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Agents: Journal of Artificial Intelligence and Data Science
Published by Universitas Islam Negeri Alauddin Makassar
ISSN : 27469204     EISSN : 27469190     DOI : https://doi.org/10.24252/jagti.v4i1.74
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
The AGENTS published the original manuscripts from researchers, practitioners, and students in the various topics of Artificial Intelligence and Data Science including but not limited to fuzzy logic, genetic algorithm, evolutionary computation, neural network, hybrid systems, adaptation and learning systems, biologically inspired evolutionary system, system life science, distributed intelligence systems, network systems, human interface, machine learning, and knowledge discovery.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 40 Documents
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PERBANDINGAN ANALISIS SENTIMEN ALGORITMA SUPPORT VECTOR MACHINE DAN NAÏVE BAYES TERHADAP TANGGAPAN PUBLIK TENTANG PEMBELAJARAN ONLINE DI MASA PANDEMI COVID-19 Yulia Ardana; Ridwan A. Kambau; Mustikasari
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 1 (2023): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (572.173 KB) | DOI: 10.24252/jagti.v3i1.46

Abstract

At the beginning of 2020, COVID-19 began to spread throughout the world, including Indonesia. The government continues to look for ways to prevent the chain from spreading, one of which is by implementing online learning. The background of this research is to use twitter to find out the response and public sentiment about online learning during the covid-19 pandemic. The purpose of this research is to find out public opinion about the application of online learning and also to compare the performance level of support vector machine and naïve Bayes algorithms. In conducting this research, the type of research used is qualitative research in order to be able to understand well what kind of phenomena experienced by the research subjects. The best sentiment analysis results are obtained by comparing two classification algorithms, support vector machine and naïve Bayes. Testing based on k-fold cross validation aims to obtain accuracy, precision, and recall values. The best algorithm will produce the right output with a higher test score.
ANALISIS CLUSTERING UNTUK SEGMENTASI PENGGUNA KARTU KREDIT DENGAN MENGGUNAKAN ALGORITMA K-MEANS DAN PRINCIPAL COMPONENT ANALYSIS Muhammad Nur Akbar; Azizah Salsabila; Aldi Perdana Asri; Muhammad Syawir
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 1 (2023): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (832.897 KB) | DOI: 10.24252/jagti.v3i1.56

Abstract

Customer segmentation is a process used by companies to group customers based on common characteristics. The goal is to understand customer needs and preferences better so that companies can provide products and services that match customer needs. One way to segment customers is to use clustering algorithms, such as k-means. This algorithm groups data into adjacent clusters with randomly selected centroids. In the case of credit card customer segmentation, the k-means algorithm can be used to group customers based on characteristics such as number of transactions, amount of payments, and credit history. Thus, companies can better understand the needs and preferences of credit card customers and determine more effective marketing strategies. The advantages of the k-means algorithm and the clustering method are that the developed models can help companies determine more effective marketing strategies, easy-to-use algorithms with fast computation time and accurate results, and the PCA algorithm is also used to reduce dimensions and makes data visualization easier. Based on the test results and analysis of credit card customer data, the performance of the k-means algorithm is considered relatively good for segmentation with the number of clusters = 3 and the Davies Bouldin value = -0.778.
IMPLEMENTASI JARINGAN SARAF TIRUAN UNTUK MENENTUKAN KELAYAKAN MAHASISWA DALAM MENDAPATKAN PEKERJAAN Ayu Azhari Zainal; Azizah Salsabila Azizah Salsabila; Hastuti Hastuti; Darmatasia
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 1 (2023): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1233.462 KB) | DOI: 10.24252/jagti.v3i1.58

Abstract

Job recruitment selection is one of the processes carried out by agencies or companies to determine whether a person is eligible for a certain job position or not. The selection process is often carried out in a subjective manner so that it can be detrimental to companies or job applicants. In the process of determining a person's eligibility to be accepted or get a particular job, a company usually has set certain criteria. In addition, a company also often holds regular employee recruitment. This study aims to implement one of the machine learning algorithms, namely an Artificial Neural Network to build a model that can assist companies in predicting a person's eligibility for employment. The model is built with reference to certain criteria data that has been set by the company such as educational history, work experience, and capabilities. The best accuracy result of 91.18% is obtained from a model built using a learning rate parameter of 0.1 and the number of hidden layers is 10.
SISTEM MANEJEMEN DAN MONITORING BIMBINGAN TUGAS AKHIR BERBASIS WEB Salmi; Darmatasia
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 1 (2023): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (832.897 KB) | DOI: 10.24252/jagti.v3i1.59

Abstract

The process of supervising student final assignments experiences many obstacles that can hinder the process of completing the final assignment itself. In addition, lecturers also carry out other tri-dharma activities, namely research and community service which require lecturers to carry out activities outside the campus. Differences in activity and liveliness between lecturers and students can be one of the obstacles in the final assignment guidance process. The purpose of this research is to design a system that can manage and monitor processes as well as provide advice related to web-based graduation projects, to facilitate processes, suggestions and assurance of information at any time and the accuracy of work processes in improving student graduation performance, especially in the final project process. The results of the accuracy test conducted on respondents and the level of satisfaction of respondents on the feasibility of the system is 80%. Keywords: Management, Guidance, Monitoring, Final Project..   Keywords: Management, Guidance, Monitoring, thesis
SISTEM UJI KELAYAKAN PENERIMA BLT BPJS MENGGUNAKAN METODE KLASIFIKASI ALGORITMA NAIVE BAYES Anita Rusmana Lefya; Mustikasari Mustikasari
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 1 (2023): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1409.593 KB) | DOI: 10.24252/jagti.v3i1.63

Abstract

The large number of registrants who receive Cash Direct Assistance for the Social Security Administering Body (BLT BPJS) in the village of Tamatto, Ujung Loe sub-district, Bulukumba district, makes village staff as managers take a long time to get a decision in the form of whether or not someone is eligible to get assistance. A system of due diligence for beneficiaries of BLT BPJS assistance is needed that can assist village staff. The purpose of this study is to design a system to determine the results of the decisions of recipients who are eligible for BLT BPJS assistance. The type of research carried out is quantitative research with an experimental research approach, the method of data collection is observation. The method used is the nave Bayes algorithm classification method. The results of this study indicate that the eligibility test system for BLT BPJS assistance recipients using the nave Bayes algorithm classification method can help to convey information in the form of the eligibility of a BPJS BLT aid recipient with an accuracy of 83.689% results using as many as 1036 data samples.
Sistem Penunjang Keputusan Pemilihan Pekerjaan Menggunakan Metode Profile Matching Hamdan Arfandy; Erik Wijaya; Izmy Alwiah Musdar
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 2 (2023): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jagti.v3i2.64

Abstract

The aim of this research is to design a decision support system for job selection. Finding job is the primary goal for students after graduation. The problem that arises is that many alumni are unaware and still confused about which field of work to pursue. In this study, a web-based decision support system was developed with the intention of being accessible via desktop and mobile devices. The Profile Matching method is utilized to generate job recommendations for system users. The application development employed the Bootstrap framework to ensure a more organized web interface. System testing was conducted using the black box method with twenty-five test cases. The result of this research is the successful development of a decision support system for job recommendations, which has undergone the system testing process. The testing results indicate that the system functions properly according to the system specifications, and no calculation errors or ranking discrepancies were found in the decision outputs displayed by the system.
Penerapan Algoritma A* untuk Pencarian Rute Terpendek pada Aplikasi Game Shoot'em Up Hasniati; Syaiful Rahman; Suyono
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 2 (2023): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jagti.v3i2.65

Abstract

The purpose of this research is to implement A* algorithm for finding shortest path in a shooter game. To design the system, use case diagram will be used to explain the functional requirements of the system, and the activity diagram to describe the system workflow. While in the application development that can be used in a desktop with a Windows operating system, Unity will be used. The testing methods used in this study are the black box method to validate that the game can run as designed, beta testing and software quality testing to verify that the A* algorithm was implemented well. The results of this study are 1) According to the results of black box testing, it can be concluded that all the buttons and features on the application manage to work as designed; 2) According to the result of endurance testing that have been done, it can be concluded that A* is very accurate and can find the shortest path in a short time, and the time used for the pathfinding is very dependant on the node count.
Rancang Bangun Aplikasi Katalog Augmented Reality Design Setup Ruang Kerja Minimalis berbasis Android ST. Aminah Dinayati Ghani; Andi Alfian
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 2 (2023): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jagti.v3i2.66

Abstract

This research is motivated by the use of Augmented Reality on the catalog page which can help clients see visualizations of the Interior design of a minimalist workspace based on the desired Interior theme in 3-dimensional form. The problem that arises is how to build an application that can scan 3D objects on catalog pages along with interesting workspace concept information by utilizing Android-based devices. The purpose of this study is to design a catalog information media that can display the Interior design of a minimalist workspace by utilizing Augmented Reality features into Android-based devices. This application was created using the C# programming language and uses Unity 3D Engine, SketchUp, and Photoshop software. Functionally testing the software on catalog applications using the blackbox method. The applications resulting from this research can help clients see the theme of minimalist workspace design designed to attract clients' attention in visualizing into the form of 3D objects
Analisis Sentimen Komentar Pengguna Aplikasi Threads Pada Google Playstore Menggunakan Algoritma Multinominal Naive Bayes Classfier Muhammad Nur Akbar; Nirwana Samrin
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 2 (2023): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jagti.v3i2.67

Abstract

The advancement of technology, especially internet and social media technology, has enabled people across the country to connect and interact with each other. In this context, Instagram has become a popular platform for content creators to share their work. In an effort to compete with other platforms, Instagram launched an integrated app called Threads, which shares some features similar to Twitter. Threads allows users to share text-based posts and provides various other features. To enhance the quality of this application, developers need to review user comments. However, the influx of comments is substantial, making manual review inefficient. Therefore, an automated application is required to categorize comments and analyze user sentiment. By utilizing text mining techniques for sentiment analysis, developers can easily sort comments into positive and negative categories. Multinomial Naive Bayes was chosen as it's specifically designed for data with frequency occurrences, such as in text analysis. It is expected that this application can assist developers in improving the quality of the generated app. From the results of this study, an accuracy of 76% was achieved, which is  relatively good and offers potential for further development to attain better results.
Rancang Bangun Pendeteksi Formalin dan Boraks pada Makanan berbasis Internet of Things (IoT) RIDWANG RIDWANG; Abd gafur; Andi Muhammad Nurul Ilham; Adriani
AGENTS: Journal of Artificial Intelligence and Data Science Vol 3 No 2 (2023): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/jagti.v3i2.69

Abstract

Consumption of unsafe food can lead to foodborne illness, a significant threat to our health. The use of formalin and borax in food can cause degenerative diseases and other health problems. To address this issue, a new study has focused on developing an IoT-based food detection tool for formaldehyde and borax. With IoT integration, this device can provide real-time and portable information via LCD screens and Android smartphones. The advantage of this tool is that it can quickly and accurately detect formaldehyde and borax in food, helping to prevent the consumption of unsafe food. Through formalin testing on meatballs and food samples containing borax, using instant noodle and egg samples and the results obtained from the addition of 1-5 drops of borax, all of which were detected as dangerous. The application of this detection tool is expected to increase the awareness of food producers and the public about the importance of food safety. It can also help control food stocks in markets, thereby reducing the risk of formaldehyde and borax induced in food products. Overall, this IoT-based food detection tool is an essential tool for ensuring the safety and quality of our food supply

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