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.
Articles
962 Documents
<![CDATA[IMPLEMENTATION OF INTERNSHIP DATA MANAGEMENT APPLICATION WITH PROTOTYPE METHOD AND USER ACCEPTANCE TEST METHOD ]]>
<![CDATA[Laura Mahendratta Tjahjono]]>;
<![CDATA[Gladys Greselda Gosal]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.304
<![CDATA[Universities generally have programs that offer students internship opportunities in departments within the university. In several universities especially Universitas Ciputra, internships in departments within these universities are mandatory activities for scholarship recipient students. This internship activity involves many parties, including students implementing internships, departments that provide internship vacancies and also student bureaus that monitor the implementation of internships. The obstacle faced in this activity is the difficulty of fulfilling internship vacancies with students who have interests, abilities and profiles that match the requirements of internship vacancies. The student bureau also has difficulty monitoring the progress of the implementation of internship activities in the field. The purpose of this research is to provide a solution to the problems faced in this internship in the form of a website application developed using the Prototype Model method using the Laravel framework and tested using the User Acceptance Test (UAT) method. The result of this research is a website prototype that can be used. The results of the UAT test show that the application made can help solve problems in this internship activity with a user satisfaction level of up to 96%.]]>
<![CDATA[IMPLEMENTATION OF STEGANOGRAPHY ON DIGITAL IMAGE WITH MODIFIED VIGENERE CIPHER ALGORITHM AND LEAST SIGNIFICANT BIT (LSB) METHOD ]]>
<![CDATA[Gilang Miftakhul Fahmi]]>;
<![CDATA[Khairunnisak Nur Isnaini]]>;
<![CDATA[Didit Suhartono]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.340
<![CDATA[Digital image can be utilized as a media to hide messages. There should be a special treatment in securing the messages so that the information accessibility can be controlled. Hiding messages to an image can be conducted using steganography. It can be combined with cryptography algorithms in order to make it harder to be accessed by unauthorized parties. The modification of cryptography algorithms can improve the confidentiality of the message content. This research is aimed to know the implementation of steganography in desktop applications using Least Significant Bit (LSB) that is combined with the modification of Vigenere Cipher algorithms. The developed software namely waterfall supports the creation of applications. The result of the research shows that the encrypted picture will change into gray or display in grayscale so that the hidden message will be more difficult to be accessed by the attacker. The encrypted picture will also have a bigger size file than the original version and the extended file. The LSB method will work precisely according to the formula of the modified cryptography algorithm. The further research is suggested to focus on the variation of media for content message and the picture format in their encryption.]]>
<![CDATA[DECISION SUPPORT SYSTEM SELECTING CRYPTOCURRENCY EXCHANGE USING AHP METHOD ]]>
<![CDATA[Dewi Monica]]>;
<![CDATA[Wahyu Tisno Atmojo]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.467
<![CDATA[Cryptocurrency is a digital currency that functions as a standard currency and can be traded virtually without service fee and have a reliable institution. Investors and traders are interested in buying or acquiring cryptocurrencies and expect to make a profit when selling them. Apart from mining, cryptocurrencies can obtain by buying through cryptocurrency exchanges. The cryptocurrency exchange is helpful as an intermediary for buying and selling crypto assets. There are many types of cryptocurrency exchanges circulating, and it makes users have to select carefully the exchanger they will use. Based on this problem, a decision support system is needed to facilitate the decision-making. The method used in this research is the Analytical Hierarchy Process (AHP). This method is selected because it helps multi-criteria decision-making, solves complex problems into small forms, and receives input from human understanding by defining problems, making hierarchies, conducting comparative assessments, determining priorities, and calculating consistency values. The final result of this research using the AHP method can be seen that Binance is the most recommended cryptocurrency exchange to be used for investing or trading because it earns a percentage of 35.34%, followed by FTX at 28.35%, Huobi Global at 18.05%, Gate.io at 6.96%, KuCoin at 5.76%, and Indodax 5.55%. The results of this calculation are obtained by calculating the priority criteria and alternatives.]]>
<![CDATA[APPLICATION OF MULTI FACTOR EVALUATION PROCESS (MFEP) METHOD FOR THE SELECTION OF BUILDING MATERIAL SUPPLIERS ON MAHAKARYA SUKRI PERKASA (MSP) CIREBON ]]>
<![CDATA[Erwin Sudrajat Rubiyanto]]>;
<![CDATA[Faisal Akbar]]>;
<![CDATA[Mohammad Fahlevvi]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.503
<![CDATA[The property sector is growing along with the increasing need for housing by people in Indonesia. Mahakarya Sukri Perkasa (MSP), is one of the companies engaged in property and housing development. Supplier selection is one of the essential aspects that ensure the smooth operation of the company. From January to May 2021, MSP received 10 consumer complaints from 60 housing development units. Consumers complained that the housing that had been built and occupied suffered damage to certain parts after several months of use. One of the causes of damage is that the quality of the building materials used is not good. This happens because when choosing a supplier for the purchase of building materials, the MSP decides on the cheapest price list of goods. If consumer complaints increase continuously, it will of course result in a decrease in the level of consumer confidence which will reduce MSP income. MSPs need a decision support system that can produce detailed supplier recommendations. The calculation method used in this study is MFEP (Multi-Factor Evaluation Process). There are 5 assessment criteria used, namely price, quality, the diversity offered, supplier response, and delivery time. The results of highest Weight Evaluation test results are 0.86 obtained by Cirebon Mega Bangunan (CMB) with an initial weight of 0.6 price factors, quality 1, the diversity offered 1, supplier response 1, and delivery time 0.6.]]>
<![CDATA[IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK WITH BACKPROPAGATION ALGORITHM FOR RATING CLASSIFICATION ON SALES OF BLACKMORES IN TOKOPEDIA ]]>
<![CDATA[Dalfa Habibah Nurul Aini]]>;
<![CDATA[Dian Kurniasari]]>;
<![CDATA[Aang Nuryaman]]>;
<![CDATA[Mustofa Usman]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.539
<![CDATA[The rating assessment classification contains feedback from consumers, which is given in the form of stars which aims to assess a product. However, the amount of data in the classification process often have differences in each class or is called an imbalanced dataset. These problems can affect the classification results. An imbalanced dataset can be overcome by applying random oversampling. To classify the rating assessment, this study proposes the Neural network method, which has a good accuracy level with the backpropagation algorithm and applies random oversampling to overcome the unbalanced amount of data. The results indicate that the neural network method with the backpropagation algorithm can classify the available data with an accuracy level of 85%. The application of resampling data using random oversampling and determining the amount of distribution of training data, testing data, number of epochs and the correct number of batch sizes affect the results obtained.]]>
<![CDATA[INDIVIDUAL IDENTIFICATION BY IRIS USING HISTOGRAM OF ORIENTED GRADIENT (HOG) AND BACKPROPAGATION NEURAL NETWORK ]]>
<![CDATA[Widya Alisya Kusuma Ningrum]]>;
<![CDATA[Iwan Iwut Tritoasmoro]]>;
<![CDATA[Sofia Saidah]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.558
<![CDATA[The eye’s iris biometrics is a type of biometric for individual identification that is more stable than other types of biometrics because a person's iris eye’s has a delicate fiber pattern and unique characteristics. Especially with the rapid development of the times, the need for identity recognition systems is also increasing. Introducing individuals in traditional ways is still less effective than biometric systems because, compared to conventional methods, biometric systems are safer and are not easily stolen, imitated, or accessed by any unauthorized person. In this research has been carried out by designing a simulation system for individual identification through iris eyes images using the Histogram of Oriented Gradien (HOG) method for image extraction. They were continued with classification using Artificial Neural Network (ANN) Backpropagation. The dataset used is primary data taken directly through smartphone cameras from 30 individuals.Based on the test results and analysis of the Histogram of Oriented Gradien method using an image size of 128×128 pixels, parameters of Cell Size 16×16 cells, Bins Numbers 12, Size Block 2×2 cells, L2-Hys normalization scheme, and JST backpropagation classification with Random state value 1, Learning Rates 0.001, Epoch 200, Hidden Layer 100 with the system's sigmoid activation function can produce a performance system with the most significant performance accuracy of 91.93% , using 1500 training data and 1500 iris eyes image test data.]]>
<![CDATA[TONE DETECTION ON TERANIKA MUSICAL INSTRUMENT USING DISCRETE WAVELET TRANSFORM AND DECISION TREE CLASSIFICATION ]]>
<![CDATA[Fadia Qothrunnada]]>;
<![CDATA[Sofia Saidah]]>;
<![CDATA[Bambang Hidayat]]>;
<![CDATA[Tasya Busrizal Putri]]>;
<![CDATA[Darwindra]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.570
<![CDATA[Musical instruments are one of the cultures that must be preserved. Teranika is one of the traditional musical instruments from the Majalengka area, which is made of clay. Currently, the manufacture of conventional musical instruments is still done manually, so there are still differences in the tone produced. Meanwhile, the quality of a musical instrument is determined by the accuracy of the technique. Therefore, we need a system that can accurately detect the method's accuracy. The author designed a tone detection system for Teranika musical instruments to help artisans carry out quality control. This system will detect whether or not the musical instrument is successfully matched with the right tone and agent. The technique contained in this musical instrument is Do Re Mi Fa So La Si Do high. To overcome these problems, the author makes this tone detection system using the Discrete Wavelet Transform method and the Decision Tree classification. The working principle of this system is that the recorded sound of musical instruments will be transmitted to this system. Then the sound will be processed as input and matched with the essential voice in the database. The output of this system produces samples according to the sampling frequency used. The test results show the best results at decomposition level 6, a thresholding value of 0.05, and a Fine Tree classification type with an accuracy of 87.5%]]>
<![CDATA[MACHINE LEARNING TO CREATE DECISION TREE MODEL TO PREDICT OUTCOME OF ENTERPRENEURSHIP PSYCHOLOGICAL READINESS (EPR) ]]>
<![CDATA[Nesi Syafitri]]>;
<![CDATA[Syarifah Farradinna]]>;
<![CDATA[Wella Jayanti]]>;
<![CDATA[Yudhi Arta]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.590
<![CDATA[This study aims to create a decision tree model using machine learning to predict psychological readiness for entrepreneurship in college graduates. This research was conducted through several stages of research. In the early stages, a survey was conducted on 700 students from several universities in Riau aged between 17-25 years. The survey was conducted using the Entrepreneur Psychology Readiness (EPR) instrument. Furthermore, the survey data was validated and obtained 604 valid data to be used in forming machine learning models The urgency of this research is to find a number of decision rules from the best decision tree model to be used in building AI-based counseling applications in measuring entrepreneurial psychology readiness for college graduates. In this research, the decision tree model that is formed is divided into 2 models, namely: decision tree with pruning model and decision tree with unpruning. The pruning decision tree model produces 180 decision rules, while the unpruning model produces 121 decision rules. Good accuracy results are obtained in the pruned decision tree, which is above 99% in the use training set mode, and 82.87% in the percentage split mode. Meanwhile, the accuracy results on the unpruned decision tree are 90.18% with the use training set mode test, and 80.38% in the percentage split mode. The decision tree model with pruning technique has better performance than the unpruning decision tree model.]]>
<![CDATA[A NEW MODEL FOR HYDROPONIC LETTUCE NUTRITION ADAPTIVE CONTROL SYSTEM BASED ON FUZZY LOGIC SUGENO METHOD USING ESP32 ]]>
<![CDATA[Andi Baso Kaswar]]>;
<![CDATA[Ridwan Daud Mahande]]>;
<![CDATA[Jasruddin Daud Malago]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.626
<![CDATA[In the last few years, the terms Smart Agriculture, Smart Farming, Urban Farming, or Precision Farming have been increasingly recognized and growing rapidly. Hydroponics is one part that is currently a trend, both in industrial or household scale businesses and hobbies. One of the most important things to consider in maintaining the quality of hydroponic plant growth is the concentration of nutrients in the water. A series of studies have been conducted to improve the quality of hydroponic plants. However, the developments that have been carried out have not focused on optimal nutritional control. The previous hydroponic plant nutrition control system still used conventional methods, namely the use of a rule base with firm values , and did not consider the quantity and quality of water. Therefore, this study proposes a new model for an adaptive control system for hydroponic lettuce nutrition based on the Fuzzy Logic Sugeno method using ESP32. The fuzzy logic Sugeno method is used to create a new model of the inference system for determining the amount of nutrient dosage based on supporting data obtained from sensors installed on hydroponic growing media. Compared with the conventional method, the resulting test results show that the proposed method can adapt the amount of added nutrients, provide optimal nutrient addition output, and prevent excess nutrient additions that can potentially accumulate toxic ions in water that degrade water quality.]]>
<![CDATA[COMPARISON OF K-NEAREST NEIGHBOR AND NAIVE BAYES METHODS FOR CLASSIFICATION OF NEWS CONTENT ]]>
<![CDATA[Andi Tejawati]]>;
<![CDATA[Anindita Septiarini]]>;
<![CDATA[Rondongalo Rismawati]]>;
<![CDATA[Novianti Puspitasari]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 4 No. 2 (2023): JUTIF Volume 4, Number 2, April 2023 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2023.4.2.676
<![CDATA[With the development of technology, news reading via the internet or digital tends to increase. In addition, there are about 300 to 400 news articles in one month and many categories of news articles in a web portal. It makes the editor's performance more and more because an editor must be able to edit articles from various channels and at the same time have to categorize articles one by one manually into several specified categories. This study aims to compare the K-Nearest Neighbor (KNN) and Naive Bayes methods to classify news content in order to obtain the best method. The data used in this study are news articles from the web portal kaltimtoday.co from January 2022 to March 2022. Therefore 576 data are obtained. The results showed that the application of the KNN and Naive Bayes methods could be used to classify news content. The KNN method is able to produce a higher accuracy value than Naïve Bayes, reaching 86% and 51% with test data of 100 news articles.]]>
