Al'Adzkiya International of Computer Science and Information Technology Journal
Computer Science, Computer Engineering and Informatics: Data Science Artificial Intelligence, Machine Learning, Neural Network, Computer Architecture, Parallel and Distributed Computer, Pervasive Computing, Computer Network, Embedded System, Human—Computer Interaction, Virtual/Augmented Reality, Computer Security, Software Engineering (Software: Lifecycle, Management, Engineering Process, Engineering Tools and Methods), Programming (Programming Methodology and Paradigm), Data Engineering (Data and Knowledge level Modelling, Information Management (DB) practices, Knowledge Based Management System, Knowledge Discovery in Data), Network Traffic Modelling, Performance Modelling, Dependable Computing, High Performance Computing, Computer Security, , Networking Technology, Optical Communication Technology, Next Generation Media, Robotic Instrumentation, Information Search Engine, Multimedia Security, Computer Vision, Distributed Computing System, Mobile Processing, Next Network Generation, Computer Network Security, Natural Language Processing, Cognitive Systems. Management Informatics, Information System and developmental economics : Human-Machine Interface, Stochastic Systems, Information Theory, Intelligent Systems, IT Governance, Smart City, e-Learning, Business Intelligence, Information Retrieval, Business Process, Financial Technology (Fintech). Telecommunication and Information Technology: Modulation and Signal Processing for Telecommunication, Information Theory and Coding, Antenna and Wave Propagation, Wireless and Mobile Communications, Radio Communication, Communication Electronics and Microwave, Radar Imaging, Distributed Platform, Communication Network and Systems, Telematics Services and Security Network. Instrumentation and Mathematics: Optimal, Robust and Adaptive Controls, Non Linear and Stochastic Controls, Modelling and Identification, Robotics, Image Based Control, Hybrid and Switching Control, Process Optimization and Scheduling, Control and Intelligent Systems, Artificial Intelligent and Expert System, Fuzzy Logic and Neural Network, Complex Adaptive Systems.
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<![CDATA[Classifying Chilli Plants Using Digital Images And Multiple Linear Regression ]]>
<![CDATA[Mahendra, Esa]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 1 (2024) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v5i1.313
<![CDATA[The present study focuses on the application of classification methods using digital images and multiple linear regression to identify types of chili plants based on texture and shape features extracted from leaf images. In the process, digital images of chili plants undergo a pre-processing stage to enhance image quality, followed by feature extraction using methods such as the Gray-Level Co-occurrence Matrix (GLCM). The present study utilised 100 datasets of chili plant images obtained from the BRIN website, which were then divided into training data and test data to train a multiple linear regression model. However, the findings of the study indicated that the multiple linear regression model was not adept at encapsulating the intricacies of the data, as evidenced by the negative R-squared value and substantial prediction errors. Consequently, it is recommended that dimensionality reduction and cross-validation techniques be applied to enhance model performance and increase accuracy in classifying chili plant types in future.]]>
<![CDATA[Convolutional Neural Network Based Human Posture Correction Implementation for Yoga Health Motion Classification ]]>
<![CDATA[Raihan, Elza Ahmad]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 1 (2024) ]]>
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DOI: 10.55311/aiocsit.v5i1.316
<![CDATA[Post-pandemic lifestyle patterns have undergone many changes with the implementation of digital transformation, one of which is the meditation pattern such as yoga practice that can be done independently at home without direct interaction with the instructor. This study also aims to develop a yoga movement classification system using Convolutional Neural Network (CNN) based on human posture correction. Using the Movenet model, this system can recognise and classify different yoga poses to provide accurate feedback on correct posture. Training data was collected from yoga photographs and processed into pose images that were analysed using CNN. The results of this study indicate that the developed system is able to achieve a high level of accuracy in identifying yoga poses, which has the potential to help users improve their posture and reduce the risk of injury. This system is also implemented in a mobile application, making it easier for users to access posture correction in real time. As such, this research makes a significant contribution to the fields of health and technology by providing innovative solutions for safer and more effective yoga practice.]]>
<![CDATA[Performance Analysis of RC4 Symmetric and RSA Asymmetric Cryptographic Algorithms In Securing Normal Text Messages ]]>
<![CDATA[R, Renaldi]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 1 (2024) ]]>
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DOI: 10.55311/aiocsit.v5i1.317
<![CDATA[Information security plays a crucial role in the digital age, particularly in safeguarding text messages from unauthorized access. Cryptography serves as a means of data security by employing encryption algorithms that transform the original message into a format that is hard to comprehend. This thesis examines the performance evaluation of two cryptographic algorithms: RC4, a symmetric algorithm, and RSA, an asymmetric algorithm, in the protection of regular text messages. This research centers on comparing the two algorithms regarding their encryption and decryption speeds, along with their effectiveness in masking the character frequency pattern present in the original text message. Testing was conducted with various short, medium, and long text documents. The test outcomes indicate that RC4 excels in speed for both encryption and decryption processes, particularly when handling large texts. Nonetheless, RSA excels in security due to its capacity to generate a more random and unpredictable character frequency distribution.]]>
<![CDATA[The Application of the Forward-Backward Chaining Method in Analyzing Oil Palm Plant Diseases at PT. Fajar Agung ]]>
<![CDATA[Salsabila, Intan Salwa]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 1 (2024) ]]>
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DOI: 10.55311/aiocsit.v5i1.318
<![CDATA[Bengabing Plantation is a pure plantation managed by a national private company, PT. Fajar Agung, which operates in the oil palm and rubber plantation sector. A frequent decline in harvest yields has been observed, caused by pests and diseases affecting the oil palm plants. Therefore, a medium is needed to help address this issue—namely, an expert system for diagnosing oil palm diseases. The aim of this research is to develop an expert system that can replicate the knowledge of plantation experts, particularly in the field of oil palm cultivation, into a computerized system by applying the forward-backward chaining method.]]>
<![CDATA[Analysis of Rainfall Prediction Using Fuzzy Time Series Method in Medan City ]]>
<![CDATA[Zikri, Syaftial]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 1 (2024) ]]>
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DOI: 10.55311/aiocsit.v5i1.319
<![CDATA[The increasingly significant climate change causes high rainfall variability, thus requiring an accurate prediction method for disaster mitigation planning and water resource managment. This study aim to analyze rainfal prediction in Medan City using Fuzzy Time Series (FTS) methode. Historical rainfall data for Medan City for a certain period is collected and processed to build an FTS model. The fuzzification process is carried out to convert numerical data into fuzzy values, then the time series relationship is identified to predict the next rainfall value. Based on Chen's fuzzy time series with the detemination of the average-based interval, the Medan City rainfall forecast based on January 2019-December 2023 data obtained the forecast results for January 2024 is 386.7 mm. From the result of tests that have caried out, the best number of sampels be used in the Medan City rainfall case is 60 data, namely the period January 2019 - December 2023.]]>
