cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Puput Dani Prasetyo Adi
Contact Email
puput@ascee.org
Phone
+6281227103387
Journal Mail Official
puput@ascee.org
Editorial Address
Jl. Kemantren 3 RT.04 RW 13 Kelurahan Bandungrejosari Kecamatan Sukun Malang
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
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 20 Documents
 1   2 
Search results for , issue "Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November]" : 20 Documents clear
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.
Implementation of Haversine Algorithm in Web-Based Online Attendance Application Wijaya, Leon Fernando; 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.v4i4.836

Abstract

Attendance is an important aspect of the world of work. A manual attendance system is a conventional attendance recording method that is still widely used. However, with the rapid advancement of technology, digital attendance now allows recording attendance through software connected to the internet. PT Password Solusi Sistem, as an information technology solution provider and system integrator, already has an online attendance application, but its effectiveness is still limited, and feature customization is difficult because the application comes from an external service provider. This research aims to develop a web-based online attendance application with the implementation of the Haversine algorithm to calculate the distance between the user’s location and the office location through geolocation technology during attendance so that the results of this calculation are used to provide information on attendance whether it is done outside or within the office radius. In addition, this study also compared the results of distance calculations between the Haversine algorithm and the Google Geometry Library in 20 different locations, which resulted in a difference of 0.0113. GPS Geolocation testing, conducted using a smartphone, showed 100% accuracy, with all test locations being valid. The results showed that the online attendance application with the Haversine algorithm was successfully implemented, and the accuracy comparison between the Haversine algorithm and Google Geometry Library showed almost similar results.
Enhancing Tourist Experiences in Glodok Pancoran Through Virtual Tours Christina, Angelica; Tony, Tony; Handhayani, Teny
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.v4i4.837

Abstract

This research aims to develop a web-based tourist destination application for Glodok Pancoran, Jakarta, to improve tourist experience and promote local culture and culinary. The methods used in developing this application include database design, development using Visual Studio Code, React for the frontend, and Go (Golang) for the backend, as well as database management with MySQL. The app was tested using black box method and System Usability Scale (SUS) assessment to ensure functionality and user satisfaction. With an Agile approach, the app integrates Google Maps and Street View to provide virtual tours, which is a new innovation in promoting local tourism. The results showed a high level of user satisfaction with an average SUS score of 90.33, which was categorized as excellent. This study highlights the importance of virtual tours in tourism, especially for first-time visitors, and recommends further development based on user feedback to improve tourism and the local economy.
Revolutionizing B2B procurement: Digital transformation at PT Sadang Jaya Riady, Clive; 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.v4i4.840

Abstract

The rapid pace of digital transformation presents both challenges and opportunities for businesses globally, especially in the realm of Business-to-Business (B2B) order management. Many Indonesian companies continue to rely on outdated, manual processes, leading to inefficiencies and scalability issues. This study explores how PT Sadang Jaya, a food production company in the Indonesian market, tackled these challenges through the strategic implementation of a custom-built B2B order management system using Angular, Express.js,  PostgreSQL, and Agile methodology. PT Sadang Jaya, despite its strong market reputation, encountered difficulties in managing orders efficiently as the company grew and the number of distributors increased. The manual order management process, conducted through WhatsApp or phone calls, became increasingly inefficient and prone to errors, resulting in irregular order queues and increased risk of recording errors. To overcome these challenges, the company recognized the need for a B2B eCommerce system that could streamline transactions between PT Sadang Jaya and its distributors. This thesis aims to design and develop a web-based online ordering application that not only reduces recording errors but also accelerates the order fulfillment process and strengthens business relationships with distributors. The results of User Acceptance Testing (UAT) demonstrate the successful completion of all test cases without any blocking issues, comprehensively verifying the system's functionality, including order management and distributor interaction. The implementation of this system is anticipated to capitalize on the immense potential of B2B eCommerce, enabling PT Sadang Jaya to broaden its market reach and elevate distributor satisfaction through more integrated and responsive services.
Performance Comparison of the Support Vector Machine Algorithm with RBF Kernel and Random Forest in Classifying Tourism Images of Nusa Penida Salim, Bryan Othman
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.v4i4.846

Abstract

Indonesia holds vast tourism potential, including Nusa Penida, Bali, renowned for its natural beauty. However, the adoption of modern technology to support tourism promotion and management remains limited. This study aims to compare the performance of Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel and Random Forest algorithms in classifying images of three main tourist attractions in Nusa Penida: Angel’s Billabong, Broken Beach, and Kelingking Beach. The dataset consists of 450 images processed using the Histogram of Oriented Gradients (HOG) method for feature extraction. Two data split scenarios (80:20 and 70:30) were applied to evaluate the algorithms based on accuracy, precision, recall, and F1-score metrics. The experimental results revealed that SVM with RBF kernel outperformed Random Forest in all scenarios, achieving the best results in the 70% training and 30% testing data split with an accuracy of 0.967, precision of 0.969, recall of 0.967, and F1-score of 0.967. While Random Forest demonstrated stable performance, it remained inferior to SVM with RBF kernel. This study concludes that SVM with RBF kernel is superior for image classification tasks, offering opportunities for implementing artificial intelligence technologies to advance the tourism sector in Indonesia.
Monitoring leakage in water pipe installation using a water flow sensor Prima, Delta Ardy; Atthariq, Atthariq; Parenreng, Jumadi Mabe
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.v4i4.861

Abstract

The need for water for humans is the main thing and cannot be replaced with anything else. Water will always be needed every time for consumption and daily activities. Therefore, the need for water is always considered in the distribution process so that every community can meet its water needs. Especially residential areas where water needs are important. However, there are obstacles to pipe leaks that cause this water distribution to be hampered. The development of the Internet of Things is the main solution in terms of monitoring water flow and water pressure in pipes. This makes it easier for pipe repair parties to increase the effectiveness of their supervision of the condition of their housing pipes. Based on the results of trials and evaluations that have been carried out, it gives the conclusion that the existence of this system can help pipe repair parties in knowing the state of water flow in pipe installations in their residential areas. This system is also supported by using the calculation of physical formulas such as the Bernoulli equation and the principle of continuity where the formula P = 1/2ρV² has been used in the calculation of calibration on the water flow sensor and to test the validation of the results issued by the water flow sensor, the Absolute Relative Error calculation is also used where the formula used is Absolute Relative Error = | (estimated - actual) / actual | * 100. Through the calculation processes carried out, it can increase the chances of reading data that is more accurate than usual and the results will be maximized in detecting any anomalies that occur during monitoring. Therefore, the opportunity to implement a residential pipe monitoring system is a convincing thing to do in improving services that are more responsive to residents in the housing complex.

Page 2 of 2 | Total Record : 20

 1   2 

Filter by Year

2024 2024


Reset
Filter By Issues
All Issue Vol. 5 No. 2 (2025): Volume 5 Issue 2, 2025 [May] Vol. 5 No. 1 (2025): Volume 5 Issue 1, 2025 [February] Vol. 4 No. 4 (2024): Volume 4 Issue 4, 2024 [November] Vol. 4 No. 3 (2024): Volume 4 Issue 3, 2024 [August] Vol. 4 No. 2 (2024): Volume 4 Issue 2, 2024 [May] Vol. 4 No. 1 (2024): Volume 4 Issue 1, 2024 [February] Vol. 3 No. 4 (2023): Vol. 3 No. 4 (2023): Volume 3 Issue 4, 2023 [November] Vol. 3 No. 3 (2023): Vol. 3 No. 3 (2023): Volume 3 Issue 3, 2023 [August] Vol. 3 No. 1 (2023): Vol. 3 No.1 (2023): Volume 3 Issue 1, 2023 [February] Vol. 3 No. 2 (2023): Volume 3 Issue 2, 2023 [May] Vol. 2 No. 4 (2022): Vol. 2 No. 4 (2022): Volume 2 Issue 4, 2022 [November] Vol. 2 No. 3 (2022): Vol. 2 No. 3 (2022): Volume 2 Issue 3, 2022 [August] Vol. 2 No. 2 (2022): Volume 2, Issue 2, 2022 [May] Vol. 2 No. 1 (2022): Volume 2 Issue 1, 2022 [February] Vol. 1 No. 4 (2021): Volume 1 Issue 4, 2021 [November] Vol. 1 No. 3 (2021): Volume 1 Issue 3, 2021 [August] Vol. 1 No. 2 (2021): Volume 1, Issue 2, 2021 [May] Vol. 1 No. 1 (2021): Volume 1 Issue 1, 2021 [February] More Issue