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All Journal IKRA-ITH ABDIMAS Formosa Journal of Science and Technology (FJST) Jurnal Pengabdian Masyarakat Bestari (JPMB)
Jose Ryu Leonesta
Universitas Matana
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Education Industrial & Manufacturing Engineering Social Sciences

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Implementasi CMS untuk Website Yayasan Bina Berdaya Bangsa Simon Prananta Barus; Prya Artha Widjaya; Jose Ryu Leonesta; Veronica Yose Ardilla; Sabrina Yose Amelia
IKRA-ITH ABDIMAS Vol 6 No 2 (2023): IKRAITH-ABDIMAS Vol 6 No 2 Juli 2023
Publisher : Universitas Persada Indonesia YAI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37817/ikra-ithabdimas.v6i2.2419

Abstract

In community service (PKM) previously, the development of a content management system (CMS) hasbeen done for the website of the Bina Berdaya Bangsa Foundation (YBBB). The CMS that was built wasadapted to the needs of YBBB. At that time the development used a prototyping model, not yet at theimplementation phase. This is due to the time constraints of the previous PKM. Therefore, this PKM is a itscontinuation, with a focus on system implementation. In the testing phase, the CMS features are tested. In thesystem implementation phase, the activities consist of data migration, database and website installation tohosting, trial, manual writing, CMS demo, and handover process to YBBB. The Matana University PKMteam is ready to maintain the sustainability of the CMS for the YBBB website so as to improve YBBBservices.
Determining Mango Plant Types Using YOLOv4 Prya Artha Widjaja; Jose Ryu Leonesta
Formosa Journal of Science and Technology Vol. 1 No. 8 (2022): December 2022
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v1i8.2155

Abstract

Mango plants consist of many types. This study tries to use leaf imagery to determine the type of mango plant. In this study, one of the object recognition methods in Deep Learning was used, namely YOLO (You Only Look Once) version 4. The types of mango used were manalagi, apple, golek and sweet and fragrant. The study used 457 pieces of data for model training and yielded an accuracy of around 95 percent.
Web Training by Using HTML and CSS to Attract Interest in Learning Programming for High School Students Prya Artha Widjaja; Simon Prananta Barus; Ary Budi Warsito; Jose Ryu Leonesta; Sabrina Yose Amalia; Veronica Yose Ardilla; Nico Abel Laia
Jurnal Pengabdian Masyarakat Bestari Vol. 2 No. 6 (2023): June 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/jpmb.v2i6.4476

Abstract

In digital field, the need for programmers is increasing, but quality resources in the field of programming are still lacking. Many schools, in this case, high schools, have not taught programming in the school curriculum. This training is given to attract students' interest in learning programming. The chosen method is to teach how to make front-end views of web pages. This method was chosen because web programming is easier to learn and participants can see the results displayed live. From the activities that have been carried out, the participants were very enthusiastic about participating and asked for further training. It can be concluded that this training succeeded in attracting the interest of participants, namely high school students, to learn programming, specifically web programming.
Differentiate a Health and Sick of Mango Leaves Using YOLOv4 Prya Artha Widjaja; Jose Ryu Leonesta
Formosa Journal of Science and Technology Vol. 2 No. 7 (2023): July, 2023
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/fjst.v2i7.4792

Abstract

Healthy plants will provide good results for farmers. As in humans, plants can also be affected by diseases that can result in death or crop failure. This study uses the object recognition method, namely YOLO (You Only Look Once) version 4 to determine whether a plant is categorized as sick or healthy. The data used in this research is secondary data. The results obtained were in line with expectations, namely being able to distinguish between healthy and diseased leaves.
Co-Authors Ary Budi Warsito Barus, Simon Prananta Nico Abel Laia Prya Artha Widjaja Sabrina Yose Amalia Sabrina Yose Amelia Veronica Yose Ardilla