Pascal: Journal of Computer Science and Informatics
Pascal: Journal of Computer Science and Informatics is a national scientific journal that publishes research articles in the field of Computer Science and Informatics which include: Computer Engineering, Information Engineering, Computer Science, Information Systems, Information Technology, Software Engineering, Computer Systems, Computer Networks, Application of Information Technology and Other Fields of Computer Science and Informatics that have not been listed. Pascal: Journal of Computer Science and Informatics is published 2 times a year, and is published by CV. Devitara Innovations.
A Comparative Analysis of the Efficiency of Blockchain Consensus Algorithms: Proof of Work, Proof of Stake, Delegated Proof of Stake, and Practical Byzantine Fault Tolerance
The rapid development of blockchain technology has accelerated the adoption of distributed systems across various sectors, including financial services, supply chain management, the Internet of Things (IoT), and digital government. Consensus algorithms play a fundamental role in blockchain by ensuring transaction validity and data consistency without relying on a centralized authority. Since each consensus mechanism exhibits different characteristics, a comparative analysis is required to identify its strengths and limitations. This study aims to analyze and compare the efficiency of four major blockchain consensus algorithms, namely Proof of Work (PoW), Proof of Stake (PoS), Delegated Proof of Stake (DPoS), and Practical Byzantine Fault Tolerance (PBFT). The research employed a comparative literature study by collecting, selecting, and analyzing relevant scientific publications. The comparison was conducted based on transaction throughput, energy efficiency, communication complexity, transaction finality, network characteristics, and fault tolerance. The results indicate that no single consensus algorithm provides optimal performance across all evaluation parameters. PoW offers high security and decentralization but suffers from high energy consumption and low throughput. PoS provides a balanced trade-off among energy efficiency, security, and scalability, while DPoS improves transaction capacity through a delegated validator mechanism. PBFT achieves high throughput and instant transaction finality but is more suitable for permissioned blockchain environments with a limited number of participating nodes. This study proposes a comparative analysis framework that can serve as a reference for selecting an appropriate consensus algorithm based on blockchain implementation requirements.
Copyright (c) 2026 Pascal: Journal of Computer Science and Informatics
Development and Performance Evaluation of an IoT-Based Smart Irrigation System for Real-Time Soil Moisture Monitoring and Automatic Irrigation
Manual irrigation management often results in watering practices that do not reflect actual soil moisture conditions, leading to inefficient water use and reduced crop productivity. This study aims to design and implement an Internet of Things (IoT)-based Smart Irrigation System capable of monitoring soil moisture in real time while automatically controlling the irrigation process. The research employed a Research and Development (R&D) method using a prototyping approach, including requirement identification, system design, hardware and software implementation, system integration, and performance testing. The proposed system was developed using an ESP32 microcontroller, a capacitive soil moisture sensor, a relay module, a water pump, and an internet-based monitoring dashboard. System performance was evaluated through sensor readings, real-time data monitoring, automatic pump control, response time measurement, and operational stability testing. The results demonstrate that the proposed system successfully monitors soil moisture, transmits data to the dashboard in real time, and automatically controls the irrigation pump based on predefined soil moisture thresholds. The implementation of a threshold with hysteresis mechanism improves pump stability by reducing frequent switching caused by sensor fluctuations. Furthermore, the system exhibits a relatively fast response time and stable operation throughout the testing period. These findings indicate that IoT technology provides an effective solution for developing efficient, practical, and scalable smart irrigation systems suitable for small- and medium-scale agricultural applications.
Development of an Internet of Things (IoT)-Based Plant Monitoring System Using a Capacitive Soil Moisture Sensor, ESP32, Firebase Realtime Database, and a Mobile Application
Soil moisture is one of the most important parameters affecting plant growth because it is directly related to water availability in the growing medium. Conventional soil moisture monitoring is generally performed manually, relying on visual observation, lacking periodic data recording, and making remote monitoring difficult. This study aims to design, implement, and evaluate an Internet of Things (IoT)-based plant monitoring system using a capacitive soil moisture sensor, an ESP32 microcontroller, Firebase Realtime Database, and an Android mobile application. The study employed an engineering research approach using the Prototype development model, consisting of requirements analysis, system design, prototype development, hardware and software integration, and system testing. The prototype was evaluated using 10 chili pepper pots over a period of 14 days with a data acquisition interval of 30 minutes. The results demonstrate that the proposed system successfully measures soil moisture, transmits data to Firebase in real time, and displays soil conditions through the mobile application with an average response time of 2.6 seconds. Accuracy evaluation indicates that the capacitive soil moisture sensor provides a relatively low measurement error, making it suitable for small-scale plant monitoring applications. In addition to displaying soil moisture values, the system automatically classifies soil conditions into dry, normal, and wet categories, enabling users to determine appropriate irrigation schedules more easily. This study contributes a simple, low-cost, and user-friendly IoT-based plant monitoring system that supports the implementation of smart farming for household gardening, educational purposes, and small-scale agricultural applications.
Design and Implementation of IoT-Based Soil Moisture Monitoring and Automatic Irrigation System Using ESP32
Proper soil moisture management plays an essential role in supporting plant growth and improving water-use efficiency. Manual irrigation is still widely practiced and often ignores the actual soil moisture condition, leading to either excessive or insufficient watering. This study aims to design and implement an Internet of Things (IoT)-based soil moisture monitoring and automatic water pump control system using the ESP32 microcontroller. The research employed a Research and Development (R&D) approach through prototype development, including literature review, system requirement analysis, hardware and software design, system implementation, sensor calibration, and performance evaluation. The proposed system integrates a capacitive soil moisture sensor, relay module, 12 V DC water pump, and the Blynk platform for real-time monitoring. A hysteresis control strategy was implemented by setting the lower and upper soil moisture thresholds at 40% and 60%, respectively, to improve pump stability. Experimental results demonstrated that the developed system achieved an average sensor error of 3.42%, an average response time of 2.14 seconds, and maintained soil moisture within the range of 50.9%–54.2% during a seven-day evaluation period. Furthermore, the system reduced water consumption by 31.6% compared with conventional manual irrigation. These findings indicate that the proposed IoT-based system is capable of providing reliable real-time soil moisture monitoring and efficient automatic irrigation, making it suitable for potted plants, home gardens, and small-scale greenhouse applications.
Conceptual Design of an Internet of Things (IoT)-Based Automatic Plant Irrigation System Using ESP8266 NodeMCU and the Blynk Platform
The increasing demand for efficient plant maintenance has accelerated the adoption of Internet of Things (IoT) technologies in smart agriculture. This paper presents a conceptual design of an IoT-based automatic plant irrigation system utilizing the ESP8266 NodeMCU microcontroller and the Blynk platform for remote monitoring and control. The proposed system design includes the selection of hardware components, namely the YL-69 soil moisture sensor, a 5 V relay module, and a DC 5 V submersible water pump, as well as the development of software architecture incorporating automatic irrigation control logic and Blynk widget configuration. The proposed architecture adopts a three-layer IoT model consisting of the device layer, the Wi-Fi communication layer, and the application layer implemented through the Blynk platform. The designed system is intended to automatically activate the water pump when the measured soil moisture falls below a predefined threshold and deactivate it once sufficient soil moisture has been achieved. In addition, users can monitor soil moisture conditions in real time and manually operate the irrigation system through the Blynk mobile application. A comparative analysis of existing IoT-based irrigation studies indicates that the proposed conceptual framework provides a comprehensive integration of hardware architecture, communication mechanisms, software workflow, and user interface design. Furthermore, the selection of ESP8266 NodeMCU and the Blynk platform offers advantages in terms of ease of implementation, low deployment cost, scalability, and user-friendly operation. Although this study is limited to the conceptual design stage without prototype implementation or experimental validation, the proposed framework can serve as a practical reference for future development and implementation of IoT-based automatic irrigation systems.
A SAW-Based Decision Support System for Selecting Final Project Topics in the Informatics Management Department at STMIK Mulia Darma
Selection of Final Project Topics is a crucial stage in the academic process, as it significantly affects the smoothness of project preparation and completion. However, the determination of final project topics often remains subjective and does not systematically consider students’ academic abilities. This study aims to design and develop a Decision Support System for selecting final project topics for students in the Informatics Management Department using the Simple Additive Weighting (SAW) method. The SAW method is employed to evaluate and rank alternative topics based on several criteria, including supporting course grades, student interest, programming skills, system analysis and design capabilities, and the availability of supervising lecturers. The results indicate that the SAW method can provide objective and transparent recommendations for final project topics. Based on the calculation, alternative A4 achieved the highest preference score of 0.962, making it the most recommended final project topic. Therefore, the developed system is expected to assist both students and academic staff in making more effective and structured decisions regarding final project topic selection.
Copyright (c) 2025 Pascal: Journal of Computer Science and Informatics
Design Of Accounting Information System for Transaction Management and Financial Reports at the Medan Pratama Haji Clinic
The rapid development of information technology requires healthcare institutions to digitize their financial data management to make administrative processes more effective and accurate. Medan's Pratama Haji Clinic currently still uses a manual system for recording transactions and preparing financial reports, resulting in frequent reporting delays, recording errors, and difficulties in tracking historical data. Based on these conditions, this study formulates three main problems, namely: how is the manual accounting information system currently implemented at Medan's Pratama Haji Clinic, what are the obstacles faced in managing financial reports manually, and how to design an accounting information system for managing transactions and financial reports. The purpose of this study is to design and build a computer-based accounting information system that can assist the process of recording transactions and preparing financial reports effectively at Medan's Pratama Haji Clinic. The research method uses the System Development Life Cycle (SDLC) with stages of analysis, design, implementation, and testing. Data were obtained through observation, interviews, and documentation. The system was designed using PHP and MySQL with the help of DFD, ERD, and Context Diagram tools. The results show that the system built is able to integrate all financial transaction processes and produce reports automatically, accurately, and efficiently. This system also facilitates management's oversight and decision-making. The study concluded that a computer-based accounting information system can replace manual systems and improve the efficiency of the clinic's finance department. A recommendation for further research is to develop this system with a web-based automated reporting module to make financial information more transparent and accessible.
Optimization of Indoor Navigation Using the A Algorithm and Adaptive Grid (Gridadapte) for Efficient Pathfinding
Optimal path navigation in indoor environments is a crucial problem in the development of robotic systems and location-based services due to complex spatial structures, the presence of obstacles, and limited available pathways. The A* algorithm, as a heuristic-based pathfinding method, is widely used; however, its performance degrades on high-resolution grid maps because of the increasing number of nodes that must be explored. This study proposes the integration of the A* algorithm with an adaptive grid simplification method (Gridadapte) to improve pathfinding efficiency without sacrificing route quality. The research methodology includes grid-based indoor map modeling, the application of Gridadapte to reduce cell density in low-obstacle areas, and the implementation of the A* heuristic function for optimal path search. Performance evaluation is conducted through simulations on several indoor map scenarios by comparing conventional A* and Gridadapte-based A* in terms of the number of explored nodes, path length, and computation time. Simulation results show that the proposed approach significantly reduces the number of search nodes by 30–45% and accelerates computation time by 25–40% compared to A* on regular grids, while the resulting path length remains optimal and does not experience a significant increase. These findings indicate that Gridadapte is effective in reducing the A* search space while preserving the topological structure of the environment. Therefore, the combination of A* and Gridadapte is proven to enhance both the efficiency and accuracy of pathfinding in complex indoor environments. This approach has strong potential for application in autonomous robotic systems, smart building guidance systems, and location-based Internet of Things (IoT) applications in indoor settings such as hospitals, campuses, and shopping malls.
Application of Natural Language Processing Based on Machine Learning and IoT Data
The development of the Internet of Things (IoT) and Natural Language Processing (NLP) has opened new opportunities to build intelligent monitoring systems capable of processing multiformat data simultaneously. This study aims to apply machine learning–based NLP methods to analyze IoT data in order to improve the accuracy of real-time environmental condition detection. The dataset used consists of temperature and humidity parameters collected from IoT sensors, as well as textual data in the form of environmental condition reports. The textual data are processed through tokenization, lowercasing, stopword removal, stemming, and lemmatization, followed by feature extraction using Term Frequency–Inverse Document Frequency (TF-IDF). The Naive Bayes algorithm is employed to classify conditions into Normal, Warning, and Critical based on a combination of sensor data and textual features. The experimental results show that integrating NLP with IoT data increases classification accuracy from 82% (using sensor data alone) to 91% and enables automatic, real-time condition detection. This study demonstrates that multiformat data integration through NLP and machine learning can enhance the effectiveness of intelligent monitoring systems and can be implemented in environmental, industrial, healthcare, and security domains, thereby making a significant contribution to data-driven decision-making.
Design and Evaluation of an Adaptive Traffic Signal Control System Based on Mamdani Fuzzy Logic
Traffic congestion in urban areas has become an increasingly complex problem due to the rapid growth in the number of vehicles and the limitations of fixed-time traffic signal control systems. Conventional approaches are unable to respond dynamically to fluctuations in traffic density, often resulting in high waiting times and reduced intersection capacity. This study aims to design and evaluate an adaptive traffic signal control system based on Mamdani fuzzy logic to improve intersection control performance. The developed system uses two input variables, namely the number of vehicles on the main approach and the number of vehicles on the competing approach, and one output variable representing the green signal duration. Membership functions are modeled using triangular and trapezoidal shapes, while the rule base is structured in the form of a Fuzzy Associative Memory (FAM). The inference process is performed using the Mamdani method, and the crisp output value is obtained through centroid defuzzification. Performance evaluation is conducted under five traffic density scenarios representing low to highly congested conditions by comparing the fuzzy-based system with a fixed-time control system. The performance indicators used include average vehicle waiting time, queue length, and intersection throughput. The experimental results show that the fuzzy-based system is able to reduce average waiting time by 18–25% and increase throughput by 15–20%, particularly under moderate to congested traffic conditions. These findings demonstrate that Mamdani fuzzy logic can produce more adaptive, responsive, and efficient signal control compared to conventional methods, indicating its strong potential as an effective solution for the development of intelligent transportation systems in urban environments.
A Decision Support System for the Selection and Distribution of Superior Durian Seedlings to the Community Using the Decision Tree Method
The durian fruit is an agricultural commodity with high economic value and strong demand both domestically and internationally. However, the success rate of durian cultivation in Indonesia remains relatively low, at approximately 30.3%. This is partly due to the limited experience of farmers in managing durian plantations and the absence of an objective system for selecting eligible recipients of superior seedlings. Inaccurate selection of seedling recipients can lead to low productivity, suboptimal fruit quality, and an imbalance between market supply and demand. To address these issues, this study proposes the development of a Decision Support System (DSS) for the selection of superior durian seedling recipients using the Decision Tree algorithm. The study identifies several factors influencing eligibility, including age, land area, land ownership, farming experience, socioeconomic status, number of plants, water availability, membership in farmer groups, regional location, and education level. Data from 300 respondents were collected and processed through several preprocessing stages, including categorical data encoding, numerical data binning, normalization, and the division of training and testing datasets. The Decision Tree model was developed using the Scikit-learn library in the Python programming language, with the Gini index as the splitting criterion. The experimental results indicate that the model achieved an accuracy of 85%, a precision of 90%, and a recall of 95% for the "Eligible" class, demonstrating the system’s effectiveness in accurately identifying qualified recipients. The system was implemented as a GUI-based desktop application using Tkinter, equipped with features for data input, eligibility prediction, recipient data management, and statistical visualization. The implementation of this system is expected to enhance objectivity, efficiency, and accountability in the distribution of superior durian seedlings, thereby contributing to increased productivity among durian farmers and promoting better market equilibrium.
Decision Support System for Determining Effective Learning Strategies for Students Using the SMART Method
Effective learning strategies are essential factors in improving students’ academic achievement. However, at SMP Negeri 2 Binjai, several challenges remain, including the low effectiveness of applied learning methods, the lack of adaptation to individual learning styles, and the limited use of academic data in supporting learning decisions. These issues were further exacerbated by the post-pandemic shift toward hybrid learning models, which has not been fully optimized. To address this problem, this study designed a Decision Support System (DSS) using the SMART (Simple Multi-Attribute Rating Technique) method to recommend suitable learning strategies for students. The system was developed through stages of requirement analysis, logical design of the SMART calculation, and the implementation of integrated multi-criteria processing. The results show that the system can provide objective and accurate learning strategy recommendations. From 32 students analyzed, 11 students (34.37%) were recommended to adopt E-learning, 7 students (21.87%) to use Blended Learning, and 14 students (43.75%) to apply Traditional Learning. The highest score of 1.00 was achieved by two students in the E-learning category, while the lowest score of 0.125 was recorded in the Traditional category. These findings confirm that the application of the SMART method in DSS is effective in helping teachers and students determine more adaptive and personalized learning strategies, thereby supporting the improvement of learning quality in schools.
Design of Indonesian Sentence Grammar Checking Software Using Left Corner Parser
Grammar checking is an important component of Natural Language Processing (NLP), particularly for improving the quality of written communication. This article discusses the design of grammar-checking software for Indonesian sentences using the Left Corner Parser method. The Left Corner Parser is a syntactic parsing method that combines the advantages of top-down and bottom-up parsing, making it efficient in recognizing sentence structures. This study includes the stages of data collection, the design of Indonesian grammatical rules, the implementation of the parser, and the evaluation of checking accuracy. The results show that the software can effectively detect sentence structure errors in various types of sentences, from simple to complex. With further development, this tool has the potential to be applied in educational tools and automatic text editing applications.
Optimizing Campus Promotion Routes Through the Application of Dijkstra’s Algorithm
This study aims to optimize campus promotion routes using Dijkstra's algorithm to increase efficiency in time and cost. By applying this method, the shortest and fastest paths to target promotion locations can be optimally determined. Data were obtained through geographical mapping of schools and road accessibility. The implementation of Dijkstra’s algorithm was analyzed in terms of effectiveness and efficiency compared to conventional methods. This study is expected to contribute to enhancing the effectiveness of campus promotion strategies through route optimization.
Design and Development of a Website for Rumah Jahit Dini Using the Prototyping Method
This study aims to design and develop a service website for Rumah Jahit Dini to improve service effectiveness and efficiency for customers. The system was developed using the iterative prototyping method, where development is carried out incrementally based on direct user feedback. The website includes features such as service ordering, product information, catalog browsing, and administrative data management. A qualitative descriptive approach was applied, supported by UML-based system modeling tools. To validate system functionality, black box testing was conducted. The results indicate that the developed web-based information system successfully addresses the limitations of the previous manual service process and enhances both accessibility and customer satisfaction with the services provided by Rumah Jahit Dini.
Development of a Web-Based Sales Information System for Benson Bakery Using the Waterfall Model
The rapid development of information technology has encouraged many businesses, including small and medium enterprises, to adopt information systems for business management. Benson Bakery, a bakery and pastry business, still relies on manual record-keeping, leading to delayed reports, data loss, and order inaccuracies. This study aims to design a web-based sales information system to improve operational efficiency and service quality. The system development method used is the Waterfall model, which includes the stages of requirement analysis, design, implementation, testing, and maintenance. The result is an integrated system capable of managing product, order, and report data in real-time. The implementation of this system is expected to optimize business processes at Benson Bakery and enhance customer satisfaction.
Design of Academic Information System and New Student Admission System (PPDB) Based on Website at SMP Swasta Delisha with Prototype Model Approach
Advances in information technology have encouraged educational institutions to adopt digital systems to improve operational efficiency and service quality. SMP Swasta Delisha currently does not have a website-based system, so the New Student Admissions (PPDB) process and information delivery are still done manually. This manual approach leads to inefficiencies and increases the risk of administrative errors. This study aims to design and develop a website-based information system that includes online registration features, school profile information, and important announcements. The system development uses the Prototype Model method, which is iterative and flexible, allowing the system to be built according to user needs through direct feedback. The results of this study are expected to help SMP Swasta Delisha in improving the efficiency of the PPDB process, expanding the reach of information, and providing better services to prospective students and the wider community.
Design and Implementation of Web-Based Product Order and Delivery Management Information System at Dheafin Bakery
This study aims to design and implement a web-based order and delivery management information system for Dheafin Bakery, a small and medium enterprise. The system was developed as a solution to operational problems that have been carried out manually, such as order recording, customer and product data management, and the delivery process. A software engineering approach was used in the development of this system, with the Waterfall method which includes the stages of needs analysis, design, implementation, testing, and maintenance. The system was built using the PHP programming language and MySQL database, and was designed responsively so that it can be accessed through various devices. The implementation results show that the system is able to integrate the ordering and delivery process automatically and in real-time, reduce recording errors, speed up the workflow, and increase efficiency and customer satisfaction. The system also provides easy-to-use customer, product, and order tracking management features. Thus, this information system has succeeded in significantly improving Dheafin Bakery's operational performance and has the potential to become a model for similar applications for other small and medium enterprises.
Web-Based Financial Information System at Ibu Sri's Shop
Ibu Sri's Shop is one of the Micro, Small and Medium Enterprises (MSMEs) engaged in the trade of daily necessities. Along with the growing need for efficiency and accuracy in recording transactions, this shop requires a system that can help manage finances in a structured and computerized manner. This study aims to design and implement a Web-Based Financial Information System that can help the process of recording transactions, calculating total purchases, and financial reporting at Ibu Sri's Shop more effectively and accurately. This system was developed using the PHP programming language and MySQL database with a waterfall approach as a software development method. The main features of this system include product management, recording sales transactions, and daily financial reports that can be accessed through a simple and user-friendly web interface. The implementation results show that the system built can speed up the recording process and reduce the potential for manual errors in managing store finances. In addition, this system also makes it easier for shop owners to monitor financial performance periodically without having to do manual recording. This research is expected to provide a real contribution to the digitalization of the financial system in MSMEs, especially in improving operational efficiency and data-based decision making.
Micro, Small and Medium Enterprises (MSMEs)
Development of a Mini Calculator Application for Processing Odd and Even Numbers Using Dev-C++
A mini calculator is a simple application designed to perform basic arithmetic operations such as addition, subtraction, multiplication, and division. This mini calculator program was developed using Dev-C++ with the primary goal of providing a practical solution for users to perform numeric calculations interactively. During the development process, several key issues were identified, including difficulties in accessing the calculator after the initial calculation, input errors, and the program’s inability to handle repeated operations without restarting the application. The development method utilized in this application was procedural programming, incorporating the use of the do-while loop structure. This approach enables the calculator to continuously request input and perform computations based on user choices without the need to close or restart the program. The do-while loop ensures that users can carry out multiple operations in succession until they choose to exit. To address the aforementioned issues, several solutions were implemented. These include input validation mechanisms to handle errors such as division by zero or invalid inputs, as well as an interactive menu system that facilitates operation selection. Moreover, error handling features were incorporated to provide users with clear messages in the event of incorrect operations. Separate functions were implemented for each mathematical operation to enhance code modularity and maintainability. The development stages of this application involved the following steps: (1) designing the algorithm and calculator menu structure; (2) implementing individual functions for each arithmetic operation; (3) applying the do-while loop to control the program’s iterative flow; (4) conducting testing and debugging to ensure proper functionality; and (5) refining the user interface and error messages to enhance user experience. In conclusion, the use of the do-while loop as a program repetition method has proven to be effective in maintaining the calculator application’s interactivity without requiring a restart. The program provides an efficient and user-friendly solution for repeated calculations through a simple and responsive interface.
Application of Decision Support System to Determine the Optimization of the Learning Plan Preparation Process in Schools Using the SAW Method
The preparation of an effective learning plan is one of the important factors in improving the quality of education. In the context of the 2024 Independent Curriculum, the flexibility and independence of schools in designing learning plans will be greater, but this also requires the right strategy in determining priorities and the resources needed. This research aims to develop a Decision Support System (DSS) that can help optimize the process of preparing lesson plans in schools using the Simple Additive Weighting (SAW) method. The SAW method was chosen because of its ability to assess and compare various alternatives based on predetermined criteria, such as Relevance to the World of Work, Project-Based Learning, Special Competency Development, Technology Utilization, Soft Skills Development, Plan Flexibility, Inclusive Learning, Collaboration with Industry, Critical Thinking Skills, Time Management. The results of this study show that the DSS implemented is able to provide more effective and efficient recommendations in preparing learning plans that are in accordance with the principles of the 2024 Independent Curriculum. Thus, it is hoped that this system can be a tool for educators in developing more structured and targeted learning plans.
Copyright (c) 2024 Pascal: Journal of Computer Science and Informatics
Designing Fan Speed Regulation Software Using Backpropagation Method
Fans have the main function of air conditioning, room fresheners, and dryers which are usually equipped with heating components. In addition, fans are also used in vacuum cleaners and various decorative elements in the room, which play a role in keeping the air temperature within the specified limits. Advances in the field of computer programming provide many benefits, especially in terms of ease and efficiency in the use of devices connected to computers. With control through a computer, the device can be operated more optimally and responsively according to the needs of the user.
Application for Promotion of Micro, Small and Medium Enterprise Activities in Increasing Student Business Creativity Using Digital Technology
This research aims to develop a digital technology-based promotion application aimed at improving students' ability to promote MSME products. This application is expected to provide innovative solutions in increasing the visibility and sales of MSMEs managed by students, by providing features that support promotional activities effectively. The data collection method is carried out through field research, interviews, and direct observation. The results of the study show that this application has great potential in supporting promotional efforts and improving students' digital skills, which in turn can have a positive impact on the local and national economy.
Legal Information System with Housing Licensing for Administrative Efficiency Process
The housing licensing administration process often faces challenges in the form of complex bureaucracy, long processing times, and lack of information integration between systems. This research aims to integrate the legal information system with the housing licensing process to improve administrative efficiency. By utilizing integrated information system technology, this research develops a platform that allows the synchronization of legal data related to housing regulations with licensing mechanisms. The methodology used includes needs analysis, system design, and efficiency evaluation through implementation case studies. The results of the study show that system integration is able to reduce processing time, improve data accuracy, and speed up decision-making. These findings are expected to make a significant contribution to optimizing the governance of housing licensing and encouraging transparency and accountability in public administration.
Decision Support System for Choosing the Best Nurse Using the Multi Factor Evaluation Process (MFEP) Method at Djoelham Hospital, Binjai City
Health workers are any person who is devoted to health and has knowledge and/or skills through education in the health field which for certain types requires the authority to carry out health efforts. A strategy is needed to increase the interest of health workers working in hospitals. The selection of exemplary health workers in hospitals is expected to be a motivation to increase the interest of health workers working in hospitals so that they can be a driver for the creation of health workers who have a nationalist, ethical and professional attitude, have a high spirit of service, are disciplined, creative, knowledgeable, skilled, virtuous and can uphold professional ethics. The purpose of this study is to evaluate the performance of nurses and reward the best nurses at Djoelham Hospital Binjai City. The use of the Multi Factor Evaluation Process (MFEP) method is relevant because it can help in integrating and evaluating various factors and criteria holistically. MFEP is a method that allows to evaluate various factors that affect decisions, as well as provide weight or value relative to each of these factors. The criteria used in this study are discipline, cooperation, loyalty, education, understanding of drug prescriptions, understanding of technology. The conclusion of this study is that the construction of this support system can help Djoelham Hospital in determining the best nurse and the use of the MFEP method in the decision support system to determine the best nurse increases accuracy in determining the best suitable nurse. This method is able to process various criteria that have been set, so that the results of decisions are more objective and fair compared to manual assessments.
Decision Support System for Choosing the Best Mechanic Using the Smart Method at Cv. Garuda Mas Motor Binjai
Mechanics are the most important asset in an automotive company, workshop mechanics are responsible for the maintenance and repair of motor vehicles when damage occurs. However, not only dealing with damage, mechanics also conduct thorough checks before damage to customers' vehicles occurs. To be able to provide satisfaction with vehicle maintenance services or motorcycle services, of course CV. Garuda Mas Motor Binjai must have good and reliable mechanics. So that customers will feel satisfied with the service provided by the Dealer. To obtain the best mechanic, of course, an assessment must be carried out on the mechanics who will work. Usually this assessment is carried out by the Dealer only by conducting direct testing on a case of damage problems without considering anything else. So that in some cases there are mechanics that are not in accordance with the qualifications desired by the Dealer. For this reason, it is necessary to build a decision support system that can help the Dealer in selecting the best mechanic on the CV. Garuda Mas Motor Binjai. From the data on the criteria for selecting the best mechanic, the results of the analysis of the SMART method from the 20 alternative data above, it can be seen that the one who obtained the best score or ranking is the mechanic on behalf of Suriono with the results of the analysis using the SMART method 0.85.
Watermarking Competency Certificates with Value Images Using the Descrete Cosine Transform (DCT) Method
Image watermarking is a technique for inserting hidden information into digital images to maintain the authenticity and integrity of documents. This study discusses the application of the Discrete Cosine Transform (DCT) method in the watermarking process on the value image stated in the Competency certificate. The DCT method allows the insertion of watermarks on the image's frequency domain, where information can be embedded without compromising the visual quality of the certificate. This implementation aims to ensure that certificates remain authentic and not easily manipulated. The embedding process is carried out by inserting a watermark on a high-frequency component that is invisible to the human eye, while the extraction process is used to verify the authenticity of the certificate. The results show that the DCT method provides reliable protection against image modification, as well as maintains the validity and security of data integrated in the competency certificate digitally.
Application of Backpropagation Method to Predict Livestock Population in Langkat Regency
Livestock has an important role in the structure of the rural economy, where small livestock is an ideal choice to support the local economy and ensure food security. In Lalat Regency, there is no accurate prediction system to find out the trend of small livestock populations in the future, both increasing and decreasing. To answer this need, this study uses the Artificial Neural Network (JST) technique with the Backpropagation method to predict the small livestock population in the region. This study develops a JST-based prediction system using available training data, training targets, and small livestock population test data. The prediction results for 23 sub-districts in 2023 show that in the first experiment, 18 sub-districts are in accordance with the prediction and 5 sub-districts are not in accordance with the prediction; In the second experiment, 17 sub-districts were compliant and 6 sub-districts were not compliant; And in the third experiment, 21 sub-districts were compliant and 2 sub-districts were not compliant. The prediction process was carried out with a target error of 0.00001, with each experiment using 20 iterations in the first experiment, as well as 4 iterations in the second and third experiments, and the training time was recorded for 00:00 seconds. This system was successfully developed using Matlab software, provides accurate prediction results of small livestock populations, and can be used by the Langkat Regency Agriculture and Food Security Office for better planning in the future.
Implementation of the Rough Set Method on Diseases Often Complained of by Patients (Case Study: RSU Raskita)
The development of medical technology requires hospitals to be more efficient in providing services, especially in terms of handling diseases that are often complained about by patients. This study aims to identify disease patterns that often appear in Raskita Hospital and provide appropriate treatment priorities based on patient characteristics. Using the Rough Set method, patient data such as age, disease type, and severity are analyzed to find relationships between attributes and determine treatment priorities. This study uses data on diseases that are often complained about by patients at Raskita Hospital in 2023-2024. Diseases such as Dengue Hemorrhagic Fever (DHF), Acute Respiratory Tract Infection (ARI), and Gastroenteritis are identified as diseases that often appear in different age groups, with toddlers and the elderly tending to get higher priority in treatment. By applying the Rough Set method, the decision-making process becomes more effective, especially in determining patient priorities and simplifying complex medical data. The results of the study show that the grouping of attributes based on age range, type of disease, and severity can improve the quality of hospital services. Raskita Hospital can optimize medical resources and provide more appropriate and efficient treatment for patients, especially in dealing with diseases that are often complained about.
Application Of The Decision Tree Method As A Factor Causing Students To Drop Out (Case Study: SMK Tunas Pelita Binjai City)
The problem of the phenomenon of dropping out of school for students at the Senior High School or Vocational Education level is increasingly widespread. In fact, education is a very important field to develop the quality of Human Resources (HR) for the country. Ayu et al said that one of the important sectors that directly contributes the most in developing the quality of Human Resources (HR) is the education sector. Meanwhile, SMK Tunas Pelita Binjai is one of the vocational high schools in Binjai City that also faces the problem of dropping out of school. Based on internal school data, in 2023 there are 32 students or around 5% of the total students at SMK Tunas Pelita Binjai who cannot complete their education until the end. This figure is quite high and is a serious concern for the school. Some of the factors such as students' interest in learning have decreased so much that they make students inactive or often alpha, parents with low levels of education tend to lack understanding and appreciation for the importance of formal education for their children's future, they may not have high aspirations for the achievement of children's education, economic impacts that are very binding on the family so that children prefer to work to help the family economy. Seeing the very complex problem of dropping out of school, a comprehensive and systematic approach is needed to analyze what factors are the causes. The application of the Decision Tree method in identifying the factors that cause school dropouts at SMK Tunas Pelita Binjai, is expected to produce new information that can be used as a basis for schools to design more effective strategies and interventions in preventing and reducing school dropout rates. The author uses the help of RapidMiner software to see the factors that cause students to drop out of school by using the C4.5 Decision Tree method to create a decision tree from existing student data. So that from the RapidMiner calculation process, it can be concluded that what are the factors that cause the student to drop out of school.