Syahrul Affandi Saidi
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Syahrul Affandi Saidi
Official Name
Syahrul Affandi, Saidi
Alternative Name
Afandi Saidi, Syahrul
Saidi, S. A.
Affandi Saidi, Syahrul
Main Affiliation
Scopus Author ID
56239489400
Researcher ID
FYT-4472-2022

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  • Publication
    Renewable Energy Driven Exhaust Fan for Use in Laboratory via IOT
    (Institute of Electrical and Electronics Engineers Inc., 2021-01-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Wan Azani Wan Mustafa
    ;
    Akbar M.F.
    ;
    Syahrul Affandi Saidi
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Zol Bahri Razali
    ;
    Osman M.K.
    ;
    Setumin S.
    ;
    Idris M.
    ;
    Mahendran Gunaseakaran
    ;
    Nor Syamina Sharifful Mizam
    This paper discussed on the hardware product of renewable energy driven exhaust fan for use in laboratory via IOT. Ventilation is generally deployed in buildings for maintaining user's safety and health. This renewable energy driven exhaust fan is the most considered system in improving the energy saving while sustaining user's safety and health. If we can renew and reuse the energy we waste, it would help in some way to the problem of scarcity of energy, which is major threat of present world. Initial capital cost of solar systems is still quite high when it comes to generate power for domestic. By using the concept of wind turbines wind-generated electricity can be used for battery charging and for connection with the power grid. Hence this research proposes a prototype of Renewable Energy Driven Exhaust Fan for use in laboratory via IOT. This research presents a prototype of regenerating power by an exhaust fan. The generated power can be either used directly or can be stored in a battery. This exhaust fan also can be controlled and monitored via IOT. The objectives of this research are, to design and develop an exhaust fan that can be driven by renewable energy, to design and develop an exhaust fan that can be controlled by IoT and to collect data and analyze the power consumptions and power saving. Methods used in this research is to use power from battery to operate the Fan 1. Than this kinetic energy produced by Fan 1 is used to drive Fan 2 and Fan 3 which are now actually a pair of generators with the help of charging circuit to directly recharge the battery which at first used to power up Fan 1. Analysis is then carried out to evaluate the theory, which actually agreed to the initial theory as presented
      11  60
  • Publication
    Optimization of the rice bran protein powder yield using spray drying technique in response surface methodology
    ( 2024-03-21)
    Mansor M.R.
    ;
    Mohd Sharizan Md Sarip
    ;
    Ibrahim L.H.
    ;
    Syahrul Affandi Saidi
    In this study rice bran protein were extracted and powdered using spray dryer. The optimization of the process were done using Box-Behkenn response surface design. Process parameter such as temperature (120°C,165°C,210°C), aspirator (52%,66%,80%) feed flow rate (5%,30%,55%) and air flow rate (20%,30%55%) were investigated. The result show that the extraction condition have significant effects on extraction yield of protein the obtained experimental data were fitted to a quadratic equation using multiple regression analysis with high coefficient of determination value of 0.8137.an optimization study using Derringer's desired function methodology was performed and the optimal conditions based on both individual and combinations of all independent variable for yield (temperature is 120˚C, Aspirator is at 80% feed flowrate set to 5% and air flowrate of 42mmhg) and protein (temperature is 120˚C, aspirator were set at 79.9%, feed flowrate set to 31.8% and air flowrate of 51mmhg) were determined with maximum protein yield of 17.29% per 50 gram of raw rice bran (RRB)
      32  1
  • Publication
    Contrast virus microscopy images recognition via k-NN classifiers
    ( 2017-07-02)
    Afiq Ahmad Shakri
    ;
    Syahrul Affandi Saidi
    ;
    Muhammad Naufal Mansor
    ;
    Haryati Jaafar
    ;
    Ahmad Kadri Junoh
    ;
    Wan Azani Wan Mustafa
    One of the topics that are commonly in focus of object detection and image recognition is virus detection. It is well known that to learn and detecting virus proven to be a challenging and quite complex task for computer systems under different noise level. This research work investigates the performances of preprocessing stages with Contrast feature extraction with K-Nearest Neighbor (KNN) classifier under various levels of noise. The real time experiment conducted proved that the proposed method are efficient, robust, and excellent of which it has produced a results accuracy of up to 88% for biological viruses images classification.
      42  2
  • Publication
    Zero-Biasing Split Ring Resonator using Metamaterial Element for High Gain Superstrates Ultra-Wideband Antenna
    ( 2023-03-01)
    Othman N.A.
    ;
    Mohd Aminudin Jamlos
    ;
    Wan Azani Wan Mustafa
    ;
    Jamlos M.F.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Syahrul Affandi Saidi
    ;
    Mirza H.
    Complex materials with artificial structures known as metamaterials (MTM) have unique properties that draw several scientists to use them in a variety of research fields. In addition, MTM can go beyond some of the restrictions placed on tools used in technical practise while improving the characteristics of microwaves. The Internet of Things (IoT) application calls for the construction of zero-index Split Ring Resonator (SRR) MTM element superstrates with an ultra-wideband antenna. Keep in mind that the MTM simulates behaviour that is not found in nature, namely the zero-reflection phase (dB) on the resonance frequency. For this project, an antenna with an SRR MTM unit cell operating at 2.70 GHz is built. The SRR has four inductance-related loops (r1, r2, r3, and r4), and gaps (slots) are added to the ring to produce the capacitance effect. Parametric research has been done for the SSR in the interim to identify the best design with zero indexes, permittivity and permeability at the desired frequency. The MTM unit cells array design's 7 x 4 and 10 x 5 dimensions achieved a dB of 0° at the 2.70 GHz frequency range. A 7 x 4 MTM unit cell makes up the first design, MTM Antenna Design 1, which at 2.70 GHz recorded a gain of 5.70 dB and a return loss (S11) of-20.007 dB. The return loss (S11) at a frequency of 2.70 GHz was-19.734 dB in the second design, an MTM antenna consisting of 10 x 5 MTM unit cells, which recorded a gain of 5.66 dB.
      2  17
  • Publication
    Quantitative analysis method for zingiber officinale water extract using high-performance liquid chromatography
    ( 2024-01-01)
    Mohd Sharizan Md Sarip
    ;
    Nik Daud N.M.A.
    ;
    Mohd Zainudin M.A.
    ;
    Ibrahim L.H.
    ;
    Syahrul Affandi Saidi
    ;
    Idham Z.
    ;
    Anuar A.
    Quantitative analysis of the Zingiber Officinale sample using subcritical water extraction (SWE) was developed employing High-Performance Liquid Chromatography (HPLC) to bolster the advancement of this innovative green extraction process. This research focuses on three principal ginger bioactive compounds: 6-gingerol, 6-shagoal, and 10-gingerol. Various stages were undertaken to establish the quantitative analysis method, encompassing the optimisation of HPLC operating conditions and the formulation of standard calibration curves, yielding individual compound equations. A robust correlation within the calibration curve was achieved, exhibiting an r2 value of 0.9814 and an RSD of 5.00%. A simultaneous, swift, and dependable method was established with an injection time of 20 minutes and an 8-minute delay between injections, in contrast to the previous HPLC analysis requiring a 45-minute injection time for detecting and quantifying all components. Notably, no post-treatment was applied after the SWE process. This advancement allows for potential future online measurement of Zingiber Officinale bioactive compounds extracted using subcritical water extraction through this technology.
      27  7
  • Publication
    Gabor Filter and Moment Invariant via LDA Classifier for Skin Cancer Detection
    ( 2020-12-18)
    Mohd Firdaus Omar
    ;
    Muhammad Naufal Mansor
    ;
    Syahrul Affandi Saidi
    Skin cancer may be a serious tumor. This can be clearly seen through the mature, uncommon appearance of fur pathology, which has abnormal properties in complex situations, wrinkled or uncertain perimeters, and dual colors. A small number of tulle melanomas of uncertain diameter can imitate benign moles and cannot be perceived by optical inspection. The only assumption for analyzing them is through dermoscopy as an option. Original identification and medical surgery can alternative for the patients. Within this research a detection method through image processing with various feature extraction such as Gabor filter and Hu Moment were employed and substantially improves the diagnosis performance with 97% via LDA Classifier.
      3  5
  • Publication
    Automotive Mechanical Vehicle Starter
    (IOP Publishing, 2021-12-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Zol Bahri Razali
    ;
    Wan Azani Wan Mustafa
    ;
    Syahrul Affandi Saidi
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Setumin S.
    ;
    Osman M.K.
    ;
    Idris M.
    ;
    Akbar M.F.
    ;
    Muhammad Anas Ahmad Sarbini
    ;
    Nor Syamina Sharifful Mizam
    This research is used to crank start automotive vehicle. There are many different system used in order to start-up vehicles using electric starter, in the time of battery low-power or totally drained. The purpose of this research is to help the driver to get out of this difficulty. Nowadays there are many people that have experienced such a bad moment, where they are stranded at road side due to malfunction starter in their car because of battery problem. Most of the vehicle electric starter failure is because of battery corrosion or battery undercharged. The importance of this research is to solve this problem. Starter is a vital part of the vehicle, without it no automotive vehicles able to operate. These starters will rotate an internal-combustion engine to initiate the engine's operation under its own power. Starters also can be malfunction too due to corroded electrical connections or an undercharged battery. This system can be used to solve this problem. This system used human energy by using mechanical parts in order to produce electrical power. In order to produce electrical current, workforce will be applied by rotating the wheel that already linked by belt and from that rotations will trigger a magnetic force and it will produce an electrical current and supply it into battery. This system is divided into two development; hardware development and software development. The hardware development involved, mechanical device which is used and electrical device such as monitor. For software development, Fritzing is used to construct circuit.
      26  32
  • Publication
    Quality and stability of rice bran protein powder at different storage condition
    ( 2020-12-18)
    Mohd Sharizan Md Sarip
    ;
    Musa N.A.
    ;
    Syahrul Affandi Saidi
    ;
    Mansor M.R.
    Rice bran contain higher amount of protein, vitamins, essential fatty acids, minerals, dietary fiber and sterol attribute to large food application. The possible application of rice bran protein in food industry are hampered due to the limited information on its stability which may be caused by the rancidity due to the exposure of its oil to lipase. Therefore, stability study for protein extracted form rice bran is essential to evaluate the protein quality at different possible storage condition. Three different storage condition was evaluated; 1. Sample 1 (Store in freezer), 2. Sample 2 (Store in close container in room temperature) and 3. Sample 3 (Store in open container in room temperature). Protein was extracted using hot water process at temperature of 120 C for 20 minutes and dried using spray drying process. All sample are monitored for 5 days for its protein composition, water activity, moisture content and pH. The functional group of the sample where analysed using Fourier transform infrared radiation (FTIR). As a conclusion, the storage condition gives an effect on the water activity and moisture content of the rice bran protein product. However, it not given the significance effect on protein concentration and pH.
      5  28
  • Publication
    Leukemia Blood Cells Detection using Neural Network Classifier
    ( 2023-12-01)
    Muhammad Naufal Mansor
    ;
    Mohd Zamri Hasan
    ;
    Wan Azani Wan Mustafa
    ;
    Farah Hanan Mohd Faudzi
    ;
    Syahrul Affandi Saidi
    ;
    Mohd Aminudin Jamlos
    ;
    Noor Anida Abu Talib
    ;
    Ahmad Kadri Junoh
    Image segmentation is an image processing operation performed on the image in order to partition the image into some images based on the information contained in the original image. Image segmentation plays an important role in many medical imaging applications, image segmentation facilitates the anatomy process in a particular body of human body. Classification and clustering are the methods used un data mining for analyzing the data sets and divide them on the basis of some particular classification rules. There are many image segmentation tools that used for medical purpose, so it is necessary to define and/or to improve the image segmentation methods in order to get the best method. In this study, the image of leukemia and red blood cells will be used as samples to determine the best algorithm in image segmentation. The procedure for doing segmentation itself is clustering image, edge detection on image, and image classification. The clustering is to extract important information from an image. The edge detection is to determine the existence of edges of lines in image in order to investigate and localize the desired edge features. Moreover, the classification analyzes the properties of some images and organizes the information into certain categories. In this study, the Neural Network and K-Nearest Neighbor are used for image classification by paired with Local Binary Pattern and Principal Component Analysis. The results revealed that the best method of proven in classifying images is from Local Binary Pattern feature extraction with the average accuracy of 94%.
      4  27
  • Publication
    Entropy virus microscopy images recognition via neural network classifiers
    ( 2017-07-02)
    Afiq Ahmad Shakri
    ;
    Syahrul Affandi Saidi
    ;
    Haryati Jaafar
    ;
    Muhammad Naufal Mansor
    ;
    Wan Azani Wan Mustafa
    ;
    Ahmad Kadri Junoh
    One of the topics that are commonly in focus of object detection and image recognition is virus detection. It is well known that to learn and detecting virus proven to be a challenging and quite complex task for computer systems under different noise level. This research work investigates the performances of preprocessing stages with Entropy feature extraction with Feed Forward Neural Network (FFNN) classifier under various levels of noise. The real time experiment conducted proved that the method proposed are efficient, robust, and excellent of which it has produced a results accuracy of up to 88% for biological viruses images classification.
      11  35