Jurnal Teknik Informatika (JUTIF)
Jurnal Teknik Informatika (JUTIF) is an Indonesian national journal, publishes high-quality research papers in the broad field of Informatics, Information Systems and Computer Science, which encompasses software engineering, information system development, computer systems, computer network, algorithms and computation, and social impact of information and telecommunication technology. Jurnal Teknik Informatika (JUTIF) is published by Informatics Department, Universitas Jenderal Soedirman twice a year, in June and December. All submissions are double-blind reviewed by peer reviewers. All papers must be submitted in BAHASA INDONESIA. JUTIF has P-ISSN : 2723-3863 and E-ISSN : 2723-3871. The journal accepts scientific research articles, review articles, and final project reports from the following fields : Computer systems organization : Computer architecture, embedded system, real-time computing 1. Networks : Network architecture, network protocol, network components, network performance evaluation, network service 2. Security : Cryptography, security services, intrusion detection system, hardware security, network security, information security, application security 3. Software organization : Interpreter, Middleware, Virtual machine, Operating system, Software quality 4. Software notations and tools : Programming paradigm, Programming language, Domain-specific language, Modeling language, Software framework, Integrated development environment 5. Software development : Software development process, Requirements analysis, Software design, Software construction, Software deployment, Software maintenance, Programming team, Open-source model 6. Theory of computation : Model of computation, Computational complexity 7. Algorithms : Algorithm design, Analysis of algorithms 8. Mathematics of computing : Discrete mathematics, Mathematical software, Information theory 9. Information systems : Database management system, Information storage systems, Enterprise information system, Social information systems, Geographic information system, Decision support system, Process control system, Multimedia information system, Data mining, Digital library, Computing platform, Digital marketing, World Wide Web, Information retrieval Human-computer interaction, Interaction design, Social computing, Ubiquitous computing, Visualization, Accessibility 10. Concurrency : Concurrent computing, Parallel computing, Distributed computing 11. Artificial intelligence : Natural language processing, Knowledge representation and reasoning, Computer vision, Automated planning and scheduling, Search methodology, Control method, Philosophy of artificial intelligence, Distributed artificial intelligence 12. Machine learning : Supervised learning, Unsupervised learning, Reinforcement learning, Multi-task learning 13. Graphics : Animation, Rendering, Image manipulation, Graphics processing unit, Mixed reality, Virtual reality, Image compression, Solid modeling 14. Applied computing : E-commerce, Enterprise software, Electronic publishing, Cyberwarfare, Electronic voting, Video game, Word processing, Operations research, Educational technology, Document management.
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962 Documents
<![CDATA[INFORMATION TECHNOLOGY GOVERNANCE ANALYSIS USING COBIT 5 FRAMEWORK AT SMPN 18 BANDAR LAMPUNG ]]>
<![CDATA[Salsabila Indriyani]]>;
<![CDATA[Priandika, Adhie Thyo]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.2.1826
<![CDATA[So far, the management of Information Technology at SMPN 18 Bandar Lampung has not held an information technology governance analysis, so that the application of information technology infrastructure cannot be known at the maturity level. This study aims to determine the level of maturity of the application of information technology required information technology governance analysis. The method used in the COBIT 5 framework is up to phase 4 - Plan Programe, the calculation used is by finding the statistical average or mean value in the form of the total value of the various items contained in the questionnaire. The results of this research the average maturity index value is 3.4 and (maturity level as is) in the APO, BAI, and MEA domains, at level 3 in the APO, BAI, MEA domains. Based on the results of the research, the researcher provides suggestions regarding the procedures chosen based on the research findings to help the information technology infrastructure of SMPN 18 Bandar Lampung reach the required maturity level.]]>
<![CDATA[ANALYSIS OF USER SATISFACTION LEVEL IN INLISLITE LIBRARY SYSTEM USING END USER COMPUTING SATISFACTION (EUCS) ]]>
<![CDATA[I Made Kerisna Laksana]]>;
<![CDATA[I Made Ardwi Pradnyana]]>;
<![CDATA[I Gusti Lanang Agung Raditya Putra]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.1834
<![CDATA[The Denpasar Library and Archives Office has implemented an automation service called INLISLite for the development of information and communication technology-based library management and services. However, there are obstacles related to the level of user satisfaction that have not been identified. This study uses the End User Computing Satisfaction (EUCS) Method, focusing on five satisfaction variables: content, accuracy, appearance, ease of use, and timeliness. The research population involved admin employees and users of the INLISLite system at the Denpasar City Library and Archives Office. The sample of 109 respondents was obtained through saturated sampling and purposive sampling. The Likert scale is used to measure user satisfaction with 24 statements for each indicator of each variable. The results of data analysis of the average user satisfaction level were 3.98 with satisfied categories in each variable, namely 4.03 for content, 3.92 for accuracy, 3.93 for format, 3.97 for timeliness, and 4.04 for ease of use. With each EUCS variable known, it has an influence and is significant on the end-user satisfaction of INLISLite. However, it is necessary to make improvements to the system with some improvements. System improvement recommendations are prepared based on open question suggestions for each variable in the EUCS. Continuous improvement and development is expected to improve the quality of library and archival services based on information and communication technology.]]>
<![CDATA[COMPARISON OF JENKINS AND GITLAB CI/CD TO IMPROVE DELIVERY TIME OF BASU DAIRY FARM ADMIN WEBSITE ]]>
<![CDATA[Kuncara, Alif Babrizq]]>;
<![CDATA[Kusumo, Dana Sulistyo]]>;
<![CDATA[Adrian, Monterico]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.3.1836
<![CDATA[The Basu Dairy Farm admin website is a web-based information system developed using monolithic architecture. The delivery process of source code changes from the GitLab repository on the "main" branch (development) to the main server (production) takes a long time because the build and deploy process is done manually. This causes the delivery time to be long. To overcome this, this research applies Continuous Integration/Continuous Deployment (CI/CD) as a solution. The CI/CD tools used are Jenkins and GitLab CI/CD because they are open source and the most popular. In this study, a comparison of the delivery time of the two tools was carried out. Delivery time is obtained when the build process starts to run until the deploy process is completed. The analysis includes the time required to run the build and deploy process of the CI/CD tool. The results of this research show that Jenkins and GitLab CI/CD are successfully implemented and can automate the build and deploy process. In terms of implementation, Jenkins requires in-depth configuration, so it looks complicated, while GitLab CI/CD offers simple and easy configuration. In the three experiments conducted, Jenkins showed a faster average time in completing the build and deploy process, so Jenkins has a better delivery time than GitLab CI/CD in the context of the Basu Dairy Farm admin website development process.]]>
<![CDATA[DESCRIPTIVE ANALYSIS AND COMPARISON OF REASONER USING ONTI MEASURES ]]>
<![CDATA[Ika Indah Lestari]]>;
<![CDATA[Nur Alfi Ekowati]]>;
<![CDATA[Sulistiyasni, Sulistiyasni]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 1 (2024): JUTIF Volume 5, Number 1, February 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.1.1839
<![CDATA[Data analysis in research is an important thing to do after the research data is obtained. In designing a web application called Onti Measures, the files that have been executed have not been analyzed in more depth. Therefore, it is necessary to analyze the OWL (Web Ontology Language) files as test data for the Onti Measures application. This research aims to present a descriptive analysis of test data using three reasoners and compare their performance. The comparison of the three reasoners is seen based on running time, the performance of each reasoner, and the resulting inconsistency values. Those three reasoners are Hermit, JFact, and Pellet. In the Onti Measures application there are 10 inconsistency measures, namely drastic inconsistency measure, MI-inconsistency measure, MIc-inconsistency measure, Df-inconsistency measure, problematic inconsistency measure, incompatibility ratio inconsistency measure, MC-inconsistency measure, the nc-inconsistency measure, the mv-inconsistency measure, dan IDmcsinconsistency measure. The method used in this research is quantitative with a descriptive approach to analysis. The OWL fie input as test data is virus and disease ontology. The results of the descriptive analysis from this research include that 57.33% of the test data have an inconsistency value of 0 (consistent). Based on the performance of each reasoner in terms of processing ontologies, the three reasoners have almost the same capabilities. If it is seen from the resulting inconsistency values, the reasoner Pellet is better than the others. Meanwhile, based on the running time comparison, JFact is better than the other reasoners. The size of the ontology files does not affect the length of the running time.]]>
<![CDATA[REUSE OF THE EFSM MODEL OF PEDULILINDUNGI APPLICATION IN SATUSEHAT APPLICATION TESTING WITH MBT METHOD ]]>
<![CDATA[Rahmadani, Muamar Fajar]]>;
<![CDATA[Riskiana , Rosa Reska]]>;
<![CDATA[Kusumo, Dana Sulistyo]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.3.1848
<![CDATA[On 2023, the Government of Indonesia announced the change of PeduliLindungi application to SatuSehat, with the addition of features that have been integrated with Electronic Medical Records (RME). In this research, the concept of model reuse is applied to facilitate the creation of test models on the same features between PeduliLindungi and SatuSehat, namely Linked Profile and Covid-19 Vaccine. In applying the reuse model, the method template and edge template strategies are used to adjust to the evolution of the model that occurs in the SATUSEHAT application, in the edge template or second iteration there are additional vertices and edges on the Linked Profile and Vaccine features. By combining the number of vertices and edges, the overall similarity percentage is around 79.81% on the Linked Profile feature, showing the efficiency of modeling with a reuse model of around 20.19%. Testing on SatuSehat using Altwalker tools with Random and Weighted Random algorithms shows high coverage achievements, especially on vertex, these achievements show the effectiveness of the reuse model. Comparison with previous research on PeduliLindungi shows an increase in coverage rate, especially on features that apply the reuse model. This research illustrates the success of the reuse model concept in accelerating the development of test models and increasing coverage in applications where changes occur.]]>
<![CDATA[IMAGE DATA SECURITY USING VERNAM CIPHER ALGORITHM ]]>
<![CDATA[Supiyanto, Supiyanto]]>;
<![CDATA[Werdhani, Anastasia Sri]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.2.1864
<![CDATA[The Vernam Cipher algorithm is a symmetric key algorithm, as it uses the same key for encryption and decryption. It utilizes a binary number system with XOR operation to produce a series of bits. This study aims to implement the Vernam cipher algorithm to secure personal and confidential image data, which is at risk of misuse when shared through chat applications like Facebook, WhatsApp, and email. Therefore, developing image protection applications is crucial. The research explores whether the vernam cipher algorithm, working with single bits in block form and based on binary numbers, can effectively secure image data, specifically grey scale images with BMP and JPG extensions. The approach involves applying the Vernam cipher algorithm to programming language to create a data security application. The outcome is an image security application program, with test results indicating successful encryption with significant randomness. The decryption process with the Vernam cipher method can restore encrypted images to their original state, although some distortion may occur, especially with JPEG images. Decryption of BMP images is nearly flawless. The key for data security can vary in length and form, with encryption taking longer than decryption.]]>
<![CDATA[APPLICATION OF ENSEMBLE METHOD FOR EMPLOYEE TURNOVER PREDICTIONS IN FINANCIAL SERVICES COMPANY ]]>
<![CDATA[Fadel, Muhamad]]>;
<![CDATA[Kanasfi, Kanasfi]]>;
<![CDATA[Arifin, Zainal]]>;
<![CDATA[Triyono, Gandung]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.3.1871
<![CDATA[High employee turnover is a challenge for every company, considering that employees are a valuable asset for the company. A high employee turnover rate indicates the high frequency of employees leaving a company. This will harm the company in terms of time, costs, human resources, and reduce the company's reputation. Low employee turnover is an objective for every company in its efforts to achieve its vision and mission, the employee turnover rate is high at 78.97% at PT. HCI operating in the financial services sector can have a negative impact on the company's reputation. Therefore, there is a need to analyze and predict employee turnover so that company management can take preventive and persuasive actions so as to reduce employee turnover rates. Therefore, a tool is needed to predict whether an employee will leave the company. This paper aims to predict the possibility of employees out of the company using the ensemble method, which is a method that uses a combination of several algorithms consisting of base learners and individual learners, algorithms with the ensemble method used are stacking, random forest, and adaboost, then comparing the result to get the best accuracy. The test results prove that the Stacking algorithm technique is the best model with the highest score in terms of accuracy with a value of 86.84%, while the Random Forest and AdaBoost algorithm techniques have a value of 81.04% and 80.30%. With this high accuracy value, the Stacking model is proven to have better individual performance in analyzing employee turnover predictions in human resource applications in companies.]]>
<![CDATA[COMPARISON OF ACCURACY LEVELS OF SVM, DECISION TREE AND RANDOM FOREST ALGORITHMS IN SENTIMENT ANALYSIS OF USER RESPONSES OF THE GOPAY APPLICATION ]]>
<![CDATA[Indriani, Indriani]]>;
<![CDATA[Ade Davy Wiranata]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.3.1885
<![CDATA[The development of technology from time to time makes all work or activities easier, one of which is online money transactions which are called e-wallets or digital wallets. One of the digital wallet applications that is often used is GoPay, which is a platform and tool created for making digital payments. Not long ago, GoPay was separated into one application, which previously existed in the Gojek application. However, every application certainly has a negative side, such as GoPay, where to use the application you have to be connected to the internet, which creates dependence on smartphones. Based on this problem, the company needs to know the response of users of the GoPay application which has been launched using the SVM, Decision Tree and Random algorithms. Forest. Therefore, the aim of this research is to carry out sentiment analysis on the responses of GoPay application users after being separated from Gojek and to find out the comparison of evaluation results or accuracy produced by the three algorithms. The results of this research show that of the three algorithms used, Positive sentiment is more than Negative sentiment, where in SVM Positive 89% and Negative 85%, Decision Tree class Positive 89% and Negative 76% while in Random Forest class positive 93% and Negative 86 %. Apart from that, the Random Forest algorithm has a high level of accuracy, namely 90%, then the SVM algorithm 88% and the Decision Tree algorithm 84%.]]>
<![CDATA[THE RIGHT STEPS TOWARDS GRADUATION: NB-PSO SMART COMBINATION FOR STUDENT GRADUATION PREDICTION ]]>
<![CDATA[Kahfi, Ahmad Hafidzul]]>;
<![CDATA[Prihatin, Titin]]>;
<![CDATA[Yudhistira, Yudhistira]]>;
<![CDATA[Sudradjat, Adjat]]>;
<![CDATA[Wijaya, Ganda]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 2 (2024): JUTIF Volume 5, Number 2, April 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.2.1889
<![CDATA[The current digital era demands a more innovative approach in predicting student campuses considering that campuses are not only important for students but also for lecturers, student guardians and higher education institutions. Previous studies have used various machine learning methods such as Decision Trees, Neural Networks, Support Vector Machines, etc. in these predictions. The problem that occurs is that even though various machine learning methods have been used, there are still limitations in the accuracy and efficiency of predicting student admissions, The problem in question can be given a real example of a case that occurred. So with this problem the aim is to develop a more effective methodology in predicting student permits, with recommendations from an intelligent combination of two computational techniques Naive Bayes (NB) and Particle Swarm Optimization (PSO). This research methodology includes data collection, NB model development and model partnership with PSO. Student graduation data is used in model testing with evaluation based on metrics such as accuracy and Area Under the Curve (AUC). The results showed a significant increase in accuracy to 86.94% from 83.30% and AUC value from 0.860 to 0.884 when using the combination of NB and PSO compared to NB without either. The integration of NB and PSO has been proven to increase effectiveness in classifying student graduation prediction cases. This research opens up opportunities for the practical application of technology in the education sector and emphasizes the importance of using effective optimization and feature selection techniques in improving prediction results.]]>
<![CDATA[APPLICATION OF CANNY OPERATOR IN BATIK MOTIF IMAGE CLASSIFICATION WITH CONVOLUTIONAL NEURAL NETWORK APPROACH ]]>
<![CDATA[Iwan Jaya Bakti]]>;
<![CDATA[Hendrastuty, Nirwana]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 3 (2024): JUTIF Volume 5, Number 3, June 2024 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.3.1894
<![CDATA[Batik, as Indonesia's cultural heritage, has high artistic value and has a variety of unique motifs.. The main focus of this research is to solve the problem of the complexity and diversity of motifs found in Indonesian batik culture. The Canny operator is used as a first step to extract the edges of batik motifs, with the aim of improving the quality of feature extraction before entering the classification stage using CNN, specifically by using the DenseNet121 model. The dataset of this study was obtained through the Kaggle platform, published by Dionisius Darryl Hermansyah. The platform consists of 983 images (.jpg) with 20 different Indonesian batik motifs. Pre-processing includes the use of Canny for edge detection and data augmentation to increase the diversity of the dataset. Next, variations in the number of epochs and batch size were used to train the model. The results show that in the first test, the use of the Canny operation gives a higher confidence level in the model. In the model with Canny, there is a 1.6% increase in accuracy (33.57% with Canny and 31.97% without Canny). In addition, there are differences in the level of confidence in some batik classes. For example, the "batik mega mendung" class shows an increase in confidence of 66.57% with Canny (88.53% with Canny and 21.96% without Canny), while the "batik sekar" class shows a decrease in confidence of 12.09% with Canny.]]>
