Journal of Informatics And Telecommunication Engineering
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373 research outputs found
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Enhancing Security and Efficiency of an IoT-Based Diesel generator Using AES Encryption
Full text linkThe Automatic Transfer Switch (ATS) system plays a crucial role in ensuring seamless power transfer between the main power source (PLN) and the backup generator (Diesel Generator), which requires real-time monitoring. PT Kereta Api Indonesia (Persero) utilizes diesel generators at strategic stations such as Kramasan Station to maintain operational continuity. This study aims to design and develop a monitoring system based on the Internet of Things (IoT) using the ESP8266 microcontroller connected to Firebase as a cloud storage platform, along with a mobile application for remote control and monitoring. The system is equipped with the PZEM-004T sensor to measure electrical parameters (voltage, current, power, and frequency), the HC-SR04 ultrasonic sensor to monitor fuel levels, and a DC voltage sensor to assess battery conditions. Data security is enhanced through encryption using the Advanced Encryption Standard (AES) algorithm before transmission to the cloud, and decrypted on the user application. Experimental results show that the system operates optimally, with relative error averages of 0.44% for voltage, 7.5% for current, 1.32% for power, and 4.00% for fuel level. The novelty of this research lies in the integration of an IoT-based ATS monitoring system with AES encryption for securing cloud data transmission, as well as the implementation of a multi-sensor approach in a single integrated and industry-applicable system. Therefore, the system has proven to be effective in improving the efficiency, security, and reliability of automatic diesel generator monitoring, and holds potential for broader industrial-scale implementation
Automated Food Preserving System Utilizing NodeMCU ESP8266-Based Drying Methodology
Full text linkFood drying is one of the effective methods for preserving food and extending its shelf life by inhibiting bacterial growth. In Indonesia, many food products require sun drying to preserve them. However, this process often disrupts due to sudden rain showers, which can impede the drying process. Therefore, a automatic food cover system is needed to facilitate human work and protect the drying process from rain disturbances. This study designs an apparatus that can automatically cover dried food using FC-37 rain sensor controlled by NodeMCU ESP8266. The device also features an email notification feature to provide information on whether it's raining or not, allowing users to take action before the rain arrives. With this automatic food cover system, we expect to improve efficiency and quality of food drying results
Classification Of Interest In Sports Using The Naive Bayes Classifier Method
Full text linkInterest in sports must be done from an early age and requires the right method to achieve the desired results, namely by using the Naive Bayes method. The purpose of this study was to explore the sports interests of students of SDN 3 Tarutung with the Naive Bayes method. The subjects of this study were students in grades 4, 5, and 6 of SDN Jenggolo Tuban who liked sports using data collection methods, namely the Naive Bayes method, Observation, Interviews and practical sports tests based on sport search, namely Height (TB), Sitting height (TD), Weight (BB), Arm span (RL), Tennis ball throw and catch (LTBT), Basketball throw (LBB), Vertical jump (LT), Agility run (LK), 60 meter sprint (L60M), and multi-stage run (MFT). The Naive Bayes modeling system is carried out in two phases, namely training data and testing data. The results of the study obtained were the results of the classification of each student who was talented in sports (football, volleyball, badminton, sprinting, swimming) or not talented in sports (football, volleyball, badminton, sprinting, and swimming). The results of the testing data showed that 7 students were talented in football, 2 students were talented in volleyball, 1 student was talented in badminton, 5 students were talented in sprinting, and 3 students were talented in swimming
Implementation of 4-Directional Depth First Search and Projection Profile for Javanese Manuscript Image Segmentation
Full text linkOne of the key steps in digitizing Javanese manuscripts is image segmentation, which separates elements such as lines and characters. This study evaluates the Projection Profile and Four-Directional Depth-First Search (4-Directional DFS) methods for segmenting handwritten Javanese script. The Projection Profile method is used for line segmentation, while 4-Directional DFS identifies interconnected pixels for character segmentation. A total of 20 scanned images were randomly selected from Serat Pratanda and Serat Primbon Reracikan Jampi Jawi. After grayscale conversion and binarization, each image underwent two treatments: with and without advanced preprocessing, before segmentation. Results showed that line segmentation achieved 100% accuracy in both treatments. Character segmentation reached 91.02% accuracy with advanced preprocessing and 84.28% without it. Segmentation errors were mainly caused by over-segmentation and under-segmentation. These results demonstrate that the Projection Profile and 4-Directional DFS methods are effective in segmenting handwritten Javanese manuscripts. They show promise for supporting future developments in automatic Javanese script transliteration
Enhancing Visibility in Low-Illumination Street Images Using HE, AHE, and CLAHE Techniques
Full text linkLow-quality images, such as those resulting from digital capture under low-light conditions, present a significant challenge in the field of digital image processing. This study aims to enhance image visual quality using three contrast enhancement methods: Histogram Equalization (HE), Adaptive Histogram Equalization (AHE), and Contrast Limited Adaptive Histogram Equalization (CLAHE). The dataset consists of 110 grayscale-converted street images captured under various lighting conditions (morning, noon, night, rainy, and clear weather). Evaluation was conducted using objective metrics, including Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), execution time, and subjective assessment from 35 respondents. The results show that CLAHE consistently produces the best visual quality, achieving the highest PSNR of 12.93 dB and the lowest MSE of 3310.28 on a 32×32 grid, with an average execution time of 2–25 seconds. In comparison, HE recorded the lowest PSNR of 8.07 dB and the highest MSE of 10119.23, but had the fastest runtime of 0.3–0.4 seconds. AHE had the longest processing time, reaching up to 103 seconds, with inconsistent output quality. Based on user preference, 65% of respondents favored AHE, despite CLAHE being objectively superior. This study confirms CLAHE as the most effective method for enhancing image quality under extreme lighting conditions without sacrificing important visual details
The Application of Genetic Algorithm in Construction Project Planning System At Cv. Haza Mulia Engineering
Full text linkProject scheduling is a crucial aspect in construction project management that aims to ensure that all tasks are carried out in an optimal sequence to maximize efficiency and reduce completion time. This study has three main objectives: (1) to build a web-based construction project planning system at CV. Haza Mulia Engineering, (2) to apply genetic algorithms to the construction project planning system at CV. Haza Mulia Engineering, and (3) to analyze the performance of genetic algorithms in generating optimal project schedules. This study was motivated by the need to complete a final assignment or thesis and used genetic algorithms as the main method. The research process begins with the identification of tasks and dependencies in a construction project. An initial population consisting of random schedules is generated and evaluated using a genetic algorithm. The selection, crossover, and mutation processes are carried out to gradually produce a new, better population. The fitness of each individual is calculated based on the number of unconnected activity dependencies, and the algorithm stops when the best mutually continuous schedule is found. The main result of this study is a web-based application built using PHP. This application is able to produce more efficient project scheduling compared to conventional methods. The schedule generated by genetic algorithm shows significant reduction in project completion time by minimizing unmet dependencies. The conclusion of this study confirms that the application of genetic algorithm in web-based project planning scheduling can avoid conflicts between activities and make the schedule more structured
Comparison of Support Vector Machine (SVM) and Naïve Bayes Algorithm Performance in Analyzing Garuda Bird Design Sentiment in IKN
Full text linkThe Government's policy in moving the Indonesian Capital City (IKN) is considered controversial, this has given rise to various responses from the public, especially on social media X. This research aims to analyze tweet sentiment related to IKN and compare the two algorithms. In this experiment, we succeeded in collecting 5128 tweet data regarding IKN in the X application, the total amount of IKN data was classified into positive sentiment as 2598 1659 negative data and sentiments. Research objectives, methods used, main results, and implications. This research aims to measure public sentiment towards the design of the Garuda bird as the main symbol of the Indonesian Capital City (IKN) by using a comparison of the performance of the Support Vector Machine (SVM) and Naïve Bayes algorithms in analyzing the sentiment of the Garuda bird design in the IKN. main results, for example: the proportion of positive, negative and neutral sentiment, as well as the factors that most influence sentiment. Implications of research results for government, designers and society
Designing a Website-Based Technology Winnicode News Portal Application with Prototyping Method to Enhance User Engagement for Technology News Reader
Full text linkA news portal is a platform that usually takes the form of a website that presents various kinds of news according to its type. With the development of technology and the emergence of social media, the audience of these news portal websites has decreased. People prefer to read news through social media pages because they are easier to access. Based on this, it is necessary to develop an efficient and eye-friendly news portal website to attract people to read news through the website. By using the prototype method, the website is designed based on a pre-made design. So that the developers have a benchmark in developing the website to be built. After that, an evaluation is needed from user reviews and testing is carried out gradually to improve the website to make it more efficient and appropriate. Of the 10 test points that have been carried out in the study, a 100 percent success rate has been achieved from the test. This shows that the performance of the website that has been built can meet the criteria to be published and can be used by the wider community. From the development of this application, people can read with the theme of technology that is more comfortable, easily accessible and can send criticism to the publisher if there is a mismatch of news, have additional information about the latest news, or suggestions for the website so that it can be develope
Analysis Of Mobile Banking User Activity Based On Transaction Time Clustering Using Self-Organizing Map (SOM) Method
Full text linkThe rapid growth of mobile banking services in Indonesia demands a deeper understanding of user behavior, especially in terms of time and transaction patterns. However, the challenge is how to effectively cluster users based on their time habits in making transactions, so that service strategies can be tailored accordingly. To address this issue, this study applies the Self-Organizing Maps (SOM) method to cluster users based on transaction time features, such as the number of transactions in the morning, afternoon, evening, night, and the division between weekdays and weekends. The dataset used includes 87,361 mobile banking users throughout 2023. The results showed that the SOM method was able to form nine different user behavior clusters, with the largest cluster being Early User (Weekday) consisting of 32,324 users (37.0%). Overall, the Early User (Weekday) segment covers about 60.3% of the user population. Meanwhile, there are also minority segments such as Night Owl (Weekday) (5.9%) and Early User (Weekend) (2.7%) that show unique behavior patterns. The model performance evaluation resulted in a Quantization Error (QE) value of 0.339 and Topographic Error (TE) of 0.066, both on validation data and test data, indicating that the clustering results are quite accurate and the data mapping topology is well maintained. This research contributes to the understanding of mobile banking user behavior segmentation and can be used as a basis for a more adaptive and personalized time-based service strategy
Data Mining with Logistic Regression and Support Vector Machine for Hepatitis Disease Diagnosis
Full text linkHepatitis is a chronic and dangerous disease that can lead to death. Making early predictions to detect hepatitis is very important because many people still underestimate the disease. These predictions can be made by collecting patient data or health examination results, so that preventive measures can be taken faster and better. Early diagnosis of the disease is important for prompt management and treatment. The right stage of diagnosis activities and accurate disease prediction in time can save many patients. The magnitude of this disease problem in Indonesia can be known from various studies, studies, and disease observation activities. In this study, researchers will apply and compare data mining classification methods, namely the Logistic Regression method and Support Vector Machine to diagnose hepatitis disease. Based on the research, it is known that the Logistic Regression method has an accuracy rate of 84.62% and an under the curve (AUC) value of 0.841, then the Support Vector Machine method has an accuracy rate of 87% and an AUC value of 0.865. From the t-test results, it can be seen that there is no significant difference between the Logistic Regression and Support Vector Machine methods, because the value = 0.520>0.05. This shows that the Logistic Regression method has almost the same performance as the Support Vector Machine method. Hopefully the results of this research can help doctors determine a diagnosis more quickly and reduce the possibility of misdiagnosis so that early detection of hepatitis can be carried out more widely, especially in remote areas with limited health facilitie