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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Norazhar Abu Bakar
Universiti Teknikal Malaysia Melaka (UTeM)
Computer Science & IT Electrical & Electronics Engineering Engineering

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A smart traffic light using a microcontroller based on the fuzzy logic Desmira Desmira; Mustofa Abi Hamid; Norazhar Abu Bakar; Muhammad Nurtanto; Sunardi Sunardi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i3.pp809-818

Abstract

Traffic jam that is resulted from the buildup of vehicles on the road has become an important problem, which leads to an interference with drivers. The impacts it has on cost and time effectiveness may take the form of increased fuel consumption, traffic emissions, and noise. This paper offers a solution by creating a smart traffic light using a fuzzy-logic-based microcontroller for a greater adaptability of the traffic light to the dynamics of the vehicles that are to cross the intersection. The ATMega2560 microcontroller-based smart traffic light is designed to create a breakthrough in the breakdown of congestions at road junctions, thereby optimizing the real-time happenings in the road. Ultrasonic, infrared, and light sensors are used in this smart traffic light, resulting in the smart traffic light’s effectiveness in parsing jams. The four sets of sensors that are placed in four sections determine the traffic light timing process. When the length of vehicle queue reaches the sensor, a signal is sent as the microcontroller’s digital input. Ultrasonic and infrared sensors can reduce congestions at traffic lights by giving a green light time when one or all of the sensors are active so that the vehicle congestions can be relieved.
Comparison of principal component analysis and ANFIS to improve EEVE Laboratory energy use prediction performance Desmira Desmira; Norazhar Abu Bakar; Romi Wiryadinata; Mustofa Abi Hamid; Nur Kholifah; Muhammad Nurtanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 2: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i2.pp970-979

Abstract

The energy use that is in excess of practicum students’ needs and the disturbed comfort that the practicum students experience when conducting practicums in the Electrical eengineering vocational education (EEVE) laboratory. The main objective in this study was to figure out how to predict and streamline the use of electrical energy in the EEVE laboratory. The model used to achieve this research’s goal was called the adaptive neuro-fuzzy inference system (ANFIS) model, which was coupled with principal component analysis (PCA) feature selection. The use of PCA in data grouping performance aims to improve the performance of the ANFIS model when predicting energy needs in accordance with the standards set by the campus while still taking students’ confidence in conducting practicum activities during campus operating hours into consideration. After some experiments and tests, very good results were obtained in the training: R=1 in training; minimum RMSE=0.011900; epoch of 100 per iteration; and R=0.37522. In conclusion, the ANFIS model coupled with PCA feature selection was excellent at predicting energy needs in the laboratory while the comfort of the students during practicums in the room remained within consideration.
Accelerated thermal aging of Kraft papers impregnated with dielectric liquids Imran Sutan Chairul; Norazhar Abu Bakar; Sharin Ab Ghani; Mohd Shahril Ahmad Khiar; Nor Hidayah Rahim; Syahrun Nizam Md Arshad@Hashim
Bulletin of Electrical Engineering and Informatics Vol 12, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i5.4336

Abstract

Accelerated thermal aging was conducted on Kraft papers impregnated with mineral insulating oil (MO) and palm insulating oil (PO), and the effect of aging time on the oils and Kraft papers was observed. Each sample consisted of insulating oil, dried Kraft paper, and weighed metal catalysts (copper, iron, zinc, and aluminum) in a bottle. Prior to aging, the bottles were left for 24 h at room temperature for impregnation to take place. The thermal aging experiments were carried out at 130 °C for 250, 500, and 750 h. The properties of the MO and PO (moisture content, acidity, and ultraviolet-visible absorption spectra) and the properties of the Kraft papers (tensile strength and colour) were determined. Results showed that the aged PO had higher moisture content compared with the aged MO. However, the Kraft papers impregnated with PO had better tensile strength after 750 h of aging, which may be attributed to the affinity of PO to moisture. This slows down the hydrolytic degradation mechanism. In terms of colour, the Kraft papers were darker than their original colour as the tensile strength decreased. To conclude, the Kraft paper impregnated with PO had higher tensile strength compared with those impregnated with MO.
Co-Authors Desmira Desmira Imran Sutan Chairul Mohd Shahril Ahmad Khiar Muhammad Nurtanto Mustofa Abi Hamid Nor Hidayah Rahim Nur Kholifah romi wiryadinata Sharin Ab Ghani Sunardi Sunardi Syahrun Nizam Md Arshad@Hashim