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

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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.
  • Publication
    Parametric Study on The Rice Bran Protein Extraction Process Using Water as a Solvent
    ( 2022-01-01)
    Kanapathy M.
    ;
    Mohd Sharizan Md Sarip
    ;
    Syahrul Affandi Saidi
    ;
    Mohd Aminudin Jamlos
    ;
    Aris N.I.A.
    Rice bran is a by-product resulting from the milling process that is frequently underutilized as cattle food or disposed through open-burning despite of its high nutritional and nutraceutical properties. Thus, this research aims in recognizing and exploring rice bran and its extraction methods that could further cultivate in the industry. This study focuses on the rice bran extraction process using water assisted with ultrasonication. The relationship between the operational parameters such as the temperature, extraction time and sample-to-solvent ratio to the protein yield were studied. The rice bran protein was subjected to the surface functional group analysis using Fourier-transform infrared spectroscopy (FTIR). As a conclusion, the extraction temperature of 60°C, sample to solvent ratio of 10 % and extraction time of 25 mins were chosen as the best conditions for the protein extraction. The extraction of the protein from rice bran is highly profitable due to its nutritional and nutraceutical properties as well as it is readily available at low cost.
  • 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
    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.
  • 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.
  • 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
    Arduino IOT Based Inventory Management System Using Load Cell and NodeMCU
    ( 2023-11-01)
    Muhammad Naufal Mansor
    ;
    Noor Anida Abu Talib
    ;
    Syahrul Affandi Saidi
    ;
    Wan Azani Wan Mustafa
    ;
    Zamri N.F.
    Nowadays, everything is made simpler with information and communication technological advancements. It is preferable to track and monitor using devices rather than perform it manually. This resulted in the rapid growth of Internet of Things (IoT) technology and relevant markets. Low cost IoT products has made access to IoT much easier and desirable. These low cost IoT devices and related technologies are widely used in areas such as educational, transportation, tracking, inventory management and many more. The use of Arduino and RFID in the inventory management system lacks in some areas including hardware limitations. In conjunction to the limitation of using an Arduino and RFID technology, this project aims to develop an IoT based inventory management system that incorporates the uses of a NodeMCU and a load cell. In comparison of the NodeMCU to an Arduino, the NodeMCU stands out with the built in Wi-Fi module with much higher processor and additional properties of it being much smaller. While the use of a load cell is much more convenient as to suit all kinds of inventory management needs compared to the use of RFID that suits better to larger scale businesses with larger inventory and massive stocks. Towards the end, this project is expected to ease inventory management by the implementation of IoT with IoT Based Inventory Management System using Load Cell and NodeMCU. The project will generate the inventory count and automatically stores data in the cloud platform. These data can be accessed with internet connection. The project also alerts users when the inventory is low or high in balance. The output of the project is that the project’s working prototype was successfully developed. Overall, the project is a success as all the objectives of the project was successfully achieved.