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[Quantum Computing Analysis in Electricity Circuit Using Python ]]>
<![CDATA[Satria, Andy]]>;
<![CDATA[Ramadhani, Fanny]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 3, No 2 (2022) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v3i2.220
<![CDATA[This study aims to determine the quantum computing analysis in electrical circuits using python ptogram. Python is a programming language that can execute a number of multi-use instructions directly (interpretive) with the object orientation method. Python is the easiest programming language to understand. Python was created by a Dutch programmer named Guido Van Rossum. In the digital era, all professions related to technology and computers are considered promising in the future, one of which is programmer. There are many things you can create while pursuing the programmer world, such as software, smartphone applications, GUI programs, CLI programs, Internet of Things, games and others. Where quantum computing has inspired countless scientists, physicists and computer scientists. The development of the field of quantum computing can be seen from several demonstration experiments in the last two decades. Quantum information processing is a field that includes quantum computation, quantum cryptography, quantum communications, and quantum games, this field brings with it the idea of using quantum mechanics more than classical mechanics to model information processing. Quantum computing theory is not about changing the physical substrate on which computations are made from classical to quantum, but rather changing the idea of computing itself. This change can be seen from the change in the basic unit of calculation on the computer, namely the bit, which is changed to the quantum bit or qubit.]]>
<![CDATA[Analysis K-Nearest Neighbors (KNN) in Identifying Tuberculosis Disease (Tb) By Utilizing Hog Feature Extraction ]]>
<![CDATA[Muhathir, Muhathir]]>;
<![CDATA[Sibarani, Theofil Tri Saputra]]>;
<![CDATA[Al-Khowarizmi, Al-Khowarizmi]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 3, No 2 (2022) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v1i1.11
<![CDATA[Pulmonary tuberculosis is an infectious disease caused by Microbacterium tuberculosis, which is one of the lower respiratory tract disease, which is largely in the pulmonary tissue of the lung infection and then undergoes a process known as the primary focus of Ghon. Because the disease is difficult and takes a long time to decide the patient is affected by the disease Tuberkolusis, then the detection of the patient affects Tuberkolusis by utilizing the K-NN method as a classification and HOG as feature extraction. Results of the classification of positive diagnosis with a total of 234 samples from 330 samples or successfully recognizable Sebasar 70.90%, while the classification result is a negative diagnosis with the amount of 240 samples from 330 samples or successfully identified by 72.72%. The results of the study showed the image classification of the X-ray Set Tuberculosis using the method K-NN and HOG feature with cross-validation 5 folds with 71.81% accuracy. Keyword : tuberculosis, K-NN, HOG.]]>
<![CDATA[Design of Decision Support System for Selection of Outstanding Students Using AHP and Promethee Methods ]]>
<![CDATA[Dachi, Surya Wisada]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 3, No 2 (2022) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v3i2.234
<![CDATA[Student affairs often has difficulty in determining students that are sent to events because of many outstanding students at the institution. So far, the sending of students is still intuitive and subjective. Therefore, this research aims to design and build a decision support system that can provide advice to determine the best student that will be sent to the event. In this research, the method of decision support system that is used is a combination of AHP and Promethee. In implementation, AHP is executed to get criteria weight. After that, Promethee is executed to determine the order of candidates priority. The purpose of combination is to increase the quality of advice about the selection of students. The result of research shows that with the decision support system that is built, student affairs can choose the students that are sent to events more quickly, accurately, and objectively. Gist-The student affairs department often has difficulty in determining outstanding students who will be sent to events due to the large number of outstanding students in the institution. Due to the absence of a decision support system, sending students so far is still intuitive and subjective. Therefore, this research aims to design and build a decision support system that can provide advice to determine the best students to be sent to the event. In this case, the decision support system method used is a combination of Analytical Hierarchy Process (AHP) and Promethee. In its application, AHP is run first to get the weight of the criteria. After that, Promethee is run to determine the priority order of prospective event participants. The purpose of this combination is to improve the quality of student selection advice. The results showed that with this decision support system, the student affairs department can select students who are sent to an event more quickly, precisely, and objectively.]]>
<![CDATA[K-Nearest Neighbor Algorithm for Predicting Land Sales Price ]]>
<![CDATA[Harahap, Tua Holomoan]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 3, No 2 (2022) ]]>
Publisher : <![CDATA[Al'Adzkiya ]]>
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DOI: 10.55311/aiocsit.v3i2.235
<![CDATA[Until now, there are still many people who have difficulty making choices in choosing strategic land at a price according to their abilities due to lack of knowledge about land prices based on market prices. Based on these problems, the design and manufacture of applications that can be used to predict the selling price of land with the K-Nearest Neighbor (KNN) algorithm approach. This application is expected to provide more accurate and efficient information about the selling price of land and help prospective buyers or sellers of land to predict the value of land according to the specified criteria. The data collected is secondary data. The method used is a combination of data mining stages known as the Cross-Industry Standard Process for Data Mining (CRISP-DM) and the Waterfall Model software development method. Overall, this application is able to predict land value with a fairly long processing because the KNN algorithm is basically comparing testing data (new data) with training data (old data) one by one. The accuracy of the testing data prediction is 80%.]]>
<![CDATA[Combinatorial Study Implementation In Kaggle Applications ]]>
<![CDATA[Afifah, Nur]]>
<![CDATA[ Al'adzkiya International of Computer Science and Information Technology (AIoCSIT) Journal Vol 3, No 2 (2022) ]]>
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DOI: 10.55311/aiocsit.v3i2.227
<![CDATA[One of the core subjects of Mathematics is that students are expected to have the ability to understand concepts, explain the interrelationships between concepts and apply concepts accurately, efficiently and precisely in solving problems. There are many students who, after learning mathematics, are unable to understand even the simplest parts, many concepts are misunderstood so that mathematics is considered a difficult science. Understanding the concept is the most important part in learning mathematics, one of which is in combinatorial material, increasing the understanding of combinatorial concepts needs to be pursued for the success of students in learning. Combinatorial is a branch of mathematics for calculating the number of possible arrangements of objects without having to enumerate all possible arrangements. Kaggle is a site or platform that holds competitions in the field of Data Science, kaggle is also a common (practically) Science learning resource. For this reason, an early introduction to this technology is needed for students who are still in school. Writing this article aims to get an overview of students' understanding of the concepts of combinatorial and kaggle so that students can apply questions about combinatorial to kaggle.]]>
