TIERS Information Technology Journal

Revolutionizing Technology Education with Artificial Intelligence and Machine Learning: A Comprehensive Systematic Literature Review

Musawer Hakimi — 2024-11-26

Machine learning and artificial intelligence in education will help to personalize the student learning process, reduce the time wastage in imploding administration systems, and innovate teaching methods. The article reports the findings of a study on the effects of these technologies on the educational systems of application, benefits, and challenges and looks forward to the implications. This has been realized through a systematic review of peer-reviewed journal articles, government reports, and policy documents published between 2021 and 2024. Results show great benefits, including enhanced personalized learning experiences and administrative efficiencies, but also highlight several challenges, such as equitable access, data privacy, and the need for professional development of educators. Rather, this research outlines the imperatives that there is a need to address challenges for the realization of the potential of AI and ML in education. The paper makes recommendations for key stakeholders and points out areas for possible future research to guide sustainable and ethical integration into educational systems. Further research should be done to understand whether these technologies affect student outcomes in the long term and are applicable with the same efficacy in other cultural and socioeconomic contexts.

Design of an IoT-Based Automatic Weighing System for Catfish Farming to Support Smart Aquaculture

Sutra Wardatul Jannah — 2024-11-26

Enhancing the accuracy and efficiency of the catfish weighing process is essential for farmers to optimize distribution to retailers and wholesalers while improving productivity and operational performance. This study focuses on developing an IoT-based automatic weighing system to provide a real-time and automated solution to these challenges. The proposed system incorporates a load cell sensor for weight measurement, an ESP32 microcontroller with a WiFi module for seamless data transmission, and an intuitive web-based interface for monitoring and control. Powered by solar energy, the system emphasizes the integration of renewable energy in aquaculture. The research involves designing the system's mechanical, electrical, and software components to create a practical and accessible tool for farmers. Field trials on catfish farms assess the system’s performance in terms of accuracy and efficiency, comparing it to conventional manual weighing methods. This innovation aims to boost operational efficiency in aquaculture while contributing to the adoption of sustainable and intelligent farming technologies.

Mobile-Based Decision Support System for Recommending Tourism Attraction Using MAGIQ-ARAS Methodology

Gede Surya Mahendra — 2024-12-06

Tourism in Bali faces challenges such as overcrowding, poor management, and diverse visitor preferences, which hinder effective decision-making for tourist destinations. This study introduces an Android-based DSS using the MAGIQ-ARAS. The MAGIQ method simplifies the weighting process, while the ARAS method evaluates alternatives to produce utility-based rankings. Together, MAGIQ-ARAS provide a structured approach for generating tourist recommendations tailored to user preferences. The research follows a combination of the CRISP-DM framework for data preparation and the Waterfall Model for system development. Field studies, interviews, and literature reviews informed the design of a mobile application that integrates MAGIQ and ARAS. Black-box testing verified functionality, and accuracy testing using a confusion matrix evaluated the alignment between recommendations and user preferences. The results demonstrate the system's effectiveness, achieving 90% accuracy in matching recommendations with user preferences. Black-box testing confirmed that all features, including preference weighting and interactive navigation, operated as intended. The system simplifies MCDM and enhances user satisfaction through its efficient and user-friendly interface. The study concludes that the MAGIQ-ARAS-based mobile application offers a reliable solution for tourist recommendations. Future work should explore real-time data integration and expand application to other tourism regions to enhance adaptability and usability.

Development of an IoT-Enabled Automatic Poultry Feeder and Cage Temperature Monitoring System Using Microcontroller Technology

Teguh Setiadi — 2024-12-06

In general, chicken farmers still use conventional systems to feed the chickens they raise. They use their hands to sprinkle feed on the feed poles and walk along the cage where the cages for the chickens they raise are very large. Such activities for chicken farmers will take up time and energy. Feeding chickens can be made easier by using mechanical devices controlled by electronic equipment. The aim of this research is to design and create an IoT-based automatic chicken feeding tool. In designing this tool, we started by designing an IoT-based automatic chicken feeding tool. Where the Servo is a feed pusher in the pipe to spill animal feed into the feeder. The results of this research show the performance of Servo which functions to provide automatic chicken feed. The results of IoT testing which functions as a timer for giving chicken feed to this tool are quite accurate. This is proven by the difference between the time on the tool and the time on the laptop of only 1 second. And temperature monitoring can be seen on the LCD, if the temperature is above 30 degrees, the fan or fun will turn on, and if it is below 30 degrees, the light will turn on automatically.

Evaluation of IT Governance in Indonesia's One-Door Investment and Integrated Services Institution using COBIT 5

Wahyu Indra Satria — 2024-12-25

This research aims to evaluate the information technology governance at Indonesia's One-Door Investment and Integrated Services Institution using the COBIT 5 framework. COBIT 5 is a comprehensive framework that provides a model for managing and governing information technology within an organization, to ensure the achievement of strategic and operational objectives. The research was conducted through several stages, including identifying relevant information technology processes, data collection through questionnaires and interviews, and analysis of the evaluation results using capability levels provided by COBIT 5 framework. The study results indicate that most information technology processes at Indonesia's One-Door Investment and Integrated Services Institution are at capability levels that require improvement, particularly in information technology risk management, performance management, and internal controls. Several recommendations are provided to enhance information technology governance at Indonesia's One-Door Investment and Integrated Services Institution, such as strengthening information technology policies and procedures, increasing human resource capacity through continuous training, and implementing regular monitoring and evaluation systems. By adopting these recommendations, it is expected that information technology governance at Indonesia's One-Door Investment and Integrated Services Institution can be optimized to support the achievement of organizational goals better and improve public services for the citizens.

The Integration of Artificial Intelligence in Project Management: A Systematic Literature Review of Emerging Trends and Challenges

Irshad Ahmed Hashimzai — 2024-12-25

The integration of Artificial Intelligence (AI) in project management has emerged as a transformative approach, revolutionizing traditional practices by enhancing efficiency, decision-making, and risk management. Despite its potential, organizations face significant challenges, including high implementation costs, concerns over data privacy, and resistance to change, which hinder effective adoption. The purpose of this study is to explore emerging trends, key applications, and challenges of AI in project management, while also evaluating its impact on improving risk management, resource allocation, and decision-making in complex projects. The study employs a systematic literature review (SLR) methodology, adhering to the PRISMA protocol, to analyze peer-reviewed articles from MDPI, IEEE, Science Direct, and Emerald databases, published between 2018 and 2024. Keywords combined with Boolean operators were used to filter relevant studies, ensuring a balanced and focused selection of high-quality publications. The results reveal AI's capacity to proactively identify risks, adapt to dynamic project environments, and optimize resource allocation, ultimately enhancing decision-making efficiency and project outcomes. However, challenges such as implementation costs and resistance to organizational change remain critical barriers. The implications suggest that while AI significantly enhances project management, addressing these challenges is essential for broader adoption and scalability. This research concludes that AI is a game-changer in project management, offering insights into emerging trends and critical challenges. Future research should focus on developing scalable, cost-effective AI solutions to overcome adoption barriers, thereby extending the benefits of AI integration across diverse industries.

Forward Chaining Method for Diagnosing Diseases and Pests in Melon Plants

Jum Dapiokta — 2024-12-25

There are many problems encountered in the field of agriculture, for example problems about diseases and pests in melon plants. Experts or experts in the field of agriculture rarely need to build a system that is able to adopt human processes and ways of thinking in the form of an expert system. The purpose of this study is to build an expert system to diagnose diseases and pests in melon plants using the forward chaining method. A reasoning that starts from facts first to test the correctness of a hypothesis. The system was tested using the black box testing method which was tested on experts and melon farmers. Based on the results of testing using the black box testing method tested on experts and farmers, the results of the assessment were obtained that the expert system for diagnosing diseases in melon plants was proven to run well as expected with 100% validation. The end result of this expert system is to make it easier for users to carry out the consultation process by providing a list of indication of diseases and pests experienced. Then the control of the type of disease and pest will be displayed according to the selected indication. In addition, this expert system also makes it easier for admins to update data such as disease data, indication and control. This expert system application program is also not only beneficial for experts but can also be useful for farmers that ordinary people who do not understand a little about melon plant diseases and pests.

Decision Support System for Laptop Selection Recommendations Using the Weigted Product (WP) Method

Anggeraeni Agustin Muris — 2024-12-25

The many types of specifications, colors and brands of laptops are complicated and confusing for ordinary people who are going to buy laptops. The reason is, there are many variants of laptops on the market with different specifications. To help potential consumers in choosing a laptop that suits their needs, a decision support system (SPK) is needed that can provide the most appropriate laptop recommendations. This study discusses the decision support system for laptop selection recommendations using the Weighted Product (WP) method. This method is used to help consumers choose a laptop that suits their needs based on predetermined criteria, such as processor, RAM, Storage, and Price. After a search of the vector to get the ranking, the largest vector value of 0.124 was obtained on Sony, Appel, and Dell Alternatives to be recommended in the selection of laptops. Based on the results of the research, it can be concluded that the decision support system (SPK) with the Weighted Product (WP) method can provide laptop recommendations that suit the needs of users. This research provides benefits for users in choosing the right laptop that suits their needs. In addition, this research can also be the basis for the development of a decision support system for the selection of laptops or computers in other fields.

Experimental Comparison of Encryption Algorithms On Smart Devices

Qurban Ali Frugh — 2024-12-25

Now, the technological environments rely on a large number of users and devices interconnected in such a way as to be able to share information and exchange resources. For such reasons, security becomes of prime importance inside these networks. Especially, encryption algorithms widely used in smart metering systems form the very backbone of ensuring security. It is unique according to every single parameter: the level of security achieved, speed, operational complexity, length, and type of key used. A comparison of performance and throughput for the most used encryption algorithms, such as AES-128, AES-192, RC4, Blowfish, and ECDSA, is presented here. Such devices, for instance, smart meters, usually represent very resource-constrained computational capability, memory, and data transfer. For these reasons, the experiments investigate performance impacts of using different encryption algorithms on a smart meter environment in a scaled setup. Experiments were run on a laptop device and then downscaled according to the limitation characteristics of the smart meter target device. As for the scaling, it has been performed concerning key factors: CPU of the smart meter, RAM, and cache memory. Execution times of the encryption and decryption processes were measured, as well as the throughput of messages for various file sizes. Quantitative key results obtained included: RC4 with a throughput of 25.37 Kbytes/sec, whereas AES-128 has 4.87 Kbytes/sec, while in ECDSA-256 the performance is much lower: its verification throughput amounts to 0.0023 Kbytes/sec. The results showed significant variations in performance, speed, and throughput between these algorithms. Even considering small smart devices, the encryption and decryption processes yielded efficient throughputs. These findings underscore the importance of choosing the right encryption algorithm for smart meters, balancing both security requirements and resource limitations to ensure optimal performance.