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International Transactions on Artificial Intelligence (ITALIC)
Published by Pandawan Sejahtera Indonesia
ISSN : 29636086     EISSN : 29631939     DOI : https://doi.org/10.33050/italic
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Library & Information Science
International Transactions on Artificial Intelligence (ITALIC) is an international, open-access journal established to publish groundbreaking research in the field of Artificial Intelligence (AI). ITALIC focuses on both theoretical and experimental AI research and explores its applications across various interdisciplinary fields. The journal places a strong emphasis on emerging technologies that contribute to sustainable development, in line with the United Nations Sustainable Development Goals (SDGs). ITALIC welcomes contributions that cover a wide range of AI applications, including machine learning, neural networks, natural language processing, AI in energy management, sustainability, and urban infrastructure. In addition to original research, the journal publishes reviews, mini-reviews, case studies, and commentaries, fostering dynamic discussions on the evolving role of AI in addressing global challenges. All submissions are rigorously reviewed through a double-blind peer-review process, ensuring high academic standards. As an open-access journal, ITALIC makes its content freely available to a global audience, enhancing the dissemination of critical insights. Each article is assigned a Digital Object Identifier (DOI), ensuring permanent access and easy referencing.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 68 Documents
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Analysis of Expert System Implementation in Computer Damage Diagnosis with Forward Chaining Method Muhammad Rehan Anwar
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.213

Abstract

The necessity for computerization is currently growing quickly because computers are now necessary for all needs connected to business and daily life. Therefore, users' ability to quickly and easily access information seems to be hindered by maintenance and repairs. An expert system is a computer-based method that uses facts, knowledge, and reasoning to solve issues that are often best handled by a subject-matter expert. Expert systems are created for expertise that is close to human capabilities in a given sector. A computer expert currently needs a lot of time to diagnose computer damage, and even technicians frequently put off their work in order to come up with fixes. Forward chaining was used in the construction of this system. In order to derive conclusions, forward chaining is employed to test the given factors against the recorded rules in the system. As a result, this expert system was developed to assist users in dealing with the damage and early maintenance that frequently affect computer systems. using computers in everyday tasks.If we are familiar with the Forward Chaining method used by the expert system to trace computer damage, the known crash features to address frequent crashes on that PC, and the application in object-oriented programming languages such as Visual Basic 6.0, we can determine where the damage is located.
Internet of Things, Big Data, and Artificial Intelligence in The Food and Agriculture Sector Suryari Purnama; Wahyu Sejati
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.274

Abstract

Big data often referred to as streaming data produced by the internet of things creates new options for monitoring food and agricultural processes. Along with sensors, social media big data is also playing a bigger role in the food business. The IoT, big data, and artificial intelligence are discussed in this review along with how they will impact the agri-food industry in the future. We begin with an introduction to the fields of IoT, big data, and AI before talking about how IoT and big data analysis are used in agriculture, including smart farm equipment, crop imaging using drones, and monitoring of greenhouses, food quality assessment using spectral techniques and sensor fusion, and eventually, food safety using gene sequencing and blockchain-based digital traceability. The commercial viability of applications and the outcomes of translational research are given significant consideration.
Overview of Life Cycle Assessment of Current Emerging Technologies Cicilia Sriliasta; Vivi Meilinda
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.290

Abstract

For its potential to facilitate the development of cutting-edgetechnologies with enhanced environmental performances,projected useat basic levels of life cycle analysis (LCA)technological readiness levels (TRL) has attracted enormousinterest in recent literature. But the normal LCA standardsfind it very difficult to evaluate developing technologies,necessitating methodological advancements in the presentLCA framework due to inadequate data, questionablefunctioning, scale-up problems, and uncertainties. We reviewpublished literature in this paper to identify majormethodological challenges and key research efforts to addressthese issues, with a focus on recent developments in five keyareas: cross-study comparability, data availability and quality,scale-up issues, uncertainty and uncertainty communication,and assessment time. Additionally, we provide a number ofsuggestions for further study to assist in the assessment of newtechnologies at low technical readiness level: (1) the creation of auniform framework and reporting procedures for life cycleassessments (LCAs) of developing technologies; (2) theincorporation of additional tools with LCA; and (3) the creation of adata repository for cutting-edge materials, procedures, andtechnologies. Decision-making techniques, such as multicriteriadecision analysis, risk analysis, and techno-economic analysis.
Remote Medical Applications of Artificial Intelligence Rini Kartika Hudiono; Sri Watini
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.292

Abstract

Artificial intelligence, usually referred to as AI, is one of thetechnologies that is a cornerstone for the sustainability ofhuman activities. When we hear the term AI, we instantly seerobots that can perform tasks independently much like aperson. An artificial intelligence (AI) system might be used toforetell user interests. What role does artificial intelligence (AI) playin the usage of telemedicine, for instance, in the context of mobileapplications? Benefits for the patient will be provided through theapplication of AI technology. Definition of mobile telemedicine as itrelates to Halodoc refers to a network-based health consultationservice that allows patients and doctors to consult. AI may research apatient's history and the actions that are performed on them. In orderto increase performance efficiency between physicians and patientsand ensure the security and confidentiality of patient data, this datacollection generates suggestions regarding services and complaintswithout directly contacting the doctor, patient information privacy,etc.
Exploratory Activities in Educational Games using Fuzzy Logic Anggy Giri Prawiyogi; Riya Widayanti
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.294

Abstract

In educational games, one of the concepts for designing activities is the use of gratitude. Learning consists of the discovery, dream, design, and destiny phases. exploration activity or discovery search and exploration are the main activities. search activity, exploration, it takes quite a long time and involves uncertainty in its execution. Reward we need momentum to continue this discovery effort. Good rewards Keep You Focused players search and explore by providing performance metrics. This study use fuzzy logic to shape dynamic rewards behavior in discovery activities. The standard the input used is the fraction of exploration and time to generate a dynamic reward discovery activity. As a result of this research, fuzzy logic can generate three levels of reward variants.
Development of Automatic Industrial Waste Detection System for Leather Products using Artificial Intelligence Lista Meria
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.296

Abstract

This rapid world situation led to a significant growth in the amount of waste, including in economic activity. Due to the huge amount of waste growth every year, effective and efficient waste management is needed to protect our environment. In leather products economic activities, waste management is very important because it can have a significant effect on labor and manufacturing processes. Given the problem, waste management technology is considered the answer to solve the situation. Current investigations report remarkable results from the sealing of artificial intelligence-based tools that serve to detect and acknowledge whether it is an industrial waste. This artificial intelligence-based tool proved to be the answer to this situation approach capable of grouping several types of garbage with good performance. Despite these advantages, this artificial intelligence-based tool still finds some limitations, such as high computing demands, especially for deep learning networks. In view of these constraints, we propose a deeper learning network that is more appropriate for recognizing the waste of economic activity. In the course of this investigation, we used a Single Shot Detector to acknowledge and classify economic activity waste. The proposed completion ideas are carried out in the TrashNet dataset and the Waste Picture dataset. Our solution achieved an mAP of 0.8813, accuracy of 0.9795, performance measure of 0.9985 and conformance of 0.9693 in the training process. Meanwhile, in the process of verifying the tool, we achieved an average accuracy of 0.8254. Based on these experiments, we can conclude that our solution is suitable for detecting waste of economic activity and has the opportunity to be implemented as an installed system for programmatically recognizing waste of economic activity.
Technology Integration in Data Analysis using Data Science Alwiyah
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.300

Abstract

Nowadays, data has become a very important thing for an entity. Many entities are competing to utilize the information and data they have. Because of this, data analysis has become very important. However, with the increasing amount of data available, managing and analyzing data has become increasingly difficult with the methods used previously. With the development of technology, new data analysis methods can be used to overcome this problem. Nowadays, we have to cope with not only structured data but also unstructured data.
An Overview of Concepts, Applications, Difficulties, Unresolved Issues in Fog Computing and Machine Learning Oscar Jayanagara; Dewi Sri Surya Wuisan
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.318

Abstract

Numerous fog computing apps and services are emerging as a result of the large volumes of data produced by systems based on fog computing. Additionally, the crucial field of machine learning (ML), which has made significant advancements in several academic areas, incorporating speech recognition, robotics, and neuromorphic computing, in addition to computer graphics and natural language processing (NLP).. The aim of current research provided insight into providing a list of the fog computing-related ML operations. The security, capacity, and latency standards for networks must be met by many IoT applications. Cloud computing does not, however, satisfy these needs. Today's technology can satisfy these objectives, and edge computing is one such option. The model enables traffic analysis and sensor data analysis. The management of resources, accuracy, and security are three areas of fog computing that we highlight in this thorough assessment of the most recent advancements in ML approaches. Additionally highlighted is the function of ML in edge computing. Additional viewpoints on the ML domain are presented, including those on the different kinds of application support, techniques, and datasets. Finally, open questions and research difficulties are highlighted.
Development of Mobile Learning Applications for Android Based on Artificial Intelligence Tatik Mariyanti
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.333

Abstract

In order to enable students to study autonomously and without being constrained by time and distance, this research was done to design an M-Learning learning media based on learning media on artificial intelligence. constrained by time and space, as well as to boost students' enthusiasm for studying. The following are the problems that need to be solved by this research: (1) How feasible is an android-based M-learning application for the field of artificial intelligence? (2) What are the students' reactions to the M-learning application built for Android in the Artificial Intelligence course?Research and development, sometimes known as R&D, is the research methodology employed. Students in the informatics engineering department at Raharja University served as the study's research targets. Techniques Instrument reliability and validity assessments as well as questionnaires are employed as data gathering methods respondents. Then, the examination of media viability and student reaction is performed as a data analysis approach. Descriptive analysis was done on the student replies. (1) Media validation by professional validators is calculated at 92.5% by percentage, according to the results. On the basis of this, it can be said that the android-based M-learning application falls within the category of "Very Excellent" and is appropriate for usage. (2) The results of the M-learning application for Android-based students were positive, with a 79.5% response rate.
Sector Analysis of Islamic Capital Markets and Artificial Intelligence Functioning as Sharia Advisors Widhy Setyowati; Intan Sri Rahayu
International Transactions on Artificial Intelligence Vol. 1 No. 2 (2023): International Transactions on Artificial Intelligence
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v1i2.334

Abstract

Artificial intelligence technologies will have a significant impact on a variety of career areas, including jobs in finance and law. The fact is that the Islamic capital market sector tends to use AI technology. There are now proposals to replace the role of sharia advisors with AI technology. The research conducted is legal research using qualitative methods. The legal historiographical approach was chosen to show the responsibility of the sharia board in realizing the concept of Islamic urbanism. The idea of Islamic urbanism is closely related to AI technology and the capital market as the main places for both of them to work in cities. This research has three objectives. It analyzes the role and function of artificial intelligence technology, Islamic capital markets, and the part of Sharia Advisors in the industry. Then the problem of using AI technology in the Islamic capital market is identified. Moreover, it offers a solution to using the proposed innovative technology. This paper argues that the ability of technology to replace the role of Islamic advisors in the Islamic capital market sector is limited. This is because AI technology, although advanced, can only deal with the physical world of cities but still needs to embody the concept of Islamic urbanism. At the same time cannot replace the role of sharia advisors.

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