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Contact Name
Mustikasari
Contact Email
mustikasari@uin-alauddin.ac.id
Phone
+6282350437597
Journal Mail Official
tin.agents@uin-alauddin.ac.id
Editorial Address
Prodi Teknik Informatika, Fakultas Sains dan Teknologi, UIN Alauddin Makassar, Jl. H. M. Yasin Limpo No.36 Samata, Gowa, Sulawesi Selatan, 92113
Location
Kab. gowa,
Sulawesi selatan
INDONESIA
Agents: Journal of Artificial Intelligence and Data Science
ISSN : 27469204     EISSN : 27469190     DOI : https://doi.org/10.24252/jagti.v4i1.74
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.
Articles 40 Documents
SISTEM CERDAS PEMELIHARAAN DAN DIAGNOSA PENYAKIT HEWAN TERNAK SAPI BERBASIS ANDROID Syahraeni; Muh.Sahib
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 1 (2022): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (796.366 KB) | DOI: 10.24252/jagti.v2i1.27

Abstract

The livestock industry's development is an integral part of agricultural sector growth and holds significant strategic importance in meeting the rising demand for animal feed due to Indonesia's increasing population. The motivation behind this research stems from the inadequate knowledge among numerous breeders when it comes to livestock maintenance. This knowledge gap leads many breeders to rely solely on their experience due to the unavailability of information or accessible knowledge resources. To address this issue, a qualitative research approach was employed, utilizing an experimental programming method following the waterfall model. Data sources included various books, journals, theses, e-books, websites, and data collection through observations and interviews with employees from the District Livestock and Animal Health Service in Sinjai, as well as the involved breeders. The study's outcome is the development of an Android-based Livestock Maintenance System Application. This application serves as a valuable resource for obtaining information related to livestock maintenance. Additionally, it offers a platform for determining appropriate treatments and diagnosing diseases during livestock care. Furthermore, this system streamlines information dissemination from the Department of Animal Husbandry and Animal Health, eliminating the need for constant field visits to stay updated on livestock rearing developments.
PENGEMBANGAN E-LIBRARY SMA NEGERI 10 BULUKUMBA Rahmat Alghasyiah; Hasrul Bakri; Abdul Wahid Yunus
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 1 (2022): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.314 KB) | DOI: 10.24252/jagti.v2i1.28

Abstract

This studyaims to determine the results of the e-library development of SMA Negeri 10Bulukumba and the results of testing the e-library of SMA Negeri 10 Bulukumbabased on the ISO/IEC 25010 testing standard. This study uses a prototypingdevelopment model, Codeigniter as a framework, built using the PHP programming language. and HTML with MySQL as the database. Data collection techniques using interviews, documentation, and questionnaires. System testing in this studyuses the ISO/IEC 25010 software quality standard focus on aspects of functional suitability, performance efficiency, usability, security, and portability. Based on theresults of testing the functional suitability aspect which was tested by the system expert by filling out a questionnaire containing 83 questions related to the functions designed in the developed e-library, it was concluded from the functionalsuitability aspect that it was acceptable. The results of the performance efficiencyaspect test have met the load time of fewer than 10 seconds. The test results from theusability aspect with 102 respondents and 20 questions obtained good categories. The results of the security aspect test area at the medium-security level. The resultsof the portability test were tested on 6 different devices and browsers, obtainedsuccessfulscoresfrom all devices and browsers.
RANCANG BANGUN WEBSITE DROPSHIP KOSMETIK MENGGUNAKAN TEKNIK RESTFUL API Rismawati. S; , Ridwan A. Kambau; Hariani
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 1 (2022): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (200.813 KB) | DOI: 10.24252/jagti.v2i1.29

Abstract

[COSMETIC DROPSHIP WEBSITE DESIGN USING RESTFUL API TECHNIQUE] Dropshipping is a solution for people who want to start an online business but have limited capital, drop shippers only need to market products from other parties without having to buy them first. One product that is in great demand by the public today is cosmetics which people are willing to spend a lot of money to look perfect, with a cosmetic dropship website can provide opportunities for dropshippers who want to develop their online business using their own name. The purpose of this research is to produce a web-based application for cosmetic dropship products that can assist dropshippers in marketing their product online. The type of research is qualitative research using a design and creation approach which includes website-based design and development . The design used is the waterfall. This system is tested using black-box testing. The results obtained based on questionnaires from 10 dropshipper respondents and 10 respondents to the website obtained an interpretation percentage of 84.6% of dropshipper respondents and 85.4% of buyer respondents. Thus, it can be concluded that this cosmetic dropship website can help and facilitate dropshippers and buyers in selling and buying cosmetic products online.  
APLIKASI SISTEM REGISTRASI AKUN OFFICE 365 ONLINE UPT. ICT CENTER UNM Muhammad Agung; Muhammad Mahdinul Bahar; Rusli Ismail; Baso Riadi Husda
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 1 (2022): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (197.721 KB) | DOI: 10.24252/jagti.v2i1.30

Abstract

The account registration system of Office 365 UNM. is a support system for the distribution of Office 365 accounts for students, lecturers, and UNM employees within the Makassar State University. This system is expected to make it easier for admins to validate the data of students, lecturers, and UNM employees who register for an Office 365 account. Microsoft Office 365 includes Office Online (Word, PowerPoint, Excel, and OneNote), unlimited OneDrive storage, SharePoint sites, and Yammer. This study aims to build a registration and administration system to get an Office 365 account. In addition, to see the efficiency and effectiveness of service management work provided by the university and the process of developing this information system using the waterfall development method, using DFD to document, specify and model system. Implemented using the PHP programming language with support for Jquery, Javascript and MYSQL on Codeigneter Freamwork and other supporting software. The results of this research are expected to produce an Office 365 account registration system. The implementation of this registration system, the distribution and validation process for Office 365 accounts will be right on target, effective and efficient. This application has very good quality with 86.51% to highest ideal score.
APLIKASI MARKETPLACE HASIL TANGKAP NELAYAN KABUPATEN GOWA BERBASIS ANDROID Nurma Fitria; Faisal 2
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 1 (2022): September - Februari
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (335.689 KB) | DOI: 10.24252/jagti.v2i1.33

Abstract

Marketing that is done traditionally faces problems due to the COVID-19 situation, people do not directly shop for fresh fish at fish auctions. An application was made to facilitate transactions between consumers and fishermen based on these problems. The purpose of this study is to design an Android-based marketplace for fishermen's catches to make it easier for fishermen and consumers to conduct online buying and selling transactions. This study uses quantitative research by collecting data through interviews, questionnaires, and literature studies. The system design is done by using Data Flow Diagrams, Use Case Diagrams, Class Diagrams, Activity Diagrams, and Sequence Diagrams. The interface is built using Android Studio and Firebase as the database. While testing the system using the BlackBox testing method and beta testing. The results of this study indicate that the Android-based marketplace application for fishermen's catches in Gowa Regency can help and make it easier for fishermen and consumers to make online fish buying and selling transactions. With test results from questionnaires for fishermen of 95.3% and consumers of 84.6% who concluded that the application helps sales and is easy to use.
Sentiment Analysis Terhadap Review Aplikasi Maxim di Google Play Store Menggunakan Support Vector Machine (SVM) Muhammad Nur Akbar; Nur Hasanahlmar'iyah Rusydi; M. Hasrul H.; Nurul Shaumi Ramadhanti; Erfiana
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 2 (2022): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1507.007 KB) | DOI: 10.24252/jagti.v2i2.39

Abstract

Before selecting and installing applications on the Google Play Store, users often read reviews of other users. This makes user review analysis very attractive for app owners to make future decisions. One of them is the Maxim application, a new online transportation application that provides different services from similar applications. This study aims to analyze user reviews of the maxim application on the Google Play Store using sentiment analysis. The research data is taken from the Google Play Store website, while the data taken is in the form of a review text. This user review analysis uses the Support Vector Machine (SVM) method producing an accuracy of 79%.
Deteksi Penyakit pada Tanaman Padi Menggunakan MobileNet Transfer Learning Berbasis Android Herwina; Ashabul Kahfi Ash Shiddiq; Theddy Dzikrullah Syahputra; Darmatasia
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 2 (2022): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1556.62 KB) | DOI: 10.24252/jagti.v2i2.41

Abstract

Rice is a staple food in several countries, including Indonesia. To produce quality rice, maintenance of rice plants is required from planting to harvest. One of the problems often experienced by farmers is the presence of diseases that attack rice plants. The limited knowledge of some farmers means that farmers do not understand the condition of their plants, resulting in delays in handling when the plants are attacked by disease. This research aims to build an application that can detect diseases in rice plants that attack rice leaves. The types of diseases that will be detected are Leaf Smut, Brown Spot, and Bacterial Leaf Blight. This research uses a transfer learning approach with the Convolutional Neural Network algorithm to detect diseases in rice leaves. The architecture used is MobileNetV1 with an accuracy of 94% and MobileNetV2 with an accuracy of 95%. The input image used is 224x224 pixels in size. The trained model is then integrated into an Android-based application. Test results on the Android application show that the model can detect diseases on rice leaves.
Implementasi Metode Perbandingan Eksponensial dalam Sistem Pendukung Keputusan Seleksi Mahasiswa Penerima Beasiswa Muammilul Khair; A. Muhammad Syafar; Darmatasia
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 2 (2022): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1988.125 KB) | DOI: 10.24252/jagti.v2i2.42

Abstract

Scholarship is one of the programs initiated by the institution that is awarded to a student based on academic achievement or other criteria that may include financial need. Scholarships are awarded selectively in accordance with the scholarships held. The most problem in scholarship program is the selection process to decide scholarship awardees. The conventional selection model in scholarship selection is commonly not transparent and misdirected. This research was conducted in UIN Alauddin Makassar which aims to develop a scholarship selection Decision Support System to facilitate the decision makers in selecting scholarship recipients. The method used in the decision-making process is the Exponential Comparison method. This method is a method with exponential calculation, the difference in value between criteria can be distinguished depending on the ability of the person who judges. The system that has been built is then tested by BlackBox testing. The results of the study show that all features of the system can function properly. This research is expected to facilitate decision makers in selecting scholarship recipients transparently and effectively.
Sistem Pengawasan Pelanggaran P2TL pada PT. PLN (Persero) Berbasis Website Erfina; Abdul Haq
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 2 (2022): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (454.411 KB) | DOI: 10.24252/jagti.v2i2.43

Abstract

P2TL monitoring system at PT. PLN (Persero) North Makassar Area against electricity theft there are several obstacles faced by the P2TL team, where many people commit fraud to gain profits so that technology for monitoring violations is needed to minimize the occurrence of electricity theft at PLN. The type of research used is descriptive qualitative by using data collection methods namely observation, interviews, and questionnaires. The programming language used is Hypertext Preprocessor (PHP) and MySQL as the database. The system design in this study uses Agile methods and black box testing. This research produces a Website-Based Electric Theft Violation Monitoring Application. Based on the results of the feasibility test of the system, the final results obtained an average of 87.19% of respondents strongly agree with the existence of the system.
Implementasi Data Mining untuk Memprediksi Kelulusan Mahasiswa Tepat Waktu Menggunakan Random Forest Zaskila Nurfadilla; Faisal
AGENTS: Journal of Artificial Intelligence and Data Science Vol 2 No 2 (2022): Maret - Agustus
Publisher : Prodi Teknik Informatika Universitas Islam Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (422 KB) | DOI: 10.24252/jagti.v2i2.45

Abstract

The level of accuracy of student graduation in tertiary institutions is one of the criteria for assessing campus accreditation. The more students who graduate on time, the better the college's performance will be. Students' graduation rates are difficult to predict early, resulting in delays in graduation. To reduce the rate of delay in graduating college for students, it is necessary to be educated seriously in order to graduate on time. One method of solving this problem is by predicting the accuracy of student graduation by using data mining or data mining methods. The purpose of this system is to make it easier for lecturers on campus to classify students who are classified as graduating on time using the Random Forest method. The results of the classification using the Random Forest Algorithm using 1,351 data, then the evaluation results with an accuracy value of 90.74% by dividing the training and testing data as much as 80:20 The system successfully displays data visualization to predict graduation on time by implementing data mining.

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