Syahrul Affandi Saidi
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Preferred name
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

Research Output

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  • Publication
    SFTA and GLCM via LDA Classifier for Skin Cancer Detection
    ( 2020-12-18)
    Mohd Firdaus Omar
    ;
    Mansor M.N.
    ;
    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.
  • Publication
    Reduced Graphene Oxide UWB Array Sensor: High Performance for Brain Tumor Imaging and Detection
    ( 2023-01-01)
    Mohd Aminudin Jamlos
    ;
    Jamlos M.F.
    ;
    Wan Azani Wan Mustafa
    ;
    Othman N.A.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Syahrul Affandi Saidi
    ;
    Mohd Sharizan Md Sarip
    ;
    Mohd Al-Hafiz Mohd Nawi
    A low cost, with high performance, reduced graphene oxide (RGO) Ultra-wide Band (UWB) array sensor is presented to be applied with a technique of confocal radar-based microwave imaging to recognize a tumor in a human brain. RGO is used to form its patches on a Taconic substrate. The sensor functioned in a range of 1.2 to 10.8 GHz under UWB frequency. The sensor demonstrates high gain of 5.2 to 14.5 dB, with the small size of 90 mm × 45 mm2, which can be easily integrated into microwave imaging systems and allow the best functionality. Moreover, the novel UWB RGO array sensor is established as a detector with a phantom of the human head. The layers’ structure represents liquid-imitating tissues that consist of skin, fat, skull, and brain. The sensor will scan nine different points to cover the whole one-sided head phantom to obtain equally distributed reflected signals under two different situations, namely the existence and absence of the tumor. In order to accurately detect the tumor by producing sharper and clearer microwave image, the Matrix Laboratory software is used to improve the microwave imaging algorithm (delay and sum) including summing the imaging algorithm and recording the scattering parameters. The existence of a tumor will produce images with an error that is lower than 2 cm.
  • 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)
  • 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.
  • 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.
  • Publication
    Development of Surveillance Hovercraft via Arduino
    ( 2024-02-01)
    Muhammad Naufal Mansor
    ;
    Syahrul Affandi Saidi
    ;
    Wan Azani Wan Mustafa
    ;
    Roejhan Md Kawi
    ;
    Mohd Aminudin Jamlos
    ;
    Talib N.A.A.
    ;
    Mohd Zamri Hasan
    The current research focuses on the development of hovercraft via Arduino. The vehicle is designed with bag skirt structure in order to reduce friction for smooth operation. Nowadays, there are a lot of natural disaster occur in everywhere especially flood. However, hovercraft is a vehicle that need a driver to drive which can cause a danger to the rescuer. Based on this problem, a wireless hovercraft is needed to develop. This study explains a hovercraft which is able to control the movement of the hovercraft from the surface. The design of the hovercraft was successfully made by using AutoCAD software. Furthermore, the material of the body was made from the insulation foam while the microprocessor is Arduino UNO R3. There are two brushless DC motors and one servo motor that used for this hovercraft. The first brushless DC motor which is located below the hovercraft is used as a hover operation, while the second motor located behind it is used to ensure the hovercraft move forward. In addition, the performance of the hovercraft was successfully tested on the 3 different surfaces. As a result, the highest performance is on the cement while the lowest is on the grass.
  • Publication
    Develop portable blood analyzer based on temperature and quantity level
    (IOP Publishing, 2020)
    Muhammad Amar Farhan Sukemi
    ;
    Wan Azani Wan Mustafa
    ;
    Muhammad Zaid Aihsan
    ;
    Zol Bahri Razali
    ;
    Syed Akhmal Syed Jamalil
    ;
    Syahrul Affandi Saidi
    This technical paper presents a developing portable blood analyzer for monitoring of human blood sample. Perseverance of blood sample in hospitals is important in order to obtain a great quality of blood and therefore it able to determining the human type of disease. This is a life-threatening early step in most medical applications fields such as diagnosis, treatment and medical research. The proposed system consists of three main parts. In the first part, the use of convenient and handy device to deal with the problem of incorrect temperature value and inadequate quantity of blood sample. Most of previous human hospitality services show a fail to handle and properly in time to take human blood sample for diagnosis in a schedule time frame such as not punctual in taking blood sample from a patient in three different times in one day. The consequences is that these blood sample are not in perfect quality for a correct estimation of the human disease towards a pathology unit. The proposed method is a device that uses infrared temperature system and non-contact blood sample quantity detection. In the second part is by combining those two approaches to single programmable electronic modules that are used to minimize the size of the portable device in the resulting techniques to improve the functionality. The third part is accomplished by using a modern technique to produce an interface to provide the value of human blood sample and shows it on display for monitoring purposes. The programmable coding has been test in several different types of sensors and physical part. The experimental results show that this method able to integrate both requirement of human blood sample perseverance with a contactless method towards a blood tube, providing the output value of quality characteristic in a display and making it well-suited for a convenient practical application system. The experimental results in real time applications shows the effectiveness, reliable and efficiency in the proposed approach which able to almost accurately detect and monitor the human blood sample with the ability to detect different types of people gender and blood type. The proposed coding system can be executed at more precise time scheduling which is better than real life human monitoring system.
  • Publication
    Liquid Composition Identification and Characteristic Measurement Using Ultrasonic Transmission Technique via Neural Network
    ( 2023-08-01)
    Muhammad Naufal Mansor
    ;
    Yahya S.
    ;
    Wan Azani Wan Mustafa
    ;
    Habibah Mokhtaruddin
    ;
    Syahrul Affandi Saidi
    ;
    Ilham Shafini Ahmad Mahyudin
    ;
    Mohd Aminudin Jamlos
    ;
    Noor Anida Abu Talib
    ;
    Mohd Zamri Hasan
    This project is to determine the composition of liquids solvent by using the ultrasonic frequency signal from echoscope scan machine. The transmission technique of ultrasonic signal is focused. On the research experiment, studies on mixing of distilled water with control sodium chloride (Kitchen Salt), kitchen sugar and monosodium glutamate (MSG). The Parameters such as Fast Fourier Transform (FFT) which is the parameters are using to identify the ratio of composition of liquid solvent. The feature extraction of median, average and root mean square (RMS) from FFT is represented with different result analysis such as sensitivity, specificity, accuracy, Area under curve, kappa, F-measure and precision. The results performed more than 90% with Neural Network.
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  • 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.
      2  20
  • Publication
    A review of diesel spray research
    ( 2020-12-18)
    Mohd Al-Hafiz Mohd Nawi
    ;
    Wan Azani Wan Mustafa
    ;
    Muhammad Nazrin Shah Shahrol Aman
    ;
    Syahrul Affandi Saidi
    ;
    Ilham Shafini Ahmad Mahyudin
    ;
    Mohd Aminudin Jamlos
    The following literature review provides an overview of research and a summary of the most condition that relevant to the present study. The overview focuses on such parameter such as the effect of ambient condition (density and temperature), the effect of fuel injection, the effect of injection pressure, the effect of mass fuel and effect of nozzle diameter that probably effects into the droplets distribution, sprays evaporation and mixture formation of diesel spray. The preferred format has been choosing to allow an easier scanning and classification which intend to summarize the relevant topic and study regarding the diesel spray fields.
      13  2