Journal of Informatics And Telecommunication Engineering
Not a member yet
373 research outputs found
Sort by
Optimum Antenna Height for 5G Radio Networks Using the Spatial Multi-tier Microcell Method
Full text linkThe construction of macrocell towers in large numbers has become a concern for city governments in terms of aesthetics. In 5G network technology, with a higher operating frequency, the resulting coverage becomes smaller, allowing for a reduction in antenna height. This study aims to re-evaluate the optimum antenna height based on coverage proportion criteria. Coverage calculations were performed using the COST 231 Hata path loss model and the Kathrein 742215 antenna model. A cellular network with a coverage radius of less than 500 m can utilize an antenna height of 10 m, where the required transmission power tends to be low, such as 1-watt, and a downtilt angle of 0° is sufficient. As the required cell radius increases beyond 500 m, the antenna height also becomes higher, starting from 20 m, with transmission power ranging from 10-watts to 20-watts and a downtilt angle in the range of 6°. Research findings also indicate that previous methods for calculating antenna height overlooked overshooting in the subsequent tier areas. Based on this method, coverage can be adjusted by considering handover zones and overshooting beyond the first tie
Simulation of the Single Sign-On Method for Service Provider Applications: A Case Study of Bhayangkara University Surabaya
Full text linkThe authentication system at Bhayangkara University Surabaya is still traditional, where users must have separate accounts for each service. This condition causes inefficiency, administrative burden, and security risks due to managing multiple credentials. This study aims to design and simulate a single authentication system based on Single Sign-On (SSO) to improve efficiency and ease of user access to campus digital services. The system was developed with an iterative approach using JSON Web Token (JWT) and RESTful API technology. The simulation was carried out by testing two applications, namely Identity Provider (IdP) and Service Provider (SP), which interact in a single authentication scenario. Three types of testing were carried out: (1) simulation of the login flow and SP access after authentication at the IdP, (2) compatibility testing between Android devices (multi-device), and (3) RESTful access performance testing, including response time, throughput, and token validity. The results show that the SSO system is able to centrally integrate campus services, accelerate authentication, and maintain access security. The average response time was recorded below 1.5 seconds, even when tested on 20 devices simultaneously. The implementation of SSO has been proven to improve operational efficiency and simplify user identity management. This system contributes to an improved user experience and can be replicated by other educational institutions with similar needs
Sensitivity of Weather Forecast Analysis in Comparison of Fuzzy Time Series And Artificial Neural Network Methods
Full text linkThis research aims to produce a comparative level of sensitivity accuracy between fuzzy time series and artificial neural network methods in weather forecasting. The background to the problem identified is that weather conditions are always changing, so a system development is needed to help obtain accuracy values from weather forecasts by paying attention to the sensitivity of the comparison results between the two methods. The research results show that the Artificial Neural Network is effective in providing weather forecast values according to existing datasets, while the Fuzzy Time Series is able to produce sensitivity accuracy values based on existing datasets. This research also reveals that both methods are quite good in determining accuracy results on weather forecast sensitivity to meet user needs. The conclusion of this research is that both methods can provide the right solution for the development of a weather forecasting system that can be used by users
Analysis of Moodle E-Learning Server Optimization with Load Balancing Technology using Round Robin and Leastconn Algorithms
Full text linkAs web services and applications become increasingly complex and user demand grows—especially with the rising number of students—the need for a reliable E-Learning system becomes critical. At Politeknik Negeri Balikpapan, the current E-Learning platform operates on a single server, leading to slow response times and potential server downtime under high traffic conditions. This study addresses the issue by implementing load balancing using two algorithms: Round Robin and Least Connection, across three web servers and one separate database server. Testing was conducted using Apache JMeter with 1000 requests per 10 seconds. Results show that the Least Connection algorithm outperformed Round Robin, achieving an average response time of 155.8ms, compared to 184.2ms. Compared to the single-server setup, the load-balanced system showed significant improvements in response time, error rate, concurrency, availability, upstream, and downstream metrics. CPU load was also reduced due to traffic distribution across multiple servers. This demonstrates that server resource optimization via load balancing can significantly enhance the overall performance of E-Learning services. These findings provide a strong foundation for more efficient and scalable IT infrastructure development and support better decision-making in managing high-demand educational platforms in the futur
SIMANKEL: A Web-based Information System for the Efficiency of Village Administration
Full text linkAdministrative services in Sekarteja Village are still carried out manually through physical recording, which causes data irregularity, risk of losing archives, and limited access to information for the community. This research aims to develop and evaluate the feasibility of a web-based Kelurahan Administration Management Information System (SIMANKEL) as a solution to these problems. System development uses the Research and Development (R&D) method with a waterfall process model that includes requirements analysis, design, implementation, testing, and documentation. The system was developed using PHP Native, MySQL as a database, and the user interface was designed based on UI/UX principles using Visual Studio Code. System evaluation was conducted by referring to three aspects of the ISO 9126 software quality standard, namely functionality, usability, and efficiency. The test results show that all functions run according to specifications (100%), the usability aspect obtained a feasibility score of 91% from 20 respondents (excellent category), and the efficiency aspect shows that the system load time is in the good category based on testing using GTMetrix. These findings indicate that SIMANKEL is feasible to use as an information system for administrative services in Sekarteja Village and has the potential to increase the effectiveness, efficiency, and transparency of pub services
Implementation of Random Forest Algorithm for Early Detection of Heart Health Using IoT and MAX30102 Sensors
Full text linkHeart disease is one of the leading causes of death in the world, including in Indonesia, which ranks second after stroke. Early detection is essential to reduce the risk of serious complications and death from cardiovascular disorders. This study aims to design an Internet of Things (IoT)-based early detection system for heart health that is integrated with MAX30102 sensors and Random Forest algorithms to classify heart rate conditions. Biometric data in the form of heart rate (BPM), blood oxygen level (SpO₂), and activity condition features (rest, light exercise, stress) were collected from 150 respondents. This data collection was validated by comparing the results using ECG devices by medical personnel. Pre-processing is done through data cleansing, category variable encoding, and feature extraction (BPM variability, PPG amplitude). The classification model was developed with the Random Forest 100 decision tree and tested with 5-fold cross validation. The results showed that the system was able to achieve an average accuracy of 93% with a standard deviation of 0.03, as well as an accuracy per fold of 93%, 93%, 97%, 93%, and 87%. The classification results are in line with the ECG data of medical personnel, indicating that this system is reliable enough for the early detection of normal or abnormal heart conditions. The study concluded that the integration of IoT and Random Forest is effective as a real-time, cost-effective, and supporting early detection of heart health, especially in remote areas. Advanced development is suggested to expand activity data and add biometric features to improve classification accuracy
The Design of Microstrip Antenna Using DGS and Series Parasitic Methods for C-Band Applications in Satellite Communications
Full text linkThis research proposes the design of a microstrip antenna for satellite communication that operates at C-Band frequency. The antenna is made of FR4 material with a thickness of 1.6 mm and has a permittivity of 4.4. The target C-Band frequency that can operate is in the range of 3.7 GHz - 8 GHz. To achieve this wide bandwidth, the defected ground structure (DGS) method is used which cuts the ground area under the substrate. Furthermore, to increase the antenna gain, the method of adding parasitic elements arranged in series (series parasitic) located at the top of the patch. The antenna design begins by designing the antenna in the DGS model and adding three parasitic elements where the basic shape of the parasitic elements has the same dimensions as the antenna patch. Then the development is created using a quarter of the patch dimensions which are added with nine parasitic elements. The simulation results show that the antenna with nine parasitic elements has an antenna bandwidth of 5.292 GHz in the range of 3.214 GHz - 8.506 GHz, where the maximum gain obtained is 8.6 dBi. While the development of an antenna with nine parasitic quarter-size patches has a bandwidth of 6.126 GHz in the frequency range of 3.344 GHz - 9.47 GHz with a maximum gain of 8.04 dBi. Therefore, it can be concluded that this research that designs antennas with the DGS method and series parasitic can operate at C-Band frequencies and can be applied to satellite communications
Evaluation of Student Satisfaction with Computer Laboratory Facilities at UIN Sumatera Utara Using the C5.0 Algorithm
Full text linkThe evaluation of student satisfaction with the computer laboratory facilities at UIN Sumatera Utara is crucial for improving the quality of educational services provided by the institution. The main issue faced is the lack of accurate data regarding student satisfaction with the facilities available in the laboratory. This study aims to analyze the level of student satisfaction using the C5.0 algorithm, which is known for its effectiveness in data classification. The research methodology involves collecting data through a comprehensive survey covering various aspects of laboratory facilities, such as reliability, responsiveness, assurance, empathy, and tangibles. The survey was conducted with a number of students to obtain representative information about their satisfaction with the provided facilities. After data collection, data cleaning and processing steps were carried out to build a classification model using the C5.0 algorithm. The results of the study showed that the C5.0 model achieved a very high accuracy rate of 99.25%, with precision of 99.72% and recall of 99.45% on the training data. Meanwhile, on the testing data, the accuracy reached 97%, precision was 100%, and recall was 96%. These findings indicate that the model has a very high ability to accurately classify student satisfaction levels. In conclusion, this model can provide useful recommendations for the university to identify areas that need improvement to meet student expectations. The implication of this research is the importance of the continuous development of laboratory facilities to improve student satisfaction and create a more optimal learning experienc
Precision and Accuracy of Ultrasonic and Infrared Laser ToF IoT Sensors
Full text linkNon-contact distance measurement using sensors allows measurements when conventional tools reach their limits. These measurements can be integrated into the Internet of Things (IoT) through IoT-enabled microcontrollers, but sensor accuracy and precision must first be verified. This study compares two sensors—infrared time-of-flight and ultrasonic—in terms of accuracy and precision. An object reflecting sound and electromagnetic waves was placed at set distances, and sensor readings were compared to ruler measurements. The sensors showed good precision, with the infrared sensor outperforming the ultrasonic one. However, both lacked the accuracy compared to actual distances. The infrared sensor was consistently more accurate, requiring less correction to align with true distances. While the ultrasonic sensor performed better at short distances, its accuracy dropped significantly beyond 40 cm. Overall, the infrared sensor proved superior in accuracy. These findings highlight the potential for integrating such sensors into standalone or IoT-connected systems for reliable measurements
Comparison of Shuffle Algorithms For Randomness, Time Complexity and Space Complexity
Full text linkThis research aims to compare the performance of three shuffle algorithms in the data randomization process. Efficient data randomization is very important in various applications, especially in the development of random data-based systems such as games, simulations, and data processing. This study uses a dataset of 1000 English words, which is broken down into several dataset sizes (100, 500, and 1000 elements). The research methods used include three types of tests: the Chi-Square Test and Runs Test to ensure randomization results; time complexity to measure execution time efficiency; and space complexity to analyze memory usage efficiency. Each test was repeated 1000 times to get accurate results. The results show that the LCM algorithm is the best-performing algorithm, producing the fastest execution time and stable memory usage. The Fisher-Yates Shuffle algorithm comes in second with good time efficiency. The conclusion of this research is that the LCM algorithm is recommended for applications that require fast and efficient randomization on large datasets, while the Fisher-Yates Shuffle algorithm can be a fairly efficient alternative. The Naive Shuffle algorithm, however, is not good for applications that require high speed. These findings provide important implications in the selection of optimal randomization algorithms for high-performance data-driven application