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Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Published by Yayasan Kita Menulis
ISSN : -     EISSN : 28084519     DOI : https://doi.org/10.53842/jaiea.v1i1
Core Subject : Science, Engineering,
Automotive Engineering Computer Science & IT Control & Systems Engineering
The Journal of Artificial Intelligence and Engineering Applications (JAIEA) is a peer-reviewed journal. The JAIEA welcomes papers on broad aspects of Artificial Intelligence and Engineering which is an always hot topic to study, but not limited to, cognition and AI applications, engineering applications, mechatronic engineering, medical engineering, chemical engineering, civil engineering, industrial engineering, energy engineering, manufacturing engineering, mechanical engineering, applied sciences, AI and Human Sciences, AI and education, AI and robotics, automated reasoning and inference, case-based reasoning, computer vision, constraint processing, heuristic search, machine learning, multi-agent systems, and natural language processing. Publications in this journal produce reports that can solve problems based on intelligence, which can be proven to be more effective.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 525 Documents
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Eye Disease Classification System Based on Fundus Images Using the InceptionV3 Architecture Annisa Aulia; Hermawan Syahputra; Yulita Molliq Rangkuti; Insan Taufik; Kana Saputra S
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2263

Abstract

This study aims to develop an automated eye disease classification system based on retinal fundus images using the InceptionV3 deep learning architecture. The dataset consists of four classes: cataract, diabetic retinopathy, glaucoma, and normal, collected from public sources and clinical data. The proposed method applies several preprocessing techniques, including background segmentation, data augmentation, data normalization, and an 80:20 data split to improve model performance and generalization. Transfer learning is implemented by utilizing pretrained ImageNet weights and modifying the final layers to suit the classification task. The model is trained using the Adam optimizer with a learning rate of 0.001 and categorical cross-entropy loss function. Evaluation results show that the model achieves an accuracy of 96%, with average precision, recall, and F1-score values of 0.97, 0.96, and 0.97, respectively. The confusion matrix analysis indicates that most predictions are correctly classified, demonstrating strong performance across all classes. Furthermore, the model is successfully integrated into a web-based system that enables users to upload fundus images and obtain classification results automatically. These findings indicate that the proposed system can effectively assist in early detection of eye diseases and support clinical decision-making.
UI/UX Design of an Incoming and Outgoing Mail Information System using the Design Thinking Method Nurhayati; Zulfi Karman; Manja Purnasari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2264

Abstract

Kantor Inspektorat Kota Jambi saat ini mengelola surat masuk dan keluar secara manual menggunakan buku catatan, yang menyebabkan risiko kehilangan dokumen dan inefisiensi dalam pengambilan data. Penelitian ini bertujuan untuk mendesain Antarmuka Pengguna (UI) dan Pengalaman Pengguna (UX) untuk Sistem Informasi Surat Masuk dan Keluar (SIMAK) yang ramah pengguna untuk meminimalkan kendala operasional tersebut. Metode yang digunakan adalah Design Thinking , yang terdiri dari lima tahapan: empati, definisi, ide, prototipe, dan pengujian. Hasil penelitian ini adalah prototipe aplikasi berbasis web yang dirancang menggunakan Figma, yang menampilkan alat manajemen untuk surat masuk, surat keluar, disposisi, dan laporan. Pengujian yang dilakukan menggunakan metode System Usability Scale (SUS) dengan 10 responden menghasilkan skor rata-rata 89,75 . Skor ini menempatkan desain aplikasi dalam kategori " Diterima " dengan peringkat " Baik ", yang menunjukkan bahwa sistem mudah dipahami dan secara efektif memenuhi kebutuhan pengguna.
Analysis of Mathematics Percentage Calculation Strategies Quickly and Accurately Based on a Literature Review Adi Sinaga; Dinda Alexa Nabila Utomo; Dwi Octa Marcellita Girsang
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2265

Abstract

Percentages are one of the important concepts in mathematics that are widely used in various contexts of daily life such as economics, commerce, and decision-making. However, various studies show that the concept of percentage is still a material that is quite difficult for students and prospective mathematics teachers to understand. These difficulties are generally related to the understanding of the basic concept of percentage, the use of the percent symbol (%), and the ability to relate the percentage value to the reference value in a problem. This study aims to analyze various percentage calculation strategies that can be carried out quickly and accurately based on the results of previous research. The method used in this study is a literature study by reviewing various scientific articles from SINTA-accredited national journals and international journals that are relevant to the topic of percentages in mathematics learning. Data is collected through documentation techniques by examining and analyzing research findings related to the percentage calculation strategy. The results of the study show that the use of mental calculation strategies, understanding the basic concept of percentages, and the use of visual models can help improve students' ability to calculate percentages more effectively and efficiently. Therefore, the right calculation strategy is essential to support the understanding of the concept of percentages in mathematics learning.
Sentiment Analysis of Film Audience for IPAR ADALAH MAUT Using Support Vector Machine Surya Agung Agan Saputra; Siti Mujilahwati; Azza Abidatin Bettaliyah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2266

Abstract

This study aims to analyze user sentiment on social media X (formerly Twitter) toward the film Ipar Adalah Maut using the Support Vector Machine (SVM) method. The data were collected through a crawling process using the snscrape library, focusing on tweets containing keywords related to the film title. The preprocessing stages included data cleaning, case folding, tokenization, stopword removal, and stemming, while feature extraction was performed using Term Frequency Inverse Document Frequency (TF-IDF). Sentiment was classified into two categories, namely positive and negative, using the SVM algorithm. The results showed that the model achieved 100% accuracy on the training data and 82% accuracy on the testing data, indicating good generalization performance, although there is a potential risk of overfitting due to the gap between training and testing results. These findings demonstrate the effectiveness of SVM in analyzing sentiment related to film discussions on social media and provide a basis for future research by incorporating larger and more balanced datasets.
Flood Prediction for the Wampu River Basin Using the Simple Additive Weighting Method:A Case Study of the Wampu River in Bahorok Miftahul Janna; Said Iskandar; Arnita; Zulfahmi Indra; Susiana
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2268

Abstract

Flood is one of the natural disasters that frequently occurs in the Wampu Watershed (DAS Wampu), especially in Bahorok District. Flood risk is influenced by several factors such as rainfall, slope gradient, land use changes, and river depth. The problem in this study is the absence of a decision support system that can objectively determine flood risk levels. This study aims to determine the criteria and weights of flood risk, apply the Simple Additive Weighting (SAW) method, and analyze the accuracy level of the SAW method in determining flood risk. The method used in this research is the Simple Additive Weighting (SAW) method through several stages including criteria weighting, decision matrix construction, data normalization, preference value calculation, and alternative ranking. The research data consists of 18 villages with four criteria: rainfall, slope gradient, land use change, and river depth. The results show the classification of flood risk levels into high, medium, and low categories based on the obtained preference values. Villages with the highest preference values indicate a higher level of flood vulnerability compared to other villages. The model evaluation results indicate that the SAW method has an accuracy level of approximately 90% in determining flood risk classification. Based on these results, it can be concluded that the SAW method can be used as a decision support system to determine flood risk levels and provide recommendations for priority flood mitigation areas in Bahorok District.
UI/UX Design of an Android-Based Sales Application at Naureen Shop using the User-Centered Design Method Yessi Hartiwi; Nurhayati; Manja Purnasari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2277

Abstract

The development of digital technology has shifted consumer behavior to prioritize convenience and efficiency through online shopping. Naureen Shop, a women's clothing business, currently faces operational constraints due to manual sales, promotion, and data recording processes, resulting in sub-optimal service. This study aims to design the User Interface (UI) and User Experience (UX) of an Android-based sales application for Naureen Shop to enhance business effectiveness. The method employed is User Centered Design (UCD), a design approach focusing on user needs and characteristics through stages of identifying the context of use, specifying user requirements, creating design solutions using Figma, and evaluation. The design testing results using the System Usability Scale (SUS) method with 15 respondents yielded an average score of 77.0. This score indicates that the application design falls into the "Acceptable" category with a "Good" Adjective Rating. Consequently, the resulting design solution fulfills functional aspects and provides a satisfying user experience to support transaction processes at Naureen Shop
Application of the Tsukamoto Fuzzy Inference System Method for Rainfall Prediction in the Adolina Area Aditia Sanjaya
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2281

Abstract

Rainfall is one of the key elements in the climate system that significantly affects various sectors, such as agriculture, spatial planning, and disaster mitigation. Adolina, a region with tropical weather characteristics and highly fluctuating rainfall, requires an accurate prediction system to support informed decision-making. This study applies the Fuzzy Inference System (FIS) Tsukamoto method to predict rainfall based on input variables such as air temperature, humidity, and wind speed. The Tsukamoto method is chosen for its capability to handle uncertainty and produce crisp output values through inference and defuzzification processes based on a set of fuzzy rules. The results show that the Tsukamoto FIS provides reasonably accurate and consistent rainfall predictions with a low error rate. Therefore, this approach can serve as an effective alternative in weather decision-support systems for the Adolina area.
Implementation of Simple Queue and Content Filtering for Bandwidth Management on WLAN and LAN Networks Zura Permata
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2284

Abstract

SMK Negeri 1 Sungai Raya is a vocational high school located on Sultan Agung Street, Kuala Dua, Sungai Raya District, Kubu Raya Regency, West Kalimantan, which offers programs such as Visual Communication Design (DKV) and Broadcasting that utilize the internet to support learning activities including completing assignments, accessing educational resources, and submitting schoolwork; however, problems frequently occur in the laboratory network such as buffering, network downtime, and bandwidth congestion due to simultaneous usage, therefore bandwidth management using the simple queue method was implemented along with content filtering to block access to social media and online gaming websites in order to prevent disruptions to the learning process, and the results showed improvements in network performance where on the LAN network throughput decreased by 0.5735%, packet loss decreased by 0.0969%, delay decreased by 0.5942%, and jitter decreased by 0.9182%, indicating better stability and efficiency, while the WLAN network in the laboratory was also successfully installed, providing improved connectivity and supporting a more effective and focused learning environment.
Design and Construction of a Village Tourism Monitoring and Evaluation System Web Based Alfian Maulana; Deffa Danendra; M. Mustakim
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2289

Abstract

Development of village tourism in the Special Region of Yogyakarta requires structured and sustainable management, particularly in monitoring and evaluation as a basis for stakeholder decision-making. Current challenges include unintegrated tourism village data, manual evaluation processes, and limited public access to tourism information and services. This study aims to design and develop a web-based monitoring and evaluation system that integrates registration, data management, monitoring, scoring, and information presentation in a centralized platform. The system is developed using the Extreme Programming method, which includes planning, design, coding, and testing stages, with functional testing conducted through Black Box Testing. The technologies used include React JS for the interface, Express JS for the backend, Supabase as the database, and Google Cloud Storage for data storage. The results indicate that all main system features function according to requirements, supporting more effective monitoring and evaluation processes, improving data accuracy, and enhancing accessibility of information for both the public and local government. Furthermore, this system has the potential to serve as a foundation for regional tourism data integration and to support sustainable tourism village development policies, while also contributing practically to improving integrated digital public information services at the national level.
Chinese Script Handwriting Pattern Introduction Application Design with Algorithm CNN-SVM Jacqueline Kwanori; Huliman; Devi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2290

Abstract

The Chinese script has a high level of visual complexity because each character consists of thousands of intricate strokes. This is a big challenge for second-language learners, especially in recognizing the various variations of human handwriting. This study aims to design an accurate and efficient application for the recognition of Chinese handwriting patterns based on Android using a hybrid model of Convolutional Neural Network (CNN) and Support Vector Machine (SVM). In this system, the CNN works like a human eye that distinguishes the details of the shape of an image, while the SVM serves as the brain that decides what characters are being written. The data used in the training process included 7,330 Chinese characters pulled from the Kaggle platform. The results of the study show that the application was successfully designed and able to display character shapes, how to read (pinyin), and the meaning of words offline without the need for an internet connection. Based on testing the Black Box method, all of the app's features are proven to work validly. The study concluded that the use of the CNN-SVM hybrid model was highly effective in recognizing diverse handwriting variations, although the degree of accuracy remained dependent on the clarity of the quality of the images taken by the user.

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