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INDONESIA
Journal of Technology Informatics and Engineering
Published by Universitas Sains Dan Teknologi Komputer
ISSN : 29619068     EISSN : 29618215     DOI : 10.51903
Core Subject : Science,
Computer Science & IT
Power Engineering Telecommunication Engineering Computer Engineering Control and Computer Systems Electronics Information technology Informatics Data and Software engineering Biomedical Engineering
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 161 Documents
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A Hybrid Approach to Typo Correction in Indonesian Documents Using Levenshtein Distance Santoso, Joseph Teguh; Yan, Song
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.184

Abstract

This study developed a typo correction system for the Indonesian language by integrating the Levenshtein Distance algorithm with empirical methods. The system is designed to improve the accuracy of typo detection and correction in Indonesian texts, which feature complex morphological structures such as prefixes, suffixes, and compound words. The findings show that the system achieved a precision rate of 92% and an F1-score of 90.5%, indicating high reliability in providing relevant correction suggestions. Additionally, the system demonstrated efficiency in processing time, with an average of 0.8 seconds for short texts and 5.3 seconds for longer texts. The use of empirical methods enables the system to handle complex language variations, resulting in more contextually appropriate correction suggestions. User feedback indicated high satisfaction with the interface and the relevance of the suggestions provided. Overall, this research makes a significant contribution to the development of more adaptive and efficient typo correction systems for the Indonesian language and opens up opportunities for further development in the context of other similar languages.
Empowering Urban Farmers: An Asynchronous Learning Application for Greenhouse Management Wibowo, Mars Caroline; Santoso, Joseph Teguh
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.185

Abstract

This paper addresses the growing need for effective educational tools in greenhouse gardening, particularly for beginners lacking prior agricultural knowledge. Despite the increasing availability of mobile applications aimed at agricultural education, many existing resources fail to engage users through interactive experiences, thereby limiting their practical skill development. This study identifies a significant knowledge gap regarding the specific needs of novice gardeners and the effectiveness of current educational applications. To address this gap, we developed an innovative mobile application designed to facilitate asynchronous learning through interactive features such as discussion forums and quizzes. A mixed-methods approach was employed, involving user testing with 30 participants to evaluate the application’s usability and engagement levels. The results indicated that 90% of users found the application intuitive and easy to navigate, with enhanced motivation attributed to its engaging visual design. These findings suggest that the proposed application not only meets the educational needs of users but also fosters a more interactive and responsive learning environment. The implications of this research highlight the potential for mobile applications to significantly improve practical knowledge and skills in greenhouse management, ultimately contributing to more sustainable agricultural practices
Reliability of Arduino Serial Communication Systems: A Case Study on the Application of Cyclic Redundancy Check (CRC) Raharjo, Budi; Wibowo, Mars Caroline
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.186

Abstract

In embedded systems, serial communication plays a crucial role in data transfer, particularly in Arduino-based projects. However, factors such as electromagnetic interference, noise, and signal degradation can compromise data integrity, leading to significant errors. Effective error detection systems are essential to ensure reliable data exchange. The Cyclic Redundancy Check (CRC) is one such method known for its ability to detect errors. Despite its potential, the practical application and impact of CRC on Arduino communication systems have not been extensively explored. This study implements CRC within Arduino serial communication by designing and developing software that integrates CRC for real-time error detection. The study rigorously tests this implementation in various scenarios to evaluate its performance, comparing data integrity with and without CRC. The results show that incorporating CRC significantly improves the reliability of data transmission in Arduino applications, enhancing error detection accuracy. This improvement strengthens existing systems and provides a solid foundation for developing more complex communication frameworks. The research advances reliable communication systems in embedded technologies. By demonstrating CRC's effectiveness in enhancing data integrity, the study offers valuable insights for developers and researchers seeking to improve serial communication across different applications.
Error-Free Arduino Communication: Integrating Hamming Code for UART Serial Transmission Raharjo, Budi; Silalahi, Fujiama Diapoldo
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.187

Abstract

Serial communication is a fundamental method for data transfer in electronic devices, particularly in Arduino-based systems. However, existing protocols, such as Universal Asynchronous Receiver/Transmitter (UART), often lack robust error detection mechanisms, leading to potential data integrity issues. This study aims to address the knowledge gap regarding error detection in UART communication by implementing Hamming Code, a well-established method for detecting and correcting single-bit errors. The research employs a systematic approach, including data encoding before transmission and decoding with error correction at the receiver end. The results demonstrate that the integration of the Hamming Code significantly enhances the reliability of data transmission, reducing error rates and improving overall system performance. The implications of this research extend to various applications requiring high data integrity, such as industrial control systems and Internet of Things (IoT) devices. By providing a practical solution to the challenges of error detection in serial communication, this study contributes to the advancement of reliable communication systems in modern technology.
Leveraging Machine Learning for Personalized Recommendations in Mobile Tourism: A Study on Collaborative and Content-Based Filtering zainudin, ahmad; Siswanto, Edy
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.190

Abstract

The rapid growth of the tourism industry, coupled with the increasing reliance on mobile technology, necessitates the development of intelligent applications that enhance user experience through personalized recommendations. This research investigates the application of machine learning techniques, specifically Collaborative Filtering and Content-Based Filtering, to create a mobile tourism application that addresses the challenges of providing relevant and tailored suggestions to users. The primary objective of this study is to improve user satisfaction and engagement by delivering precise recommendations based on individual preferences and behaviors. To achieve this, the research employs a mixed-methods approach, combining quantitative data analysis from user interactions and qualitative assessments of user feedback. The study utilizes datasets sourced from reputable platforms, including user ratings and demographic information, to train the recommendation algorithms effectively. The evaluation of the implemented system demonstrates a significant increase in recommendation accuracy, leading to enhanced user satisfaction and increased visitation rates to tourist attractions. The findings indicate that the integration of Collaborative Filtering and Content-Based Filtering not only optimizes the personalization of recommendations but also fosters user loyalty and engagement with the application. By leveraging machine learning techniques, tourism providers can better understand user preferences, ultimately leading to a competitive advantage in a crowded market. This study contributes to the ongoing discourse on the intersection of technology and tourism, offering valuable insights for future research and application development in this dynamic field.
Utilizing phpMyAdmin for System Design in Enterprise Administration Wibowo, Mars Caroline; Wijanarko Adi Putra, Toni
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.193

Abstract

In today's digital landscape, effective data management is essential for organizations, particularly small and medium-sized enterprises (SMEs) that often struggle with traditional manual methods, leading to inefficiencies and data inaccuracies. This research aims to investigate the implementation of phpMyAdmin, a web-based database management tool, to enhance administrative systems within SMEs. The study employs a mixed-methods approach, integrating qualitative case studies and quantitative surveys to gather comprehensive insights into user experiences and operational performance. The findings reveal that the adoption of phpMyAdmin significantly improves data management efficiency, with 75% of respondents expressing satisfaction with its user-friendly interface. However, challenges such as security vulnerabilities and the necessity for user training were also identified, indicating that while phpMyAdmin offers substantial benefits, organizations must address these issues to fully leverage their capabilities. The implications of this research suggest that SMEs should prioritize investing in user training and implementing robust security measures to mitigate risks associated with data management. By doing so, organizations can enhance their operational efficiency and decision-making processes. Future research should focus on the long-term impacts of phpMyAdmin and explore its integration with other management systems to further optimize organizational performance.
A Robust Authentication Method for Electronic Banking Transactions: Two-Way Challenge-Response Approach Achlison, Unang; Miftahurrohman, Miftahurrohman; Siswanto, Edy
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.195

Abstract

The security of electronic banking transactions is becoming increasingly critical due to the rising threat of cyberattacks, which can result in financial and reputational damage to financial institutions. Despite the implementation of various authentication methods, vulnerabilities remain that can be exploited by attackers, particularly in the context of static passwords and tokens. This study aims to address these shortcomings by implementing the Two-Way Challenge-Response method, which offers a more robust and dynamic authentication approach. The method employed in this research involves the exchange of information between the client and server, where the challenges generated are unique to each authentication session. This process not only validates user identities but also ensures that the transmitted information cannot be predicted by third parties. The results of the study indicate that the application of this method significantly reduces the risk of attacks such as identity theft and replay attacks, while also enhancing the speed and efficiency of the authentication process. The implications of these findings suggest that the Two-Way Challenge-Response method can be an effective solution for enhancing the security of electronic banking transactions. By adopting this method, financial institutions can strengthen their security systems, increase user trust, and reduce the potential for losses due to cyberattacks. This research contributes significantly to the development of more secure authentication systems in the digital age
Framework-Driven Design: Analyzing the Impact of the Zachman Framework on LMS Effectiveness Silalahi, Fujiama Diapoldo; Nugroho, Setiyo Adi; Hartono, Budi
Journal of Technology Informatics and Engineering Vol 3 No 2 (2024): Agustus : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v3i2.196

Abstract

In today's digital era, Learning Management Systems (LMS) play a crucial role in education. Despite the availability of numerous LMS platforms, challenges in designing effective and efficient systems persist, particularly in integrating comprehensive frameworks like the Zachman Framework. This study aims to explore the application of the Zachman Framework in LMS design to enhance system effectiveness and user satisfaction. The research employs a mixed-methods approach, combining qualitative and quantitative methods. Data is collected through a survey involving 100 respondents, including instructors, LMS developers, and students. The study analyzes qualitative data using thematic analysis and quantitative data through descriptive statistical techniques. The findings reveal that 85% of respondents believe that applying the Zachman Framework in LMS design significantly improves system effectiveness. Additionally, the average user satisfaction score for LMS designed using this framework is 4.2 on a 5-point scale, indicating a high level of satisfaction. This research concludes that implementing the Zachman Framework not only aids in identifying user needs and designing essential system functions but also ensures that all elements are well-integrated. These findings provide valuable insights for LMS developers and educational institutions in creating more effective and responsive systems that meet user needs..
Optimization of Inclusive Education Through the Implementation of Artificial Intelligence: Opportunities and Challenges Jamaludin, Haris; Hartono, Budi; Kuncoro, Arsito Ari
Journal of Technology Informatics and Engineering Vol. 4 No. 2 (2025): AUGUST | JTIE : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v4i2.219

Abstract

Inclusive education is critical to ensuring equitable learning opportunities for all students, regardless of their abilities or backgrounds. This study aims to analyze the optimization of inclusive education by implementing artificial intelligence (AI), focusing on identifying the opportunities and challenges that arise. A systematic literature review was conducted as the research method, referencing five journals related to the application of AI in education and other relevant sectors. The findings reveal that AI has significant potential to enhance the quality of inclusive education by enabling personalized learning materials, real-time student data analysis, and improved teacher-student interactions. These advancements can help address diverse learning needs and promote a more inclusive learning environment. However, several challenges must be addressed, including technological disparities, limited infrastructure, and ethical concerns related to AI usage, such as data privacy and algorithmic bias. The study concludes that the successful implementation of AI in inclusive education requires collaborative efforts among governments, educational institutions, and other stakeholders to ensure accessibility, equity, and sustainability. Key recommendations include the development of supportive policies, enhancement of digital literacy among educators and students, and investment in technological infrastructure to bridge the digital divide. This research contributes to the growing discourse on the integration of AI in education, providing insights for policymakers and practitioners aiming to harness AI's potential for inclusive education.
Contextual Framework for Remote Intelligent Monitoring and Detection System for Prediction of Pregnancy Complications Udonna, Uduakobong; Umoren, Imeh; Ansa, Godwin
Journal of Technology Informatics and Engineering Vol. 4 No. 2 (2025): AUGUST | JTIE : Journal of Technology Informatics and Engineering
Publisher : University of Science and Computer Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtie.v4i2.244

Abstract

Maternal health disorders can cause complications and harmful incidents in women during pregnancy. To minimize risks, this research developed a platform powered by a supervised machine learning model (SMLM) to support remote intelligent monitoring and prediction of pregnancy complications caused by hypertensive disorder, gestational diabetes, and related indicators. The study used real-world datasets with six UCI Machine Learning Repository features to identify and predict Maternal Health Risk (MHR) factors. A Support Vector Machine (SVM) algorithm was applied to construct the classifier model, which was trained and evaluated using StratifiedKFold cross-validation (k=10). The model achieved 80% accuracy with a precision, recall, and F1-score of 77%. The outcome of this work is the P-Health mobile application, designed to record and track blood pressure, blood sugar, heart rate, body temperature, and weight, while predicting the risk level of pregnancy complications through inference from the integrated machine learning model. Developed with Kotlin and Android Studio, the application enables healthcare practitioners to remotely monitor patients’ vitals in real time. This innovation addresses the challenge of early detection of pregnancy complications and provides continuous monitoring and assessment. The findings suggest that P-Health can improve early detection and timely intervention, helping medical specialists minimize maternal health risks. The system also has the potential to raise public awareness of maternal health issues, thereby contributing to the prevention of complications during pregnancy.

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