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[Job Portal Prototype Using Design Thinking Method: A Case Study at Djuanda University ]]>
<![CDATA[Jabbar, Ma’shum Abdul]]>;
<![CDATA[Encep, Muhammad]]>;
<![CDATA[Novrian, Risfan]]>;
<![CDATA[Fachrani, Jihan]]>
<![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.v8i1.344
<![CDATA[The importance of higher education in cultivating skilled human capital in the current global landscape cannot be overstated. The University of Djuanda is committed to closing the gap between job seekers and employers through the implementation of innovative initiatives that acknowledge the dynamic nature of career opportunities. This study focuses on the development of a Job Portal utilizing Design Thinking as a transformative method. The University of Djuanda employs Design Thinking, a renowned methodology recognized for its cognitive, innovative, and pragmatic problem-solving approaches, to gain a thorough comprehension of the needs, challenges, and preferences of its student body. The primary objective is to create a Job Portal that is relevant and satisfying, so enhancing user satisfaction and fostering long-lasting relationships, while also addressing the limitations of traditional recruitment methods. The core aspect of this approach revolves around the implementation of Design Thinking, which improves the effectiveness of problem-solving endeavors. The objective of the research is to create a Job Portal that efficiently caters to the needs of job seekers and employers by demonstrating empathy towards them. The website aims to consistently improve its features and functionalities through iterative methods of generating ideas, creating prototypes, and conducting tests. This is done to fulfil the requirements of all stakeholders involved in the recruitment process. To evaluate the user experience, a User Experience Questionnaire (UEQ) was administered to a sample of 20 participants, comprising 10 job seekers and 10 recruiters. The visualization employs a questionnaire consisting of six Likert-scale items, which encompassed a range from "Strongly Disagree" to "Strongly Agree." The results indicate a significant level of user satisfaction, affirming the effectiveness of the Design Thinking method in developing a Job Portal tailored to the diverse needs of job seekers and recruiters]]>
<![CDATA[Implementation of the Lean User Experience Method in Home Care Registration Information System Application Yakes Telkom Regional West Java ]]>
<![CDATA[Sofalina, Fresa Dwi Juniar]]>;
<![CDATA[Rusdiana, Yudi]]>
<![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.v7i4.328
<![CDATA[The Lean method is used to determine the UI UX of a website-based Home Care service registration application. This method can help writers to make applications that are effective and in accordance with the psychological and geographic conditions of the user. Based on the results of the design using the lean method, the appearance of the Home Care service registration application is designed as simple as possible and does not make it difficult for users to operate it. This reason is due to the age of application users who incidentally are officers in the range of 30 years to 55 years.]]>
<![CDATA[Lobster Sales Prediction Using Adaptive Neuro Fuzzy Inference System (ANFIS) In Simeulue District ]]>
<![CDATA[Sandira, Sri Delwis]]>;
<![CDATA[Kurniawan, Rakhmat]]>;
<![CDATA[Hasibuan, Muhammad Siddik]]>
<![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.v7i6.339
<![CDATA[The rapid progress of technology and information is making the challenges of the past become a tantalizing reality of the fourth industrial revolution. Rapid technological progress is marked by major developments in all aspects of life, such as economics, education, health, social and cultural. In the economic world, increasingly sophisticated technological developments will help the work of business actors and force them to innovate and be creative in improving the quality, capacity and products produced. With the vast lobster market, lobster demand experiences a sharp increase every year along with an increase in prices which will provide profits for fishermen in Simeulue. Therefore, predictions of lobster sales are quite important for fishermen in Semeulue to predict lobster sales that will be marketed abroad and domestically the following day, so that fishermen can estimate the lobster seeds or lobster catch needed optimally. In the prediction process The sales data obtained is in the form of a sales history report from 2017 to 2022, then the data obtained will be calculated using the adaptive neuro fuzzy inference system (ANFIS) to then obtain sales prediction results for the following year. And using MAPE calculations with the results of lobster sales training data calculations, the accuracy yields above 99% with a value of 0.0000168031. Therefore, this research will discuss predictions of lobster sales using the adaptive neuro fuzzy inference system (ANFIS) in Simeulue Regency.]]>
<![CDATA[Application of The K-Means Clustering Algorithm to Identify Strawberry Fruit Ripe ]]>
<![CDATA[Rizki, Muhammad]]>;
<![CDATA[Furqan, Mhd]]>;
<![CDATA[Sriani, S]]>
<![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.v8i2.356
<![CDATA[Fruit ripeness will usually be determined by several parameters, including size, weight, color characteristics, fragrance, etc. The parameter of fruit ripeness in terms of fruit skin color is one of the important factors in identifying fruit maturity. Segmentation is a method in digital image processing to differentiate objects in an input image. The general classification process is carried out by looking directly at the fruit object. The purpose of this research is to create an analysis in identifying the ripeness of strawberry fruit and designing an application system that can identify the ripeness of strawberry fruit. This application was built with the MATLAB application. The methods used include K-Means Clustering segmentation, labeling and feature extraction. The detection of the type of fruit is carried out using feature matching at the level of shape and color. Before classifying the name of the type of fruit and the level of maturity, the fruit training must be carried out first and then continued with fruit detection and identification of maturity. Based on the results of the strawberry image maturity identification test with six test strawberry images consisting of three types of maturity levels, the results were obtained, namely mature test one and mature test two levels of ripeness and correct identification results, half ripe test one and half ripe test two levels of ripeness and results Correct understanding, raw test one and raw test two mature levels and correct recognition. Meanwhile, the accuracy test results obtained an accuracy value of 100% for identifying the maturity of strawberry images. From the results of the tests carried out, it can be concluded that identification of ripeness in strawberry fruit images was successfully applied using the K-Means Clustering method on images of ripe, half-ripe and unripe strawberries. And from testing the identification of ripeness of strawberry fruit with test data of six images and training data of twelve images, it gave an accuracy result of 100%.]]>
<![CDATA[A Bibliometric Analysis of the Internet of Everything in Business in 2012 - 2022 ]]>
<![CDATA[Fitriastuti, Lucia Ika]]>;
<![CDATA[Vemberi, Yohannes]]>
<![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.v7i4.323
<![CDATA[The Internet of Everything (IOE) plays a vital role in the business field in the current era of digitalization. The Internet of Everything (IOE) is a combination of 4 main elements, namely people, processes, data, and objects, that make network connections more valuable. In this article, researchers present an analysis of various studies related to the Internet of Everything (IoE) in Business over the last ten years. Bibliometric analysis was used to analyze 280 articles published from 2012 to 2022. Articles will be analyzed based on the trend of the topic raised, the type of document, the name of the journal, the source of the document, the name of the publisher and even the presentation of the authors' collaboration related to IoE. The data analysis method used is bibliometric analysis. The data is imported from the Scopus database and uses Harzing's Publish or Perish applications. Meanwhile, to get data visualization, this study uses the VoS Viewer application. This study found that most articles related to the topic of IoE in Business are published more in conference proceedings than in journals, books, or book series. The most significant number of citations were articles in 2014. The highest number of publications occurred in 2021. The results of network visualization show that articles related to the Internet of Things (IoT) are the main terms or topics that are widely found related to IoE. Other related terms are Internet, Cloud Computing, Big Data, Network Security, and Social Networking (online). Implications for businesspeople can maximize the use of IoE in their business to the maximum in the current digitalization era in order to increase their business's competitive advantage. This research also shows further researchers that there are still many research opportunities related to IoE, which can be related to IoT, big data, cloud computing, and other update issues.]]>
<![CDATA[Analysis and System Design at Mitra Sejati Hospital for Patient Drug Administration using Data Mining and Apriori Algorithm ]]>
<![CDATA[Manurung, Johanes Rico Alexander]]>;
<![CDATA[Khairani, Mufida]]>;
<![CDATA[Dharmawati, D]]>
<![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.v8i2.351
<![CDATA[This research focuses on system analysis and design at Mitra Sejati Hospital to increase the efficiency of administering medicines to patients. In this effort, data mining approaches and Apriori algorithms were implemented to identify significant treatment patterns and facilitate better decision making in medication administration management. This research is aimed at finding out how to analyze data on drug administration to patients at Mitra Sejati Hospital. The research methodology includes the system requirements analysis stage, collecting patient treatment data, and identifying treatment patterns using data mining techniques. The Apriori algorithm is used to extract association rules that represent the relationship between drugs given to patients. Next, system design was carried out to integrate the analysis results into the drug administration process at Mitra Sejati Hospital. The research results show that the application of data mining and the Apriori algorithm can help identify critical treatment patterns, reduce the risk of drug interactions, and increase the efficiency of the drug administration process. The proposed system is able to provide more precise drug recommendations based on the patient's medication history. By combining data mining technology and the Apriori algorithm in the drug administration system, Mitra Sejati Hospital can optimize patient medication management, improve the quality of health services, and reduce the potential risk of errors in medication. This research contributes to the development of intelligent and innovative health information systems in the hospital environment.]]>
<![CDATA[Android-Based Attendance Application at PT. Solusi Hidup Mandiri (SHM) ]]>
<![CDATA[Fakhri, Raja Muh.]]>;
<![CDATA[Abduh, Hisma]]>;
<![CDATA[Muhallim, Muhlis]]>
<![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.v7i5.334
<![CDATA[This research aims to design and build an Android-based attendance application. The research method used is a qualitative method. The data collection methods in this research are (1) data documentation, (2) observation, (3) interviews, and (4) questionnaires. In this research, the system development method used is a prototype with the system design using UML (Unified Modeling Language) which consists of use case diagrams, activity diagrams, sequence diagrams and class diagrams. The software used in designing and implementing the system uses XAMPP as a web server, MySQL as a database, Visual Studio Code as a web design editor and Android Studio as an Android application design editor. The Android-based attendance application includes attendance, absence, absence history, and permit applications. The score obtained from the usability testing results is 93% and is in the "Strongly Agree" category. The application has been tested so that an application that runs well is obtained.]]>
<![CDATA[Modelling of C4.5 Algorithm for Graduation Classification ]]>
<![CDATA[Wati, Embun Fajar]]>;
<![CDATA[Sudrajat, Budi]]>;
<![CDATA[Nasution, Raudah]]>
<![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.v8i1.345
<![CDATA[Student admissions in universities every year become a routine thing to do, some even do student admissions every semester. That way, the number of students will continue to grow. Especially if there are students who graduate late, it will increase the number of students in the university. There are many things that can affect graduation, namely personal data (gender, age, marital status, job status) and academic data (grade). Before making a decision, universities must analyze the number of students and the factors that most influence student graduation. Analysis by classifying graduation using C4.5 algorithms. The research method used consists of selection to ensure the data used in the KDD process is appropriate and quality data. Then preprocessing by means of data cleaning, data reduction, and data normalization. The next method is transformation for age attributes to young and old, grade attributes to large and small. The last method is C4.5 algorithm modeling with rapid miner and evaluation. Through the calculation process using the classification method and C4.5 algorithm with the attributes described earlier, the results were obtained that the accuracy of the graduation classification reached 97.00%, the precision value was 91.79%, and the recall value was 100.00%, and the AUC value was 0.978. This means that the model has a very high level of accuracy and has an excellent ability to separate samples from both target classes.]]>
<![CDATA[Subject Scheduling Application Using Genetic Algorithm ]]>
<![CDATA[Wijaya, Benny]]>;
<![CDATA[Irawadi, Syafrul]]>;
<![CDATA[Sari, Lili Indah]]>;
<![CDATA[Probonegoro, Wishnu Aribowo]]>
<![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.v7i4.329
<![CDATA[Scheduling is a very important issue in an educational institution. The many obstacles sometimes make scheduling difficult to create. One method for solving such problems is to use genetic algorithms. Based on this background, the formulation of the problem of this study is "how to implement genetic algorithms for subject scheduling applications at SMK Bakti Pangkalpinang". The purpose of this study is to implement genetic algorithms for subject scheduling, formulate subject scheduling problems so that they can be solved with genetic algorithms and help schedule preparation to be more efficient. Genetic algorithms are heuristic search algorithms based on biological evolutionary mechanisms. In this study the author uses a prototype model, which includes activities such as gathering needs, designing and evaluating. The result of this study is an application that can be used to compile a lesson schedule with the desired results. Testing is done with blackbox testing and the test results show the application can function properly.]]>
<![CDATA[Classification of Domestic Flight Passengers at Main Airports Using the K-Means Clustering Method ]]>
<![CDATA[Syaoqiyah, Syifa Siti]]>;
<![CDATA[Anisa, A]]>;
<![CDATA[Selvina, Yudhi Yulianti Selvina]]>;
<![CDATA[Rahmadenti, Nadhia Ayu]]>;
<![CDATA[Aria, Ririn Restu]]>
<![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.v8i1.340
<![CDATA[The aviation business in Indonesia has recently experienced quite significant growth, which can be seen from the fact that many people tend to choose air transportation to travel and connect them to cities in Indonesia. With air transportation, the time spent traveling to one area or city can be reduced. accomplished in a short time. This causes the number of passengers per flight to be quite high, especially in domestic flights which occur at the main airport. This research will use the K-Means Clustering algorithm to find out the schedule for the busiest month for the highest domestic airlines at major airports. The data source for this research comes from the central statistics agency regarding the number of domestic airline passengers at major airports. The criteria used in this research are divided into 3 clusters, namely high, medium, and low. The results of this research show that the highest number of passengers (C1) occurs in January to April, while the moderate number of passengers (C2) occurs in May to December, and the lowest number of passengers (C3) occurs in August to November.]]>
