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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<![CDATA[IMPLEMENTATION OF THE SIMPLE MULTI-ATTRIBUTE RATING TECHNIQUE (SMART) METHOD FOR SUPPORT SELECTION OF COFFEE SHOP BUSINESS LOCATION ]]>
<![CDATA[Viola Alfheny]]>;
<![CDATA[Ali Ibrahim]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.4.508
<![CDATA[In choosing a business location, a computerized system is needed and can provide effective and accurate information about the business location. Many young entrepreneurs today are starting to try to manage and create a coffee shop business, so the competition in coffee shops is very high. The high competition in the coffee shop business makes it difficult for prospective tenants to determine the most appropriate location to establish a place of business according to their desired needs. In addition, the selection of business locations cannot be chosen arbitrarily because it can cause a shortage of visitors which results in the coffee shop being deserted. Therefore, choosing a strategic place using several criteria is needed to support business success. There are twelve criteria that will be used, the criteria are rental price, number of competitors, parking area, cleanliness, building area, supporting business, road distance, road access, population density, pedestrian traffic, population income, and the center of the crowd. This study aims to help prospective tenants who will open a place of business in the city of Bandar Lampung. The method used in this research is the Simple Multi Attribute Rating Technique (SMART). The SMART method is used because it is a multi-attribute decision-making method where the alternative consists of a set of criteria, with weights to determine how important one criterion is with another. The results obtained in this study are a decision support system for choosing a strategic coffee shop business location, making it easier for prospective tenants to choose the right business location for the development of a coffee shop business in Bandar Lampung.]]>
<![CDATA[ANALYSIS AND DESIGN OF DATA WAREHOUSE BASED ON SNDIKTI USING DATA WAREHOUSE LIFE CYCLE METHOD AT UNSOED ENGINEERING FACULTY ]]>
<![CDATA[Nurul Hidayat]]>;
<![CDATA[Dadang Iskandar]]>;
<![CDATA[Lasmedi Afuan]]>;
<![CDATA[Arief Kelik Nugroho]]>;
<![CDATA[Nandha Arwiansyah]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 3 (2022): JUTIF Volume 3, Number 3, June 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.3.514
<![CDATA[The National Standard for Higher Education (Standar Nasional Pendidikan Tinggi or SNDIKTI) is a standard unit that includes the National Education Standards, plus the Research Standards, and Community Service Standards. Based on the policy in the Regulation of the Minister of Education and Culture (Peraturan Menteri Pendidikan dan Kebudayaan or Permendikbud) No. 3 of 2020 regarding SNDIKTI, Jenderal Soedirman University (Unsoed) Architecture needs to prepare data/ information for analysis based on SNDIKTI 2020. The data is obtained from several internal systems and manual recapitulation within a predetermined period of time. Currently the architecture already has many information systems, but it is still difficult to manage the existing data. So it is important for the architecture to have an important repository to minimize human errors and data inconsistencies. So to perform complex data management, a data warehouse is needed. In this study, the data warehouse design uses the Data Warehouse Life Cycle (DWLC) method with the data warehouse model used is the star schema model. The results of the data warehousing process are in the form of a dashboard, Online Analytical Processing (OLAP), and reports intended for the executives of the Unsoed Faculty of Engineering. The output is presented using a BI (Business Intelligence) tool called Knowage.]]>
<![CDATA[AUGMENTED REALITY FOR UNIVERSITAS ISLAM NEGERI WALISONGO'S PROFILE USING AGILE METHODOLOGY ]]>
<![CDATA[Siti Nur’aini]]>;
<![CDATA[Muhammad Naufal Muhadzib Al-Faruq]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.4.519
<![CDATA[The use of Information Technology for the process of delivering information has grown so rapidly. One of them is Augmented Reality. Augmented Reality is widely implemented for various things, including in the world of education, health, military, entertainment and many others. Augmented Reality is a technology that combines virtual objects and the real world in real-time and interactively. This research developed an Augmented Reality Application that can be used to introduce Universitas Islam Negeri (UIN) Walisongo more broadly, attractively, interactively, and competitively. This application is named AR UINWS. Agile methodology was chosen to develop AR UINWS. The results show that the agile methodology is suitable to be implemented because of its flexibility, so that the needs of developing applications can be easily adapted. AR UINWS works well on all types of android devices that have a minimum camera resolution of 720x1280 pixels. AR UINWS can detect markers if the marker surface is visible at least 65% of the total marker surface area. This application can detect markers of various sizes as long as the background is light. The size of the marker that can be detected is 1.5x2 cm with the minimum distance between the marker and the android device is 1 5cm. While the largest marker size being tested is 15x23cm with the minimum distance between the marker and the android device is 150 cm.]]>
<![CDATA[WEBSITE BASED EMPLOYEE ACCEPTANCE INFORMATION SYSTEM AT PT NOTO TEKNOLOGI INDONESIA ]]>
<![CDATA[lasmedi afuan]]>;
<![CDATA[Nurul Hidayat]]>;
<![CDATA[Bangun Wijayanto]]>;
<![CDATA[Indah Cahya Febriani]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.5.524
<![CDATA[The development of information technology is currently growing very rapidly, many companies want to improve their work processes by using information systems to process company data more quickly and efficiently. The process of accepting prospective employees at PT Noto Teknologi Indonesia is still done manually, i.e. prospective employees must register and deliver job application files to the office. To find out the results of the selection of employee recruitment, prospective employees still get information via WhatsApp. This makes the acceptance of new employee candidates less effective and efficient because it will take a lot of time and the possibility of data errors. So in this study a website based recruitment information system was created to facilitate the process of accepting new employees. The method used in making this system is the waterfall method where this method has 5 stages, namely user needs analysis, system design, implementation, testing and maintenance by PT Noto Teknologi Indonesia. The results of the black-box test show valid results for all features which indicate that this system is as expected. From the results of black-box testing, it can be concluded that this system is feasible to use as a tool to facilitate the process of accepting new employees at PT Noto Teknologi Indonesia.]]>
<![CDATA[DISASTER RESPONSE MODELING BASE ON LANDSLIDE EARLY WARNING USING CASE MANAGEMENT MODEL AND NOTATION ]]>
<![CDATA[Sarah Ayu Ekamas]]>;
<![CDATA[Hanson Prihantoro Putro]]>;
<![CDATA[Teduh Dirgahayu]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.5.528
<![CDATA[There are a few handling steps in the emergency response to landslides that need thorough explanation. The flexibility of emergency response situations is ineffectively supported by traditional modeling methodologies because they are excessively inflexible. Companies have traditionally modeled their business processes using the Business Process Management Approach and Notation (BPMN) model. For design case management, such as the emergency reaction to a landslide disaster, BPMN modeling is unsuitable. because the BPMN modeling focuses how business processes flow inside a company. The Case Management Model and Notation (CMMN), the newest modeling approach from the Object Management Group (OMG), was launched in 2013 with the purpose of completing the BPMN modeling approach. The unstructured and adaptable CMMN claims to be able to handle urgent situations. This study's intention is to develop a CMMN model of a landslide emergency reaction scenario based on an emergency alert from an Early Warning System (EWS) sensor. In order to acquire the qualitative data for this study, the researcher first conducted a literature review. Then used the interview and observation methods to gather data, and from this data, we created the model using the CMMN modeling approach. The Yogyakarta Special Region Disaster Management Agency's (BPBD DIY) data flow of a disaster management information system, which was already operational, was analyzed by researchers. Then, the researchers used CMMN to model the data in order to find out opportunities to improve the disaster management information system already in use at BPBD DIY. Two CMMN models—the BPBD DIY disaster management information system model and the recommendation model for system improvements—were created in this study. The analysis of the current disaster management information system model resulted in the recomendation of this model. A prototype of feature recommendation is created as part of this research and given to specialists in natural disasters for model validation.]]>
<![CDATA[USABILITY ANALYSIS OF THE WEBSITE OF THE SOUTH SUMATERA PROVINCIAL LIBRARY SERVICE USING THE WEBUSE METHOD ]]>
<![CDATA[Tri Oktarina]]>;
<![CDATA[Ana Orija]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.5.540
<![CDATA[The South Sumatra Provincial Library Service is an institution that assists the Governor in organizing Government in the field of Education and uses the website to convey information to the public. The importance of usability is to measure the level of quality of the system with the intention of being easy to learn and then easy to use, encouraging users to use the system to achieve the goals of the user. Each website has a different usability level, the higher the usability value, the easier the website is for users to understand. This study aims to determine or measure the Website of the South Sumatra Provincial Library Service using the WEBUSE method. In this study, researchers used the WEBUSE method, there are 4 categories of usability (1 Content, organization and readability. (2)Navigation and links. (3)User interface design. (4)Performance and effectiveness. Data analysis using validity test, reliability using SPSS version.25. The results of the calculation of the WEBUSE method were processed with Ms.Excel 2007. The results of the overall study of the South Sumatra Provincial Library Service showed that the highest score or value was obtained by the Content, organization and readability variable with usability points of 0.80 usability level Excellent while the lowest score was in the Performance and category. usability effectivity point is 0.78 with Good usability level for the website usability level is at Good level.]]>
<![CDATA[APPLICATION OF DATA MINING FOR PREDICTION OF LONG COVID ON COVID-19 SURVIVAL WITH FEATURE SELECTION AND NAÏVE BAYES METHOD ]]>
<![CDATA[Siti Rokhmah]]>;
<![CDATA[Nendy Akbar Rozaq Rais]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.5.561
<![CDATA[Since it was declared a global pandemic in March 2020, Corona Virus Disease (Covid-19) has become the world's attention, a lot of research has focused on all things related to Covid-19. Covid-19 is an infectious disease caused by the acute respiratory syndrome Corona virus 2 (SARS-CoV-2). Several studies have shown that the symptoms of COVID-19 persist for a long period of time even though they have been declared cured of Covid-19, this is known as Long Covid. Complaints that are often experienced by patients who progress to Long Covid are fatigue, headaches, coughs, runny noses, sleep disturbances and even shortness of breath. Several risk factors for the occurrence of Long Covid include age, gender, patient congenital disease, condition during acute infection, ethnicity and the patient's Body Mass Index (BMI). To anticipate the occurrence of long covid, it is necessary to have a risk prediction system for the occurrence of long covid in covid-19 patients, this aims to anticipate and prepare for early handling and prevention efforts for covid-19 patients who are at risk of experiencing long covid. Prediction of the risk of long covid can be done by classifying long covid risk factors by utilizing data mining. The purpose of this study is to classify symptom data and patient history, so that data patterns can be obtained that can be used as predictions to estimate the risk of the occurrence of Long covid-19 in Covid-19 survivors. This study uses the Naïve Bayes classification method by classifying data based on the Long covid risk factor and the feature selection information gain method which is used as a technique in attribute selection to optimize the nave Bayes algorithm. The results of this study have a real contribution to the development of science and technology. The concept of the resulting prediction data pattern can be used as a reference in developing early detection of the risk of the occurrence of Long Covid.]]>
<![CDATA[APPLICATION OF LEXICON BASED FOR SENTIMENT ANALYSIS OF COVID-19 BOOSTER VACCINATIONS ON TWITTER SOCIAL MEDIA USING NAÏVE BAYES METHOD ]]>
<![CDATA[Muhamad Fahmi]]>;
<![CDATA[Syarif Hidayat]]>;
<![CDATA[Ahmad Fathan Hidayatullah]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.4.565
<![CDATA[To combat the Covid-19 epidemic, the government issues laws governing vaccination implementation. Health Minister Number Ten of 2021 issued the regulation. This program raises advantages and disadvantages, necessitating examination through feedback. The opinions and narratives that individuals share on social media sites like Twitter can be used to get feedback. This work seeks to construct a model to assess public opinion of the Covid-19 Booster Vaccination by using the Lexicon Based technique to identify sentiment on tweet data. Naïve Bayes and logistic regression are the classification techniques employed in this study. The comparison of the two methods' findings reveals that Logistic Regression, with an accuracy of 72%, is superior to Naïve Bayes, which has an accuracy of 70%. There were 607 tweet messages from Twitter that were processed. From January 1 to July 30, 2022, the model was tested for its ability to interpret public opinion on Twitter. The model found that people's attitudes toward the COVID-19 booster shot tended to be favorable. It can be developed by including datasets for additional research. For further research, it can be developed by adding datasets.]]>
<![CDATA[KNOWLEDGE BASED RECOMMENDATION MODELING FOR CLOTHING PRODUCT SELECTION RECOMMENDATION SYSTEM ]]>
<![CDATA[Vihi Atina]]>;
<![CDATA[Dwi Hartanti]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.5.584
<![CDATA[One of the markets which is the largest wholesaler of clothing in Central Java is the Klewer market area and its surroundings. The Simple Inc Store is one of the clothing stores in the area. Simple Inc Store is a large kiosk that sells clothing products in the form of various types of t-shirts, shirts, jackets, sweaters and pants. Sales of products in these stores are still done conventionally, namely customers come directly to the store to choose and buy products. The number of clothing products that are sold makes customers experience difficulties in the process of selecting clothing products. Therefore, it is necessary to develop a recommendation system that can assist customers in choosing clothing products. The purpose of this research is to create a Knowledge Based Recommendation model for the Recommendation System for Selection of Clothing Products. The system development method used in this research is Rapid Application Development (RAD), which consists of stages, namely business modeling, data modeling and process modeling. The recommendation system method used in this research is knowledge based recommendation. Knowledge based recommendation has the advantage of being able to set the level of user priority based on the user's needs for the product by calculating the similarity value between customer needs and clothing product attributes. Knowledge based recommendation modeling for this clothing product selection recommendation system can provide 5 choices of clothing product search attributes, namely brand, price, material, color and size. Based on the results of modeling the knowledge based recommendation method with 20 sample data, it can provide recommendations for clothing products based on the criteria needed by customers by calculating the similarity value between customer needs and the attributes possessed by each clothing product. Clothing products with the highest similarity value will be displayed as a result of clothing product recommendations, namely the highest similarity value of 0.6 is obtained for Maternal t-shirts. The results of this knowledge-based recommendation modeling can be used as a reference in developing a recommendation system for the selection of clothing products.]]>
<![CDATA[APPLICATION OF MACHINE LEARNING IN DETERMINING THE CLASSIFICATION OF CHILDREN'S NUTRITION WITH DECISION TREE ]]>
<![CDATA[Mutammimul Ula]]>;
<![CDATA[Ananda Faridhatul Ulva]]>;
<![CDATA[Mauliza Mauliza]]>;
<![CDATA[Muhammad Abdullah Ali]]>;
<![CDATA[Yumna Rilasmi Said]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 3 No. 5 (2022): JUTIF Volume 3, Number 5, October 2022 ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.20884/1.jutif.2022.3.5.599
<![CDATA[The problem of nutrition for children is a health problem that must be solved by the government. Malnutrition is a very important problem in the development of children, especially during the growth period. Lack of nutritional intake in children will have a negative impact on resistance to the virus. This will risk death caused by malnutrition. There is direct monitoring from the government, hospitals, and health offices in looking at the classification of nutrition in children in a system. This study aims to classify the nutritional status of children using a machine learning model, which then the final result can show the classification of nutritional vulnerability in each patient at the North Aceh Hospital. The stages of the research include the identification of theories about nutritional problems. Second, data collection is in the form of symptoms and diagnosis of disease classification in machine learning implementation. The third is to analyze the data using the research and development (R&D) method according to the classification of children's nutrition. Finally, the implementation of the patient classification model with decision tree into machine learning The variables included in the system include JK(X1), U (X2), BB(X3), TB (X4), and BB (X3), which are the variables that have the most influence on malnutrition in children. The results of this study for testing weight 16, height 9.7, age 33 months, nutritional value 54,23772 which the program output results are normal. Patient Syafira Nisman, weight 9, height 72, age 21 months, suffered from malnutrition. The results of the research on the application of machine learning for the classification of malnutrition using the decision tree method make it easier for patients and hospitals to classify children's nutrition.]]>
