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Internet of Things and Artificial Intelligence Journal
Published by Association for Scientic Computing Electronics and Engineering
ISSN : -     EISSN : 27744353     DOI : https://doi.org/10.31763/iota
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Internet of Things and Artificial Intelligence Journal (IOTA) is a journal that is officially under the auspices of the Association for Scientific Computing, Electronics, and Engineering (ASCEE), Internet of Things and Artificial Intelligence Journal is a journal that focuses on the Internet of Things (IoT), ISSN 2774-4353, publishing the latest papers in the IoT field and Artificial Intelligence (AI) i.e., Machine Learning (ML), and Deep Learning (DL)., etc., Topics can be included in this journal : IoT for various applications ( medical, sport, agriculture, smart city, smart home, smart environment, etc.) IoT communication and networking protocols ( LoRa, WiFi, Bluetooth Low Energy, etc.) IoT enabling technologies IoT system architecture IoT with a Recently Sensors Technology IoT with Wireless Sensor Network (WSNs) Technology Cloud-based IoT IoT data analytics IoT Security IoT Management Services IoT with Low Power and Energy Harvesting Future technologies for IoT Future Internet design for IoT Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) Drone or UAV, and IoT Analyzes IoT with a Financial Technology (FINTECH) Managemen approach IoT for Education Technology IoT for Industry Computers & Security :: computer security, audit, control and data integrity in all sectors - industry, commerce and academia Computer application for Economy, Finance, Business, Micro, Small & Medium Enterprises (MSMEs), Accounting, Management, and other sectors Review articles on international & national legal rules in the use of computer software, internet of things, frequency usage, etc. Internet of Things and Artificial Intelligence Journal has a frequency of being published 4 times a year or 4 issues every year (February, May, August, and November) with the Peer review process.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 174 Documents
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Prediction of New Customer Segmentation Classification Using Artificial Intelligence Project Cycle Orange Data Mining Kosat , Fransiska Febriyanti; Rema, Yasinta Oktaviana Legu; Ullu, Hevi Herlina
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.813

Abstract

This research aims to predict the right segmentation group or classification of new customers to become a classification comparison data carried out by the sales team to determine the strategy used to enter the market, whether it can be said to be feasible or not. This article discusses the basis of the method used, i.e., Machine Learning, discussed in detail about Artificial Intelligence (AI). Also discusses what is Classification, Segmentation, Data Mining, Neural Networks, Naive Bayes, Decision Trees, Random Forest (RF), and Support Vector Machine (SVM). This article discusses comprehensively the method used, and the development of Modeling, in the results and analysis section, comprehensively shows the prediction analysis of new customer segmentation classification, algorithm performance results of several methods, and distributions analysis. With the percentage prediction of new potential customer segmentation using the Neural Network method, the percentage prediction of Segmentation A is 25.21%, the percentage prediction of Segmentation B is 21.77%, the percentage prediction of Segmentation C is 23.49%, the percentage prediction of Segmentation D is 29.53%. The percentage of segmentation that has been calculated by the company is the percentage of Segmentation A of 32.13%, the percentage of Segmentation B of 20.89%, the percentage of Segmentation C of 17.69%, and the percentage of prediction of Segmentation D of 29.29%.
Design of a Monitoring System for the Number of Visitors and Room Temperature Telkom Plaza Bengkulu suwarto, suwarto; Riska, Riska; Mardiana, Yessi
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.815

Abstract

The development of Internet of Things (IoT) technology has brought significant impacts on various aspects of life, including the management and monitoring of public facilities. One of the public facilities that requires monitoring the number of visitors isTelkom Plaza Bengkulu. The main problem atTelkom Plaza Bengkulu is the absence of an effective monitoring system that tracks the number of visitors and room temperature in real time. The purpose of this research is to design a system that can monitor the number of visitors and room temperature automatically, help management make decisions, and optimize services. The research is expected to contribute to the development of information technology in the management of public facilities in the digital era. The method used is an experimental method to design an IoT-based monitoring system. This system uses PIR and DHT22 sensors as input for ESP32, then displays data on the number of visitors and room temperature in real-time through the website and smartphone application using the Blynk IoT platform, as well as automatic fan operation based on room temperature. The test results show the success of the IoT-based monitoring system for the number of visitors and room temperature of Plaza Telkom. The PIR sensor detects movement up to a distance of 2 meters. DHT22 sensor measures temperature with an accuracy of ±0.02%. The relay module controls the fan responsively. Blynk dashboard displays real-time data. The user interface works on laptops and smartphones, providing consistent access and display. An IoT-based monitoring system for the number of visitors and room temperature forTelkom Plaza Bengkulu was successfully designed and implemented. This system fulfills the research objectives and can be applied in other Plaza Telkom locations, although there is still a need for improvement and room for further development.
Development of an Information System for eTax Return Reporting PPh 21 Employees at PT. FBR Mitra Sejati Hasibuan, Maimunah Permata Hati; Prasetio, Primadi
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.816

Abstract

This research aims to develop an information system that supports collecting Income Tax (PPh) for employees in a tax consulting company. This research analyzes the suitability of the tax collection procedures applied by the company and the applicable tax provisions. The method used in this research is descriptive analysis based on data obtained through interviews, observations, and literature review. The results show that the principle of income tax collection in tax consulting companies is in line with the general tax withholding method, with estimated net income as the basis for calculation. The tax rate variations applied include the provisions in Article 17 of the Income Tax Law and related government regulations. The information system developed aims to improve efficiency and accuracy in the reporting of Income Tax Return 21 and support better tax compliance.
Website-Based Retail Sales Monitoring System at Purbaratu Market Cooperative, Tasikmalaya City Cahyadi, Cepi; Jaelani, Rusani; Arfian, Andi
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.817

Abstract

Purbaratu Market is a gathering place for traders and buyers who always have buying and selling transactions every day. This market has a cooperative to monitor everything in the market, but the retail sales transaction process system in the current cooperative is still traditional in the buying and selling of merchandise, therefore, transactions need to be monitored carefully and quickly to find out transactions consisting of various types of goods, so it requires accuracy in recording the type and number of products sold, Based on the description of existing problems, an increase in services in the field of computerization is carried out. That is, this traditional system will be developed into a digital system in the form of a monitoring system for Retail Sales of the Purbaratu market cooperative. This technology is made using PHP and MySQL databases. The purpose of planning this application is to provide convenience in the process of transactions and processing retail sales data in the Purbaratu market cooperative.
Use of Artificial Intelligence Applications: Friend or Threat for Indonesian Language and Literature Education Students at Singaperbangsa University of Karawang Amal, Bahar; Khaierunnisa, Aqillah; Rahmawati, Elisa; Syifa, Naora; Dewani, Pramesvary Nazwa; Septariyani, Putri Ratih; Fauzi, Syahrul Ilham
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.821

Abstract

This research aims to explore the impact of artificial intelligence (AI) on students of Indonesian Language and Literature Education students at Singaperbangsa Karawang University. Through a survey of Indonesian Language and Literature Education students, this study shows that AI has become a popular tool to support the learning process, but also raises concerns about excessive dependence and a decline in critical thinking skills. The results show that AI can be a valuable tool to assist students in various academic tasks, but can also pose a threat if used unwisely. Therefore, it is important for students to understand the potential and limitations of AI, and to use it in a balanced manner to achieve optimal learning outcomes.
Performance Comparison of K-nearest Neighbor, Decision Tree, and Random Forest Methods for Classification of Cyber Defense Master Scholarship Recipients dinisfusya'ban, dinisfusya'ban; Suharjo, Bambang; Indrajit, Richardus Eko
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.823

Abstract

Cyber defense education is essential for developing a workforce capable of addressing evolving cyber threats, particularly in the military sector, where interconnected systems are vital for secure communication and command. This research aims to enhance the selection process for the Cyber Defense Master Scholarship at the Republic of Indonesia Defense University by employing machine learning algorithms. The study compares the performance of K-Nearest Neighbor (KNN), Decision Tree, and Random Forest for classifying eligible scholarship candidates. The results reveal a clear performance hierarchy: KNN achieves a moderate accuracy of 80.68%, offering simplicity and interpretability but lacking the precision of other models. The decision Tree performs with high accuracy (98.86%) but shows vulnerability to overfitting, which may impact generalizability to unseen data. Random Forest emerges as the most robust model, achieving the highest precision and overall stability, with minimal compromise on other metrics. Given the scholarship’s selection requirements, Random Forest is recommended for tasks needing high accuracy and resilience against overfitting, while KNN and Decision Tree offer suitable alternatives for simpler, more interpretable applications.
Building a Web-Based Application for Transaction Recording and Inventory Management at Unipro Store Peter, Peter; Mulyawan, Bagus
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.827

Abstract

Unipro Store, a retail shop specializing in cellphone accessories, faces significant challenges in recording transactions and managing inventory due to its reliance on manual processes. All transactions, whether purchases from suppliers or sales conducted through various channels such as WhatsApp, Tokopedia, Shopee, or in-store are still documented manually using a notebook. This manual system makes it difficult for shop owners to retrieve historical transaction data and increases the risk of data loss, as there is no backup if the notebook is lost or damaged. To address these issues, a transaction recording and inventory management application has been designed to streamline the management of product stock, sales, and purchase data. The application supports two types of users: the owner and the admin. Its development follows the Software Development Life Cycle (SDLC) using the waterfall model. During implementation, HTML, CSS, and JavaScript were utilized alongside the Bootstrap and ASP.NET frameworks to develop the application, with Microsoft SQL Server selected as the database solution. In the testing phase, user acceptance testing (UAT) was conducted using a black box testing approach, successfully passing all test scenarios. Additionally, a System Usability Scale (SUS) questionnaire was distributed, yielding a final score of 81.67, which falls under grade A in the usability assessment.
Automating Internship Data Management Processes in a Web-Based Application: A Case Study of FTI UNTAR Gosal, Maria Rosa; Wasino, Wasino; Tony, Tony
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.828

Abstract

The Faculty of Information Technology at Universitas Tarumanagara (FTI UNTAR) supports the “Merdeka Belajar-Kampus Merdeka” (MBKM) industrial internship program, providing students with valuable work experiences through partnerships with companies and accessible internship listings. However, the existing management system lacks comprehensive digital support, leaving many processes manual and prone to inefficiencies, delays, and data errors. To address these challenges, this paper presents the design of a web-based application that aims to streamline internship data management by automating core processes and reducing administrative overhead. The application leverages the iterative methodology within the Software Development Life Cycle (SDLC), allowing for flexible adjustments and continuous refinement through repeated cycles of development and testing. Following development, the application successfully passed User Acceptance Testing (UAT) with all user types, including students, faculty advisors, company mentors, and administrators. Additionally, a System Usability Scale (SUS) survey conducted specifically for student users resulted in an excellent final score of 90.42, graded as A+. This outcome confirms the application’s effectiveness in enhancing operational accuracy and accessibility, elevating the overall quality of internship management at the faculty.
Implementing Hierarchical Role-Based Access Control for Document Administration in Student Organizations Destini, Janessa Sarah; Tony, Tony
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.832

Abstract

Student organizations in higher education institutions play a pivotal role in fostering leadership and collaboration. Despite their importance, many still utilize manual document administration processes, resulting in inefficiencies, delays, and a lack of transparency. This research introduces the design and implementation of a web-based Document Management System integrated with Hierarchical Role-Based Access Control (HRBAC) for student organizations at Universitas Tarumanagara. The system adopts a structured and secure framework tailored to the organization’s approval hierarchy, encompassing roles such as UKM/HIMA, BEM, DPM, Faculty Advisors, Deans, and the Student Affairs Office. Each role is assigned specific access privileges to ensure secure and efficient document submission and approval workflows, aligned with organizational needs. The system was developed using the Laravel framework, PHP, HTML, SCSS, JavaScript, and MySQL, following the Waterfall methodology. Usability was evaluated using the System Usability Scale (SUS), achieving a score of 78.33, categorizing it as “Good” in terms of user experience and navigability. The findings indicate significant improvements in process automation, role-based access control, and document traceability. This research offers a comprehensive model for digital transformation in student organization administration, emphasizing the effectiveness of hierarchical access control in optimizing administrative workflows within academic institutions.
Student Feedback Systems: Developing a Web-Based Solution for Efficient Complaint Processing at Faculty of Information Technology Tarumanagara University Phratama, Owen Maytrio; Handhayani, Teny; Perdana, Novario Jaya
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i4.834

Abstract

The collection of student feedback, encompassing aspirations, and complaints, serves as a cornerstone in improving the quality of education and fostering institutional responsiveness in higher education. However, many universities, including Tarumanagara University, especially the Faculty of Information Technology still rely on manual processes for submitting these concerns, necessitating face-to-face interactions with faculty administrative personnel. This traditional approach often results in inefficiencies, including delayed responses and difficulty tracking complaints. This research addresses these issues by proposing the development of a web-based application designed to centralize and streamline the processing of student complaints and aspirations. Utilizing the waterfall model as the development methodology, the application is developed using ASP.NET with C# and SQL Server to ensure robust performance and data management. The outcomes of this initiative demonstrate significant improvements in both time efficiency and resource allocation for handling student feedback within the Faculty of Information Technology at Tarumanagara University. By implementing this web-based solution, the faculty aims to foster a more effective and responsive feedback mechanism that enhances student engagement and satisfaction.

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