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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 8 Documents
 1 
Search results for , issue "Vol. 3 No. 3 (2024): June 2024" : 8 Documents clear
Application of Multimedia Learning for Pancasila and Citizenship Education in SD Inpres Waingapu 3 Mbana, Marlyn Rambu Day; Hariadi, Fajar; Mira, Trisari Dewi Novyanti B
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.532

Abstract

PPKn is an essential subject in elementary schools to instill Pancasila values and national identity. However, the results of the End-of-Semester Assessment (PAS) at SD Inpres Waingapu 3 consistently show low PPKn scores. To address this issue, this study developed a multimedia learning application for PPKn. This application is designed to enhance student understanding of PPKn material, particularly related to Pancasila values. The SDLC (Software Development Life Cycle) Waterfall method was used in the application's development. The application's effectiveness was tested through pre-test and post-test, showing a significant increase in the average score of 79.5%. The application's usability was also tested using the System Usability Scale (SUS), with an average score of 85 and a category of "Excellent". These results indicate that the PPKn multimedia learning application is effective and ready for use in elementary schools. hopefully this application can help improve the quality of PPKn learning and instill Pancasila values more strongly in students.
Forward Chaining Method in Expert System for Diagnosing Pests and Plant Diseases: A Systematic Literature Review Goda, Karina Dhena; Bay, Jenny Ronawati
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.535

Abstract

Pest and disease attacks on plants are very detrimental factors for farmers. Lack of knowledge leads to a difficult diagnosis of attacks and slow control. The technology that can help farmers in diagnosing plant pests and diseases is the expert system. One of the most widely used algorithms is forward chaining. Although there have been many used further research is needed to determine the effectiveness of this method. This research wants to find out more advantages, types of platforms used, and benefits of expert systems with forward chaining algorithms. This study uses a systematic method literature review (SLR) to collect, assess, and analyze data systematically from various scientific articles. The results of the study show that the use of forward chaining has advantages and benefits for developers and farmers.
Implementation of the Simple Additive Weighting Method in Determining Promotional Locations for Prospective New Student Admissions in Colleges Kurniawijaya, Putu Andhika; Karsana, I Wayan Widi
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.537

Abstract

Universities are currently competing in the selection of prospective students. By attracting high school graduates and others to continue their education to a higher level of education, universities promote high schools and vocational schools in the surrounding area. Every year, universities actively conduct promotional activities to gain the capacity that has been targeted by university leaders. One of the obstacles faced by universities in achieving the promotion target is the number of high schools and vocational schools spread across all provinces in Indonesia. The promotion section in determining the target area of promotion is requested by university leaders to be right on target because the budget of each university is limited. Determining the right promotion target can help universities strategize and use the budget appropriately and efficiently. The Simple Additive Weighting (SAW) method was chosen because it has an easy-to-understand concept. The criteria used in this study are: 1) the number of private universities in the district; 2) the number of high schools and vocational schools in the district; 3) the number of students in the district; and 4) the distance of private universities from the district.
Prediction of the Number of New Student UnregistrationBased on Mamdani Aries, Aries Setiawan; Wahid, Achmad Wahid Kurniawan; Retno, Retno Astuti Setijaningsih; Ida, Ida Farida; Budi, Budi Widjajanto; Jaka, Jaka Prasetya; Andi, Andi Hallang Lewa; Maria, Maria Safitri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.554

Abstract

One of the annual routine events carried out by a private university is the admission of new students (PMB). From a number of prospective students who register, there are usually a number of students who unregister or cancel registration. Several factors for unregistration of new students are (1) acceptance of state universities, the interest of prospective students to study at state universities is still high, (2) there are doubts about the study program chosen by students, (3) Inadequate ability to pay. Some of the above factors must be taken seriously so that there is no decrease in the number of registrations. The mamdani method is one of the calculation methods that can be used to predict the number of new student registrations, with 4 main stages, namely creating fuzzy sets, implementing implication functions, applying rules and regulations, and affirming. Prediction of unregistration using the Mamdani method will make it easier for academics, in this case the academic bureau, to find solutions to reduce the number of unregistration itself.
Design of a Web-Based Information System for Incoming and Outgoing Mail Archiving Using the Waterfall Method in Kambata Tana Village East Sumba Turu NdapaOtu, Nelson; Alfa R. L. Lede, Pingky
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.570

Abstract

Surat merupakan salah satu media komunikasi yang sangat penting dalam lembaga, perusahaan, atau bentuk organisasi lainnya, yang digunakan untuk berkomunikasi dengan pihak eksternal maupun internal. Segala sesuatu yang berhubungan dengan kegiatan organisasi selalu dituangkan dalam bentuk surat. Kantor Desa Kambata Tana merupakan lembaga pemerintahan yang bertugas untuk menegakkan kewibawaan pemerintahan. Dalam menjalankan tugasnya, kantor tersebut banyak terlibat dalam bidang komunikasi. Saat ini terdapat beberapa kendala dalam penyampaian surat, misalnya tidak semua surat terarsipkan dengan baik dan sering hilang, yang perlu ditindaklanjuti oleh pihak yang bertanggung jawab. Tujuan dari penelitian ini adalah untuk merancang dan mengembangkan sistem informasi pengarsipan surat masuk dan keluar pada Kantor Desa Kambata Tana, sehingga memudahkan aparat desa dalam mengolah dan mengarsipkan data surat masuk dan keluar sehingga surat yang dibutuhkan dapat ditemukan dengan lebih cepat dan mendukung kelancaran kegiatan aparat desa. Metode penelitian yang digunakan adalah metode waterfall dengan langkah-langkah pengembangan sebagai berikut: pengumpulan data, analisis, pengembangan sistem informasi, dan pengujian.
Website-Based Academic Application Design at Rumah Gemilang Indonesia Depok Safudin, Mahmud; Eko Yulianto
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.571

Abstract

Rumah Gemilang Indonesia is an empowerment program unit and training center under the Al-Azhar National Amil Zakat Institute Program directorate. The current collection of academic data is felt to be less effective because it is still done manually. One of the superior features planned is an online report card system that allows academic staff and students to access the academic data needed for their respective needs. The method of collecting data in the preparation of this thesis is the method of observation, interviews and literature study. A web development method developed using the Code Igniter framework whose programming language is PHP based, Code Igniter applies the MVC (Model, View, Controller) concept which makes it easier for developers to design a website. By developing this academic application, it can make it easier for academic staff to manage academic data and student report card scores online, which will be very effective and efficient in terms of time and students can immediately see the results of their report card scores online by accessing This academic application is through a website that is opened using a browser.
Analysis of Machine Learning Algorithms for Early Detection of Alzheimer’s Disease: A Comparative Study Deni Gunawan; Robi Aziz Zuama; Muhamad Abdul Ghani
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.579

Abstract

This study aims to analyze and compare the performance of various machine learning algorithms in predicting Alzheimer's disease based on patient clinical data. The algorithms tested include Decision Tree, Random Forest, K-Nearest Neighbors (KNN), and Logistic Regression. The dataset used in this research consists of clinical data from patients, encompassing various health parameters. The results indicate that the Decision Tree and Random Forest algorithms provide the best performance, with an overall accuracy of 93%. Random Forest performs slightly better in recall for class 0 but slightly worse in recall for class 1 compared to Decision Tree. Logistic Regression also shows good performance with an overall accuracy of 83%, while K-Nearest Neighbors has the lowest performance with an overall accuracy of 72%. This research offers insights into the effectiveness of various machine learning algorithms in detecting Alzheimer's disease and underscores the importance of selecting the appropriate model based on data characteristics and application needs. For future research, it is recommended to further optimize the model hyperparameters, increase the dataset size, add new relevant features, and combine several models using ensemble learning techniques. External validation and the development of more interpretable models are also crucial to build trust in the use of machine learning in the healthcare field.
MOORA Method Analysis For Decision Support System Determining the Best Subsidized Housing in Tanjung Morawa Marpaung, Preddy; Suci Amalia Sari; Fadya Larasati; Pasaribu, Sutrisno Arianto
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 3 (2024): June 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i3.702

Abstract

Subsidized housing is a government program as an alternative for low-income communities so that the primary needs of the community such as housing are met, especially for people who are already married. One of the areas where subsidized housing is located is the Tanjung Morawa area, Deli Serdang, North Sumatra. However, the problem for the community or employees who want to find a residence to live in the Tanjung Merowa area is the difficulty in determining a subsidized house that suits their wishes, such as comfort, housing price, house model, strategic location. The factor that makes it difficult for people to determine a residential house is because there is no knowledge or information about which subsidized house is the best according to the criteria to be occupied. Therefore, it is necessary to apply a method to analyze to determine the best subsidized house, the Objective Optimization on the basis of Ratio Analysis Simple (MOORA) method is applied to analyze the decision support system to determine the best subsidized house in Tanjung Morawa, where the MOORA method is able to produce the best subsidized house based on the highest value or ranking, where the highest value is ranking 1 alternative 6, Mulia Residence housing.

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