IJISTECH
IJISTECH (International Journal of Information System & Technology) has changed the number of publications to six times a year from volume 5, number 1, 2021 (June, August, October, December, February, and April) and has made modifications to administrative data on the URL LIPI Page: http://u.lipi.go.id/1492681220 IJISTECH (International Journal Of Information System & Technology) is a peer-reviewed open-access journal published two times a year in English-language, provides scientists and engineers throughout the world for the exchange and dissemination of theoretical and practice-oriented papers dealing with advances in intelligent informatics. All the papers are refereed by two international reviewers, accepted papers will be available online (free access), and no publication fee for authors. The articles of IJISTECH will be available online in the GOOGLE Scholar. IJISTECH (International Journal Of Information System & Technology) is published with both online and print versions. The journal covers the frontier issues in computer science and their applications in business, industry, and other subjects. Computer science is a branch of engineering science that studies computable processes and structures. It contains theories for understanding computing systems and methods; computational algorithms and tools; methodologies for testing of concepts. The subjects covered by the journal include artificial intelligence, bioinformatics, computational statistics, database, data mining, financial engineering, hardware systems, imaging engineering, internet computing, networking, scientific computing, software engineering, and their applications, etc. • Artificial Immune Systems, Ant Colonies, and Swarm Intelligence • Autonomous Agents and Multi-Agent Systems • Bayesian Networks and Probabilistic Reasoning • Biologically Inspired Intelligence • Brain-Computer Interfacing • Business Intelligence • Chaos theory and intelligent control systems • Clustering and Data Analysis • Complex Systems and Applications • Computational Intelligence and Soft Computing • Cognitive systems • Distributed Intelligent Systems • Database Management and Information Retrieval • Evolutionary computation and DNA/cellular/molecular computing • Expert Systems • Fault detection, fault analysis, and diagnostics • Fusion of Neural Networks and Fuzzy Systems • Green and Renewable Energy Systems • Human Interface, Human-Computer Interaction, Human Information Processing • Hybrid and Distributed Algorithms • High-Performance Computing • Information storage, security, integrity, privacy, and trust • Image and Speech Signal Processing • Knowledge-Based Systems, Knowledge Networks • Knowledge discovery and ontology engineering • Machine Learning, Reinforcement Learning • Memetic Computing • Multimedia and Applications • Networked Control Systems • Neural Networks and Applications • Natural Language Processing • Optimization and Decision Making • Pattern Classification, Recognition, speech recognition, and synthesis • Robotic Intelligence • Rough sets and granular computing • Robustness Analysis • Self-Organizing Systems • Social Intelligence • Soft computing in P2P, Grid, Cloud and Internet Computing Technologies • Stochastic systems • Support Vector Machines • Ubiquitous, grid and high-performance computing • Virtual Reality in Engineering Applications • Web and mobile Intelligence, and Big Data
Articles
394 Documents
<![CDATA[Prediction of Student Graduation using the K-Nearest Neighbors Method ]]>
<![CDATA[Wati, Embun Fajar]]>;
<![CDATA[Perangin-Angin, Elvi Sunita]]>;
<![CDATA[Sari, Anggi Puspita]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 7, No 3 (2023): The October edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v7i3.318
<![CDATA[Predictions on the accuracy of student graduation are designed to support study programs in guiding students so that they can graduate on time. The number of student graduations will influence the university's accreditation score. Graduation predictions can provide very useful information in decision-making; therefore, research was conducted on student graduation data. This data will be processed using the K-Nearest Neighbor method. The dataset used consisted of 150 students majoring in informatics engineering. The variables included gender, age, marital status, grade, and job status. The research methodology used in this study consists of 6 stages: Data Collection, Data Selection, Preprocessing, Transformation, Testing, and Evaluation. In the preprocessing or cleaning stage, the data can be fully utilized because all fields have been filled in correctly. Meanwhile, in the transformation stage, the data is categorized as follows: age (young: 19-24, old: 25-50) and grade (large: 3-4, small: 1-2.9). The K-Nearest Neighbor (KNN) method can predict student graduation rates. The KNN method, processed with the RapidMiner 9.9 tool, obtained an average accuracy of 100%. Based on the results of 100% accuracy and an AUC value of 1, it can be concluded that the KNN method is highly accurate in classifying graduation data for the 150 students.]]>
<![CDATA[Use of The Merdeka Teaching Platform Application In The Implementation of the Independent Curriculum ]]>
<![CDATA[Alawiah, Enok Tuti]]>;
<![CDATA[Setyorin, Dini]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 7, No 3 (2023): The October edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v7i3.312
<![CDATA[Independent Teaching Platform is an application launched by the Ministry of Education, Culture, Research and Technology aimed at teachers in the framework of adaptation to the independent curriculum. This application must be used by teachers to share information, good practices, aspiration videos and learning resources. The Merdeka Mengajar Platform is an application launched by the Ministry of Education, Culture, Research and Technology aimed at teachers in the framework of adaptation to the independent curriculum. This application must be used by teachers to share information, good practices, aspiration videos and learning resources. However, the Merdeka Mengajar Platform has not been fully accepted by teachers because not all teachers have the ability to access information technology, inadequate infrastructure, difficulty accessing and lack of motivation in learning the new paradigm so that they enter into using the old paradigm in the learning process in class. This study uses the TOPSIS method, which is a multi-criteria method used to find the most ideal preference value in the decision-making process. The results of the study obtained a score of 8.35 for the Readiness of the Education Unit, which means that the use of the Merdeka Mengajar Platform in its implementation requires the readiness of the Education unit which consists of the Principal, Learning Committee and Teachers]]>
<![CDATA[Design of a Web-Based Truck Maintenance Information System Using Web Engineering Methods at PT. POS Logistics Indonesia Palembang Branch Office ]]>
<![CDATA[Nugraha, Adriansyah]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 7, No 3 (2023): The October edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v7i3.313
<![CDATA[PT Pos Logistics Indonesia Palembang Branch Office as a logistics company faces challenges in maintaining a fleet of trucks for optimal operations. The lack of a truck maintenance information system causes efficiency and effectiveness to be hampered. Therefore, this research designs a web-based truck maintenance information system with the aim of improving the management and performance of truck fleets. The development method used is web engineering with integration of truck, driver, mechanic and spare parts data. This system also supports data archiving to maintain good historical documentation. By implementing this system, it is hoped that truck maintenance information will become more accurate, complete and efficient.]]>
<![CDATA[Efficiency Development Analysis Use of Automation Testing using Katalon on Mobile-Based Applications (Case Insurance Company) ]]>
<![CDATA[Anggrainy, Shynta Eza]]>;
<![CDATA[Muhammad, Alva Hendi]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 1 (2024): The June edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i1.347
<![CDATA[The use of automation in mobile application testing has become an important tool in improving the efficiency and quality of applications. Katalon Studio, as one of the automated testing tools, offers convenience for testers in conducting automated testing without having to master any programming language. This tool allows continuous testing to maximize the potential of features and applications as a whole. Katalon Studio also allows the addition of an alert feature on failed scenarios, so that the relevant team will be notified if a failure occurs when the script is run. In addition, the use of automated testing tools such as Katalon Studio can speed up the testing process and increase efficiency. In the context of mobile-based applications, automated testing is very important to ensure the quality of the user experience (usability). By conducting automated testing, the app design and development team can be aware of issues that may arise and fix them immediately. Overall, the use of Katalon Studio in automated testing of mobile applications can help improve the efficiency of the testing process and application quality, as well as maximize the potential of application features.]]>
<![CDATA[Face-Based Attendance Data Using Principal Component Analysis ]]>
<![CDATA[Aulia, Muhammad Arief]]>;
<![CDATA[Furqan, Mhd.]]>;
<![CDATA[Sriani, S]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 7, No 5 (2024): The February edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v7i5.331
<![CDATA[The face is one of the easiest physiological measurements and is often used to distinguish the identity of one individual from another. This facial recognition process uses raw information from image pixels produced through the camera which is then represented in the Principal Components Analysis method. The way the Principal Components Analysis method works is by calculating the average flatvector pixel of images that have been stored in a database, from the average flatvector the eigenface value of each image will be obtained and then the closest eigenface value of the image will be searched for. image of the face you want to recognize. The test results show the overall success rate of face recognition that the application can carry out face recognition using digital camera hardware for the attendance system by displaying the name of the face owner as well as the date and time of recognition. The average accuracy value of the test with the light intensity level is 96.66%, the accuracy value The average test value with changes in the distance between the camera and the face was 98.33% and the average accuracy value of the test using glasses and hat accessories was 85%.]]>
<![CDATA[Application of Prediction of Motorcycle Spare Part Sales with the Trend Moment Method ]]>
<![CDATA[Septiani, Noer Azni]]>;
<![CDATA[Ramdhani, M Ronal]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 1 (2024): The June edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i1.342
<![CDATA[One important aspect of running a successful motorcycle repair shop business is being able to control the inventory of motorcycle spare parts. Motorcycle spare parts in motorcycle workshops usually estimate stock by guessing only, which results in existing stock piling up unsold, because there is no calculation for the estimated sales stock of motorcycle spare parts for the next year, this is a constraint in the availability and need for spare parts stock. The author's purpose in this study is to determine the process of forecasting or forecasting the sales stock of motorcycle spare parts in a workshop, to design and make sales predictions in the workshop that are objective and measurable in accordance with past sales data, to apply sales predictions using the Trend Moment method in determining the estimated stock of spare part sales in each subsequent month. From the existing problems, the workshop will predict the sale of motorcycle spare parts. Application design that has been designed with a system that has been implemented using PHP programming language and database using MySQL, XAMPP using the process of forecasting motorcycle spare part sales using the Trend Moment method, starting from entering sales data in the previous period, to the forecasting process using the Trend Moment method to get results on how much stock of motorcycle spare part sales for the next month]]>
<![CDATA[IOT-Based Bengawan Solo River Water Discharge Increase Marker System (Internet of Things) ]]>
<![CDATA[Anggita, Febri Arif]]>;
<![CDATA[Maulindar, Joni]]>;
<![CDATA[Susanto, Rudi]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 2 (2024): The August edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i2.359
<![CDATA[When the rainy season comes, the water in the Bengawan Solo river will experience an increase in water discharge and will result in the area being flooded in the watershed area so that the community will suffer material and life losses. So that a device to detect the increase in water discharge is injured remotely, to give a sign that the water has increased so that the community can save valuable goods. So that the community does not suffer many losses and can immediately evacuate goods and souls to a safe place. This research aims to create a device to detect the increase in water discharge in the Bengawan Solo river remotely. In making the tool, the author uses the prototype development method, the author searches for data with various sources and types of data. The author collected data from interviews with local residents and related agencies. From this study, the author produced a system to detect the increase in water discharge and type of rain by using a water level sensor, rain sensor and ESP 32 microcontroller which can be monitored through a telegram application remotely using an internet connection. The tool made by the author can detect the river water level from level 3, level 2 and level 1 and also detect the type of rain that occurs around the river.]]>
<![CDATA[New Student Admission Using SAW Method at Darut Ta'lim Islamic Boarding School ]]>
<![CDATA[Perkasa, Eza Budi]]>;
<![CDATA[Irawadi, Syafrul]]>;
<![CDATA[Yanuarti, Elly]]>;
<![CDATA[Anisah, A]]>;
<![CDATA[Romadiana, Parlia]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 7, No 4 (2023): The December edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v7i4.326
<![CDATA[With current technological advances, it is certainly very easy for human work, an example of current technological advances is smartphones. This can be a development of a smartphone technology, namely the Android-Based New Student Admission Application with the Simple Additive Weighting (SAW) Method at Darut Ta'lim Islamic Boarding School in Kundi Village. This application is an application that aims to make it easier for prospective new students to be able to register online and be able to optimize the data collection process for prospective new students at Darut Ta'lim Islamic Boarding School in Kundi Village. The method used in this research is the Prototype Method which has four stages, namely the data collection stage, the rapid planning stage, the Prototype Design Stage and the Prototype Testing Stage. The quick planning stage uses UML (Unified Modelling Language) diagrams such as use case diagram, activity diagram, class diagram and sequence diagrams. The results obtained from this research is an application design that can be developed into an application made using Android Studio with Kotlin programming language and using PHP with MySQL database.]]>
<![CDATA[Combined Performance of Hill Cipher and Rivest Code 6 (Rc6) Algorithms in Image Security ]]>
<![CDATA[Santoso, Heri]]>;
<![CDATA[Rambe, Nia Sabrina]]>;
<![CDATA[Suhardi, S]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 7, No 6 (2024): The April edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v7i6.337
<![CDATA[Digital image files are a form of information that is accurate and reliable enough to describe something, so the level of authenticity of this information needs to be maintained. Especially when sent via the internet as in chat-based applications such as Facebook, WhatsApp, Instagram and other social media. To maintain the security and confidentiality of digital image/image information, it is necessary to have a technique called cryptography. Cryptography is a technique or algorithm for changing data or information to be different from the original information. For example, in everyday life, there is a result of a design order that is still in the development stage that needs to be shown to prospective buyers, a drawing file or documentation image file that is private and confidential, so it is important to pay attention to its security. This research will use the combined performance of the Hill Cipher and Rivest Code 6 cryptographic algorithms in securing image files. The results of the Hill Cipher and Rivest Code 6 cryptographic algorithm encryption are able to disguise the image during the encryption process. And can restore to the original image in the decryption process. So that the encrypted image is safer to send via the internet or social media.]]>
<![CDATA[Implementation of Machine Learning Classification of Obesity Weight using Dicision Tree ]]>
<![CDATA[Putra, Fajar Rahardika Bahari]]>;
<![CDATA[Surahmanto, Muhammad]]>;
<![CDATA[Haris, H]]>
<![CDATA[ IJISTECH (International Journal of Information System and Technology) Vol 8, No 2 (2024): The August edition ]]>
Publisher : <![CDATA[Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa ]]>
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DOI: 10.30645/ijistech.v8i2.354
<![CDATA[This work presents the application of the Decision Tree algorithm in the classification of obesity status using a machine learning approach. Indonesia is faced with three nutrition problems at once: stunting, wasting, and obesity or overnutrition. Obesity is a condition with excessive accumulation of body fat, which can lead to diseases and reduce quality of life. This study uses a dataset of 500 respondents and aims to classify obesity status early using the Decision Tree algorithm. The findings show that the developed Decision Tree model has an accuracy of 82%, with high precision and recall values, demonstrating the effectiveness of the algorithm in classifying obesity status. In conclusion, this study demonstrates the significant potential of the Decision Tree algorithm in supporting the early detection of obesity and facilitating more focused health interventions.]]>
