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 SYSTEM DESIGN USING CUTOMER RELATIONSHIP MANAGEMENT (CRM) METHOD AT PAGLAK PETUNG CAFE AND ART IN BANYUWANGI DISTRICT ]]>
<![CDATA[Nur Indahsari, Luluk]]>;
<![CDATA[Yunita, Irma]]>;
<![CDATA[Fatah, Zaehol]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.2263
<![CDATA[The development of information and communication technology (ICT) has transformed the business world. The success of a cafe is now measured not only by its profits but also by its ability to build long-term customer relationships. Customer Relationship Management (CRM) is a strategy for building and maintaining good relationships with customers. Paglak Petung Cafe and Art in Banyuwangi faces customer management challenges as the number of customers increases. This research aims to design and build a CRM-based information system for the cafe to enhance the efficiency of managing customer data, orders, and promotions. The findings show that the developed system can improve the customer experience and provide a competitive advantage for the cafe. The system also facilitates management in making more accurate data-driven decisions]]>
<![CDATA[STATISTICAL DATA SERVICE SYSTEM (SIPEDAS) IN BPS NORTH SULAWESI PROVINCE WEBSITE-BASED ]]>
<![CDATA[Pandoh, Kevin Mclaren]]>;
<![CDATA[Rantung, Vivi Peggie]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.2265
<![CDATA[The Central Bureau of Statistics (BPS) is important in providing high-quality statistical data to various parties. The demand for accurate and timely data is increasing in this digital era. This research aims to develop a Website-Based Statistical Data Service System (SIPEDAS) application using the Rapid Application Development (RAD) method to speed up design and ensure the system meets user needs. The RAD method consists of four stages in application development: requirements planning, system design, development process, and implementation. Data collection was conducted through interviews with mentors and sourcing data from the BPS WebAPI. Following these stages can produce an application that meets user expectations. After testing, it can be concluded that this application makes it easier for users to search for information, news, infographics, and publications needed without having to visit the North Sulawesi BPS Office directly.]]>
<![CDATA[ANDROID-BASED GARBAGE MANAGEMENT APPLICATION USING K-MEANS ALGORITHM ON RT 03/02 KEL. KARAWACI BARU ]]>
<![CDATA[Abid, M. Nur Rois]]>;
<![CDATA[Artanti, Sarah Camilla]]>;
<![CDATA[Adiyati, Nita]]>;
<![CDATA[Junaedi, Edi]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.2274
<![CDATA[Technological advances have brought significant changes in human life, one of which is the facilitation of access to information. Despite this, garbage management remains an important issue that requires serious attention. Without practical management efforts, the negative environmental impact will continue to increase. Therefore, the study aims to develop an Android-based waste management application using the Waterfall methodology approach and the K-means algorithm method to allow users to group the type of garbage according to its characteristics so that the waste management process can be done more systematically and efficiently. From the application design and testing results, it was concluded that this waste management application can serve as an effective tool in helping people manage their garbage more efficiently. With this digital platform, it is expected that public awareness of the importance of garbage management can be increased and contribute to the maintenance of hygiene and the health of the environment. Thus, the Android-based waste management application has great potential to be a relevant solution in dealing with the problem of waste management. With this digital approach, it is expected that people can be more effective in regulating and utilizing garbage and actively participate in efforts to maintain environmental sustainability for generations to come.]]>
<![CDATA[FORENSIC ANALYSIS OF PHISHING ATTACKS: INVESTIGATIVE APPROACH ]]>
<![CDATA[Kainde, Quido Conferti]]>;
<![CDATA[Tambanaung, Josua Setdefit]]>;
<![CDATA[Inkiriwang, Valent Tio]]>;
<![CDATA[Mile, Alexandra Anrala Putri]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.2294
<![CDATA[Phishing attacks continue to pose a significant threat to cybersecurity, with perpetrators becoming increasingly sophisticated in crafting convincing fraudulent methods. This article examines the forensic analysis process used to effectively investigate phishing attacks. Through a review of existing literature, the author understands the workings of phishing and analyzes real cases that have occurred, followed by data collection using secondary sources. Using theories and insights gained from literature studies, the author analyzes and identifies important aspects of the conducted research data. A content analysis method is employed to analyze the data, determining the steps for prevention and investigation of phishing attacks. In this analysis, thematic and textual methods are applied to gather crucial components of a phishing attack. The analysis results indicate that forensic approaches and a deep understanding of phishing mechanisms can help protect data and significantly reduce the impact of phishing attacks. This article concludes by providing practical recommendations to enhance readiness in facing future phishing attacks.]]>
<![CDATA[WEB-BASED CRM APPLICATION WITH CUSTOMER ELIGIBILITY SIMULATION FEATURE USING EXPONENTIAL COMPARISON METHOD AT KOPERASI NUSANTARA MANDIRI ]]>
<![CDATA[Benyamin, Evan]]>;
<![CDATA[Chasanah, Nur]]>;
<![CDATA[Ekowati, Nur Alfi]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.2305
<![CDATA[In the competitive and dynamic digital era, cooperatives must have systems that accommodate both operational needs and customers to improve service quality and customer satisfaction. However, Koperasi Nusantara Mandiri in Bandung Regency does not yet have a system that encompasses both aspects, rendering the cooperative's services ineffective and less competitive. Therefore, the cooperative requires a Customer Relationship Management (CRM) system to assist potential customers by providing loan eligibility calculation simulations. This research aims to implement a decision support method in a system using the waterfall methodology, which includes the stages of requirements, design, implementation, testing, and maintenance to develop a web-based CRM application. The application is designed and developed to help the cooperative manages the customer data, ease the business processes, and enhance effectiveness in both operations and customer analysis. Testing is conducted using the black box technique to ensure the application meets the specified requirements. The research results indicate that the developed CRM application functions well and meets the needs of Koperasi Nusantara Mandiri, thereby increasing the cooperative's operational effectiveness.]]>
<![CDATA[DEVELOPMENT OF A STOCK PURCHASE RECOMMENDATION SYSTEM APPLICATION ]]>
<![CDATA[Maruanaya, Greghar Juan Tjether]]>;
<![CDATA[Triyono, Gandung]]>;
<![CDATA[Maruanaya, Rita Fransina]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.2322
<![CDATA[Investing in stocks has become a significant source of passive income through indirect earnings with minimal activity. Choosing stocks for investment requires careful analysis. The Indonesia Stock Exchange has 866 listed stocks, divided into several indices, including IDXBUMN20, which includes 20 stocks from state-owned enterprises (BUMN), regional-owned enterprises (BUMD), and their affiliates. This index helps traders monitor the performance of BUMN stocks. The list of IDXBUMN20 stocks includes ADHI, ANTM, BBNI, AGRO, BBRI, BRIS, BBTN, BJBR, BMRI, MTEL, ELSA, JSMR, PGAS, PTBA, PTPP, SMGR, TINS, TLKM, WIKA, and WSKT. Traders need recommendations to select stocks with positive trends. Forecast analysis becomes a potential solution to provide references for stocks with positive trends. This study applies the Simple Moving Average (SMA) method to forecast the prices of IDXBUMN20 stocks. The SMA will be measured using 30, 40, 50, and 60-day periods as indicators. This method is chosen for its ability to identify stock price trends by calculating the average closing price over a specific period. Therefore, forecasting results using SMA will provide a more accurate picture of stock price movements and aid in making better investment decisions. From the forecasting results using the SMA method, recommendations for the top five stocks showing positive trends will be obtained. Subsequently, to determine which stock is most recommended, a stock recommendation model will be developed using the Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method. TOPSIS will consider various criteria such as average frequency, Price Earning Ratio (PER), Price Book Value (PBV), Return on Assets (ROA), and Return on Equity (ROE). The results showed that the most recommendable stocks based on the positive trend of price movements are SMGR for indicator 30 and TLKM for indicators 40, 50 and 60. Therefore, it can be concluded that the most recommended stock is TLKM (PT Telkom Indonesia (Persero) Tbk).This recommendation model is expected to help traders select the stocks with the best investment potential, maximizing profits and minimizing investment risks in the capital market.]]>
<![CDATA[ANDROID-BASED UTILITY FACILITY MAINTENANCE APPLICATION USING DYNAMIC SYSTEM DEVELOPMENT METHODOLOGY (DSDM) ]]>
<![CDATA[Edison Siregar, Master]]>;
<![CDATA[Mayatopani, Hendra]]>;
<![CDATA[Kurniawan, Rido Dwi]]>;
<![CDATA[Prathama, Dhion Angga]]>
<![CDATA[ Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024 - SENIKO ]]>
Publisher : <![CDATA[Informatika, Universitas Jenderal Soedirman ]]>
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DOI: 10.52436/1.jutif.2024.5.4.2371
<![CDATA[In the ever-evolving digital era, the maintenance of utility facilities is becoming increasingly important to ensure smooth operations and services. Utility facilities include critical infrastructure such as waterways, electricity, and communication networks that must be properly maintained to maintain their function and reliability. The main contribution of this research is the application of DSDM in the development of related applications to improve the maintenance efficiency of utility facilities. organizational challenges faced in managing maintenance processes effectively, including untimely reporting issues, poor coordination, and lack of integration with company systems. To address this issue, this paper presents the development of an Android-based application designed to streamline and improve the maintenance process of utility facilities. The application leverages the Dynamic Systems Development Methodology (DSDM), known for its iterative and incremental approach, to ensure on-time delivery and adaptability to changing needs. The main goal of the app is to provide facility managers and maintenance personnel with a comprehensive solution through features such as real-time reporting, maintenance scheduling, and task management. By implementing DSDM in the context of utility maintenance, application users can be actively involved in the entire development process, allowing for rapid adaptation to changing needs The results of the development of this application are expected to improve the maintenance management of utility facilities efficiently, encourage preventive maintenance, and optimize the performance of these vital infrastructures.]]>
<![CDATA[OPTIMAL STUDY OF REAL-ESTATE PRICE PREDICTION MODELS USING MACHINE LEARNING ]]>
<![CDATA[Maulana, Ikhsan]]>;
<![CDATA[Siregar, Amril Mutoi]]>;
<![CDATA[Lestari, Santi Arum Puspita]]>;
<![CDATA[Faisal, Sutan]]>
<![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.2024.5.4.2565
<![CDATA[Everyone wants a place to live, especially close to work, shopping centers, easy transportation, low crime rates and others. Pricing must also pay attention to external factors, not just the house. Determining this price is sometimes difficult for some people. Therefore, the aim of this research is to predict real-estate prices by taking these factors into account. Prediction results are very useful for sellers who have difficulty determining prices and also for prospective buyers who are confused when making financial plans to buy a house in the desired neighborhood. The dataset used in this research was obtained from Kaggle and consists of 506 samples with 14 attributes. Several machine learning algorithms, such as Extra Trees (ET), Support Vector Regression (SVR), Random Forest (RF), eXtreme Gradient Boosting (XGB), Gradient Boosting Machine (GBM), Light Gradient Boosting Machine (LGBM), and CatBoost, used to predict real-estate prices. This research uses Principal Component Analysis (PCA) for feature selection techniques in data sets after the preprocessing phase and before model building. The highest accuracy model obtained is CatBoost with GridSearchCV, this model has been cross validated so there is very little chance of overfitting when given new data. The SVR model with a poly kernel uses a Principal Component (PC) of 10 and GridSearchCV gets an R2 Score of 0.87, a very large number close to the score of CatBoost with GridSearchCV.]]>
<![CDATA[IMPLEMENTATION OF DIABETES PREDICTION MODEL USING RANDOM FOREST ALGORITHM, K-NEAREST NEIGHBOR, AND LOGISTIC REGRESSION ]]>
<![CDATA[Pratama, Rio]]>;
<![CDATA[Siregar, Amril Mutoi]]>;
<![CDATA[Lestari, Santi Arum Puspita]]>;
<![CDATA[Faisal, Sutan]]>
<![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.2024.5.4.2593
<![CDATA[Diabetes is a serious metabolic disease that can cause various health complications. With more than 537 million people worldwide living with diabetes in 2021, early detection is crucial to preventing further complications. This research aims to predict the risk of diabetes using machine learning algorithms, namely Random Forest (RF), K-Nearest Neighbor (KNN), and Logistic Regression (LR), with the diabetes dataset from UCI. Previous research has explored a variety of algorithms and techniques, with results varying in accuracy. This research uses a dataset from Kaggle which consists of 768 data with 8 parameters, which are processed through pre-processing and data normalization techniques. The model was evaluated using metrics such as accuracy, confusion matrix, and ROC-AUC. The results showed that Logistic Regression had the best performance with 77% accuracy and AUC 0.83, compared to KNN (75% accuracy, AUC 0.81) and Random Forest ( 74% accuracy, AUC 0.81). These findings emphasize the importance of appropriate algorithm selection and good data pre-processing in diabetes risk prediction. This study concludes that Logistic Regression is the most effective method for predicting diabetes risk in the dataset used.]]>
<![CDATA[PERSONAL PROTCTIVE EQUIPMENT DETECTION FOR OCCUPATIONAL SAFETY AND HEALTH USING YOLOV8 IN MANUFACTURING COMPANIES: DETEKSI ALAT PELINDUNG DIRI (APD) UNTUK KESELAMATAN DAN KESEHATAN KERJA MENGGUNAKAN YOLOV8 ]]>
<![CDATA[Gapur, Abdul]]>;
<![CDATA[Wahiddin, Deden]]>;
<![CDATA[Mudzakir, Tohirin Al]]>;
<![CDATA[Indra, Jamaludin]]>
<![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.2024.5.5.2619
<![CDATA[According to data from BPJS Keltelnagakelrjaan, 265,333 cases of work accidents were recorded in 2022. The use of personal protective equipment (PPE) is very important in reducing and preventing work accidents in the company. Although PPE cannot eliminate all risks, it is possible to minimise the number of work accidents in manufacturing companies. The aim of this research is to automatically select Personal Protective Equipment (PPE) in the form of hard hats and vests and to improve the accuracy results using the YOLOv8 model. With a dataset of 500 helmet and velst images for deltelksi which will be categorised into 4 classes namely hellelm, velst, no-hellelm, no-velst. The dataset used is 500 data, which is then divided into three datasets, namely: training data as much as 70%, validation data as much as 20%, and telst data as much as 10%, from the dataselt telrselbut the best results of testing data values from 50 dataselt the accuracy results obtained are 0.98. It is hoped that with the use of Meltode and accuracy results using Yolo v8, it can be used in companies by detecting Personal Protective Equipment (PPE) with fast and accurate results, so that it can be applied in monitoring the use of PPE in manufacturing companies to reduce the risk of work accidents in manufacturing companies]]>
