSpeak application was integrated with the gas sensor and hardware parts to monitor the carbon dioxide concentration in a real-time system. Gas sensor G1 produced the highest response and highest sensitivity with values of 2.120 and 0.245, respectively.
Co-Authors Abdul Aziz, Nor Hidayati Ali, Nursabillilah Mohd Chachuli, Siti Amaniah Mohd Coban, Omer Hanafi, Ainain Nur Karis, Mohd Safirin Mohd Chachuli, Siti Amaniah Noheng, Norman Koliah Anak Nor Azmi, Muhammad Haziq Raof, Nurliyana Abdul Selamat, Nur Asmiza Shair, Ezreen Farina Tawai, Hrithik Ying, Wong Hui