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.
Articles
52 Documents
<![CDATA[Implementation of Digital Image Processing Techniques in Measuring the Diameter of Citrus Fruits ]]>
<![CDATA[Husaini, Abdillah]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 4, No 1 (2023) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v3i1.251
<![CDATA[Oranges are one of the many fruits that produce vitamin C. The size of oranges will affect the selling price in the market. Large oranges will be sold at a higher price and even become an export commodity. Oranges are valued by two factors; size and quality. This research aims to develop an automated system to determine the size of oranges using the requirements of the Indonesian National Standard (SNI 3932:2008) on the quality of Kepro oranges. This process uses image processing techniques, specifically segmentation by finding the area of the orange diameter. Orange size is measured by its diameter, and there are four levels of size based on SNI, namely first (70 mm), second (61-70 mm), third (51-60 mm), and fourth (40-50 mm). This size determination is usually done visually, but due to its subjectivity, this research aims to create a more objective automated system. The image processing includes testing several edge detection methods such as Prewitt, Canny, Roberts, and Sobel. In addition, the use of RGB coloring was also explored to improve the clarity of orange edges. The results show that the developed system is successful in acquiring images of oranges and identifying their size according to the requirements of the Indonesian National Standard.]]>
<![CDATA[Android-Based Student Behavior Study using Cloud Computing Infrastructure ]]>
<![CDATA[Ardi Hutagalung, Gabriel]]>;
<![CDATA[Nugroho, Okvi]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 1, No 1 (2020) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v1i1.9
<![CDATA[Android-based student behavior data collection system is a system to improve student data collection so that student data can be seen as fellow students, besides this system makes it easy for students to see grades and absences for 1 semester so that accessing grades and absences is very useful for students' parents, design Andorid-based student behavioral data collection system uses the UML (Unified Modeling Laanguage) design method, the purpose of this system is to improve student data collection, absences, grades and achievements with a computerized system that users can access student data online. The result of system design is a system that can be used by students, lecturers, to make it easier to collect student data. Keyword : Unified Modelling Language, Online, Student, Andorid.]]>
<![CDATA[Design of a Web-Based Mail Management System at The Sub- District Office of Tano Tombangan Angkola ]]>
<![CDATA[Ichsan, Aulia]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 3, No 1 (2022) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v3i1.237
<![CDATA[In the process of modernizing the administration, it is necessary to implement an information system that can support all administrative activities in an institution, institution or company. At the CAMAT Tano Tombangan Angkola office, South Tapanuli Regency, there is still a conventional letter archive management method where archive recording is still carried out using books and stationery. This often causes many problems, such as loss of documents, damage or documents that are not recorded. During the practical work, the author tries to develop an application that can record all archives in the agency. Then it will be stored in a database and can be accessed anytime and anywhere. As a result, many benefits are provided to the agency, such as more structured and neat archive data collection.]]>
<![CDATA[Design of Sentiment Analysis on Indodax Instagram Social Media Comments About Cryptocurrency Using Naïve Bayes Classifier ]]>
<![CDATA[Prayoga, Dimas]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 2 (2024) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v5i2.325
<![CDATA[In today's digital era, social media such as Instagram has become the main platform for many individuals to interact and express opinions online. One application that is often the subject of conversation is Indodax, a well-known digital asset trading platform in Indonesia. This research aims to evaluate the sentiment of Instagram users towards Indodax services through a sentiment analysis approach using Naive Bayes Classifier. The data collected consists of Instagram users' comments, which are analyzed to assess the tendency of their sentiments, whether positive or negative towards Indodax services. This method applies probability and statistical concepts to classify sentiments based on the words present in the comments. It is hoped that the results of this study can provide insights for Indodax to improve the quality of their services based on the perceptions of users. Based on the experiments conducted, the Naive Bayes Classifier method shows fairly accurate classification results, so it can support sentiment analysis related to the Indodax application.]]>
<![CDATA[Information System Location Selling Coffee Using Google Maps ]]>
<![CDATA[Hsb, Mhd Diansyari]]>;
<![CDATA[Syahputra, Edy Rahman]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 4, No 2 (2023) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v2i1.98
<![CDATA[The existence of suppliers in the coffee industry is very important in maintaining business continuity. Coffee farmers in general are still faced with a coffee trade system that is still controlled by traders. This trading system condition can regulate coffee sales transactions, both with regard to time, place and to whom the farmers' coffee beans are sold. The purpose of this research is to make it easier for sellers and buyers of coffee to find the whereabouts of coffee sellers. This research uses the Google Maps API to decide the location of coffee sales. In addition, this application is built using supporting software Android Studio and MySQL database. The results of the research show that the application functions properly without any errors or debug when the testing program is carried out where the results of the processing system display, including being able to find the location of the farmer, knowing the number of available coffee stocks and showing the way to the farmer's site. Keyword : Coffee Farmers, Sales Locations, Google Maps, Android]]>
<![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[Design of Palm Oil Transport Information Systems at CV. Simatahari ]]>
<![CDATA[Putra Mustakim Nasution, Putra Mustakim Nasution]]>;
<![CDATA[Hasdiana, Hasdiana]]>;
<![CDATA[Nurjamiyah, Nurjamiyah]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 1, No 2 (2020) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v1i2.89
<![CDATA[Transportation is the movement of goods or people from one place to another using a tool or vehicle. Transportation system in the CV. Simatahari is still manual, if the farmer wants to transport palm oil, the farmer first contacts the company via telephone to inform the transportation schedule and address. This often results in mistakes from the company when recording the schedule and address for transporting oil palm. One solution is to create a web-based palm oil transportation information system. The research method used in the manufacture of transportation information systems namely design thinking methods, programming languages using PHP and MySQL are used as databases. The results of this study can facilitate farmers in ordering oil palm transportation in real-time and also can find out information on the price of oil palm per kilo and transportation wages. Keyword: Transportation System, Palm Oil, Website, Design Thinking]]>
<![CDATA[Implementation of Discrete Mathematics to Improve The Understanding of The Concept of Space Building Based On Desktop Java ]]>
<![CDATA[Purba, Oktaviana Nirmala]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 4, No 1 (2023) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v4i1.233
<![CDATA[The introduction of mathematical space building media is often applied in learning module media such as books. In this case it is less effective because students are less able to absorb what is conveyed by the teacher because the media is still a two-dimensional image. With the existence of a desktop java-based application, objects in the introduction of building space can be made into 3-dimensional images. This means that it is possible that this technology can be used as a tool for a more innovative method of introducing the Mathematical Space Formulas, such as by highlighting a camera connected to a cellphone the user can see in three dimensions how the shape of the real space.]]>
<![CDATA[Optimization Of The Fuzzy C-Means Cluster Center For Credit Data Grouping Using Genetic Algorithms ]]>
<![CDATA[Apdilah, Dicky]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 2, No 2 (2021) ]]>
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DOI: 10.55311/aiocsit.v2i2.225
<![CDATA[Data grouping can be used in the marketing strategy of a product. The process of grouping data that previously behaved differently into groups that now behave more uniformly. As with the grouping of creditworthiness assessment data, this data grouping is needed to obtain the dominant values that will characterize each group or segment. The clustering method is quite widely used to overcome problems related to data segmentation. Clustering is a grouping method based on a measure of proximity, the more accurately the clusters are formed, the clearer the similarity of customer behavior patterns will be. Thus, companies can determine marketing strategies more precisely, based on customer behavior patterns. One of the clustering methods that can be used to group data is Fuzzy C-Means (FCM), which is a method of grouping data determined by the degree of membership. Optimization by presenting a Genetic Algorithm to obtain test data cluster results regarding the grouping of credit data. The purpose of this study is to examine the application of the Genetic Algorithm in fuzzy clustering, especially Fuzzy C-Means, and to examine the extent to which the Genetic Algorithm can improve the performance of Fuzzy C-Means in optimizing cluster centers to obtain grouping of customer data which will later be used for assessing creditworthiness.]]>
<![CDATA[Predicting the Risk of Online Sales Fraud with the Naïve Bayes Approach on Facebook Social Media ]]>
<![CDATA[Pasha, Leony Ayu Diah]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 5, No 2 (2024) ]]>
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DOI: 10.55311/aiocsit.v5i2.320
<![CDATA[The rapid development of digital shopping media is accompanied by increasing cases of online fraud, especially through social media platforms such as Facebook. This study aims to develop a prediction model for the risk of online sales fraud using the Naïve Bayes algorithm. The data used is the data of buying and selling transactions that occur through the Facebook marketplace. The data has been collected on the Kaggle platform so that it can be used directly. Data in the form of extracted features include seller characteristics, products sold, number of transactions, device usage and other fraud indicators. Important features that affect the potential for fraud are identified and used in the machine learning process. The results of the study show that the Naïve Bayes model is able to provide accurate predictions in identifying the risk of online sales fraud, with a satisfactory accuracy rate of 95%. The results of the study are expected to contribute to the development of a more effective fraud detection system and increase user confidence in making online transactions.]]>
