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Journal Of Artificial Intelligence And Software Engineering
Published by Politeknik Negeri Lhokseumawe
ISSN : 2797054X     EISSN : 2777001X     DOI : http://dx.doi.org/10.30811/jaise
Core Subject : Science,
Computer Science & IT
Artificial Intelligence Natural Language Processing Computer Vision Robotics and Navigation Systems Decision Support System Implementation of Algorithms Expert System Data Mining Enterprise Architecture Design & Management Software & Networking Engineering IoT
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 8 Documents
 1 
Search results for , issue "Vol 4, No 2 (2024)" : 8 Documents clear
Application of the Random Forest Method for UKT Classification at Politeknik Negeri Lhokseumawe Al Khaidar; Muhammad Arhami; Mustainul Abdi
Journal of Artificial Intelligence and Software Engineering Vol 4, No 2 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i2.6131

Abstract

Classification is the systematic grouping of objects, ideas, books, or other items into specific classes based on similar characteristics. One of its applications is in the grouping of tuition fees, which are fees paid each semester or academic year based on the student's economic ability. However, there are several issues, such as the placement of underprivileged students into fee groups that are still not appropriate and the limited accuracy of the grouping process due to it being done manually. To address these issues, a classification system was designed using the Random Forest method. Random Forest is a machine learning algorithm that combines multiple decision trees for more accurate predictions. Testing the Random Forest method using cross-validation shows an average accuracy of 95%. Evaluation with a confusion matrix shows an accuracy of 94%, with varying values of precision, recall, and f1-score for each group.
Implementation of Profile Matching Analysis Method for Decision-Making in Online Learning for Homeschooling Student Jikti Khairina; Nurdin Nurdin; Muhammad Nasir
Journal of Artificial Intelligence and Software Engineering Vol 4, No 2 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i2.6126

Abstract

In a homeschooling learning system, adjustment between learning methods and student characteristics is very important to achieve optimal learning outcomes. Online learning provides flexibility for homeschooled students, but determining the most appropriate learning method according to the student's profile is still a challenge. In the context of homeschooling, where an individual approach is needed, the application of the Profile Matching method in decision-making for an online learning system allows for the personalization of education according to student characteristics, where this method provides recommendations for the most appropriate learning methods based on student profiles, including learning styles, cognitive abilities, and learning preferences. By comparing the profile of students' competencies and learning styles against predetermined criteria, the system can provide recommendations for appropriate learning methods. The results of this study indicate that the Profile Matching Analysis method can improve learning effectiveness and facilitate personalization of the learning process.
Air Temperature and Humidity Monitoring System for Server Rooms and Data Centers Using the Fuzzy Tsukamoto Method with IoT JB, Salwa Nur; Huzaeni, Huzaeni; Salahuddin, Salahuddin
Journal of Artificial Intelligence and Software Engineering Vol 4, No 2 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i2.6132

Abstract

Lhokseumawe State Polytechnic has UPT Information and Communication Technology (ICT) Data Center that manages important infrastructure for the teaching and learning process. This study aims to design and build an IoT-based air temperature and humidity monitoring system, using Fuzzy Tsukamoto algorithms to handle highly variable sensor data. Blackbox testing showed that the system managed to provide real-time server room condition information and send notifications when conditions reached a certain limit. Turning the AC on and off and incandescent lamps also work well. Whitebox testing successfully ensures that Tsukamoto's Fuzzy algorithm is implemented correctly and that hardware integration runs without problems. The Blackbox test managed to achieve 100% da success on and the Whitebox only achieved 100% on both Tests.
Implementation of Cloud Computing in E-Gizi for Recording and Reporting Toddler Nutrition Status in Batuphat Timur Village via Mobile Applications Munanda, Allissa; Hidayat, Hari Toha; Safriadi, Safriadi
Journal of Artificial Intelligence and Software Engineering Vol 4, No 2 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i2.6127

Abstract

Based on existing data in 2022, Aceh still at the fifth highest level in indonesia for the stunting category. At this time, many posyandu still use books to record children’s growth development and this is very ineffective. Based on this fact, a mobile application is needed that can be used for recording and reporting child growth and development. The reseach aims to produce an application that is effective and can be implemented in the East Batuphat posyandu, so that it make easier for posyandu officiers to record and report child growth and development. This reseach used the blackbox testing method to detemine the level of user satisfaction with the feasibility of the application. The result of testing the feasibility of applications using blackbox testing are 95.8% user satisfaction and 4.2% user dissatisfactions and result based on child data obtained from the East Batuphat health center more than 80% of children are in good nutritional status.
A Web-Based Laptop Purchase Recommendation Model Using Natural Language Processing (NLP) on Marketplace Reviews Syahdana, Irham; Hidayat, Rahmad; Khadafi, M
Journal of Artificial Intelligence and Software Engineering Vol 4, No 2 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i2.6133

Abstract

This system will use the Natural Language Processing (NLP) method to analyze user reviews. In addition, the Naive Bayes classification algorithm will be used to provide recommendations based on the analysis. The methods used include collecting laptop user review data from the Shopee platform, Natural Language Processing (NLP) for text analysis, classification with the Naive Bayes algorithm, developing a recommendation system, and evaluating the system using relevant metrics. The results of the study show that this model achieves an accuracy of 0.86 with a precision of 0.93 for positive reviews and 0.69 for negative reviews. Of the total 42 reviews tested, the system provides a recall of 0.87 for positive reviews and 0.82 for negative reviews. The total reviews in the dataset consist of 96 positive reviews and 43 negative reviews. This study is expected to contribute to the development of review-based recommendation systems, so that users can make the right decisions.
Synchronous Multiplayer Shooting in the 2D Game "War Cops" Using Unity Engine Geubrina, Tiara; Husaini, Husaini; Mahlil, Mahlil
Journal of Artificial Intelligence and Software Engineering Vol 4, No 2 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i2.6128

Abstract

In this modern era, the digital game industry continues to grow rapidly with various innovations in game creation. One of the game development platforms that is often used is the Unity Engine. Currently, developed games are only played offline, and users must buy special devices. To overcome this problem, innovation is needed to allow players to play together without these restrictions. In this effort, Unity Engine 2D can be used with Photon Unity Network support for games over different networks. This study aims to determine the response speed of Photon. The results show that the ping test response from the photon obtained an average value of 201 ms.
Smart Infusion Digitalization Based on IoT, Long-Range Communication, and Cloud Ananta, Adam; Nasir, Muhammad; Erdiansyah, Umri
Journal of Artificial Intelligence and Software Engineering Vol 4, No 2 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i2.6135

Abstract

Currently, the monitoring of infusion fluids is performed by periodically checking each patient, regardless of whether there is an obstruction or not. To address this challenge, a system based on the Internet of Things (IoT), Long Range (LoRa) at a 2.4 GHz frequency, and Cloud technology, known as the digital smart infusion system, has been developed. This system aims to enhance the efficiency and safety of infusion fluid delivery, facilitate real-time monitoring by nurses, and provide accurate and up-to-date data. The testing results indicate that the implementation of the MQTT protocol in this system yields positive outcomes, with delay times varying between 42 ms (5 minutes), 84.3 ms (10 minutes), and 73.8 ms (15 minutes), along with very low packet loss rates of 0.03% at 5 minutes, 0.02% at 10 minutes, and 0.01% at 15 minutes. Additionally, the system's throughput remains stable, with values of 92.6 Kbps at 5 minutes, 83.8 Kbps at 10 minutes, and 86.2 Kbps at 15 minutes. In tests of LoRa without obstructions, packet loss percentages remain low up to a distance of 10 meters, with a value of 0%, but then increase to 68.29% at 25 meters. Tests with obstructions show a more drastic decline in signal quality, with packet loss reaching 6.98% at 5 meters and increasing to 70.97% at 25 meters.
Implementation of RFID-Based Attendance Integrated with Management Systems and Notifications via WhatsApp Salsabila, Salsabila; Anwar, Anwar; Syahputra, Guntur
Journal of Artificial Intelligence and Software Engineering Vol 4, No 2 (2024)
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v4i2.6130

Abstract

Currently, attendance recording faces challenges, especially with validation using Mac Addresses which is suboptimal due to the dynamic nature of device IP Addresses. To address this issue, the researcher proposes integrating the existing management system with RFID-based attendance. RFID technology enables tracking and identification using radio waves without direct contact, ensuring efficient and accurate attendance recording. The system will send attendance notifications to teachers via WhatsApp and store data in a database, facilitating monthly summaries and ensuring data security and availability for future reference. This research utilizes blackbox testing to evaluate system accuracy, achieving a 95% accuracy rate in RFID tag readings and successful RFID tag scanning processes. Network speed measurement using QoS shows favorable results, with a throughput of 77.4 Kbps, zero packet loss, an average delay of 1.919 ms, and jitter of 1.92 ms in tests involving 15 RFID tags

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