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All Journal JOURNAL OF COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS) JoDENS: Journal of Digital Ecosystem for Natural Sustainability
Steffany
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Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Socialization of the Visual Meaning of Basiba as a Cultural Identity Minangkabau to the Younger Generation through Digital Media: Sosialisasi Makna Visual Basiba sebagai Identitas Budaya Minangkabau kepada Generasi Muda melalui Media Digital Sayuti, Muhammad; Melisa Suardi; Steffany; Okta Andrica Putra; Harkamsyah Andrianof
Journal of Community Service and Application of Science Vol. 4 No. 1 (2025): COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS)
Publisher : KPN Kopertis X

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62769/8arthg26

Abstract

Basiba is an important element in traditional Minangkabau women's clothing, possessing profound philosophical value and reflecting local cultural identity. However, amidst globalization and the dominance of popular culture, the younger generation is beginning to lose touch with traditional cultural symbols, including Basiba. This community service project aims to disseminate the visual meaning of Basiba as a Minangkabau cultural identity to the younger generation through a digital media-based visual communication design approach. This topic was chosen based on the urgency of preserving local cultural values in a format relevant to media developments and the information consumption patterns of today's young generation. Partners in this activity are student and university students in Padang City who have a Minangkabau background but have minimal knowledge about the philosophy of traditional clothing. The community service method includes observation, focus group discussions (FGDs), creation of digital visual content (such as infographics, educational videos, and social media campaigns), and evaluation through questionnaire before and after the activity. The results showed an increased understanding and appreciation of the visual meaning of Basiba, as well as an increased interest in relearning other local cultural symbols. Digital media has proven effective in bridging cross-generational communication and rebuilding a lost cultural identity. This activity underscores the importance of visual strategies and digital technology in supporting the sustainable preservation of Minangkabau culture among the younger generation.
Penerapan Metode Radial Basis Function (RBF) dalam Mengklasifikasikan Penyakit Demam Berdarah Steffany; Purnajaya , Akhmad Rezki; Jelita, Rika; Tesvara, Eva; Nestelrody, Milson; Irwansyah , Joni
Journal of Digital Ecosystem for Natural Sustainability Vol 3 No 1 (2023): Juli 2023
Publisher : Fakultas Komputer - Universitas Universal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63643/jodens.v3i1.133

Abstract

Dengue fever is an arbovirus disease caused by dengue virus infection through the bite of the Aedes mosquito, Aedes aegypti. Signs or symptoms of dengue usually resemble ordinary viral infections, but can become more severe and cause other symptoms that can paralyze the activities of the patient who suffers from it. The initial symptoms of someone who is infected with the dengue virus will experience a fever within 4–6 days after being infected. Therefore, early diagnosis is needed whether a person is infected or not with dengue fever. Because if someone is late getting treatment by medical personnel, then this can lead to death. Prevention can be done by making the right predictions. Dengue fever disease prediction research is needed to assist medical personnel in making a diagnosis. To get a good level of accuracy, research collected data and used the Radial Basis Function (RBF) approach method. The results of the RBF prediction evaluation obtained are that the RBF model gets 100% accuracy, 100% sensitivity, 100% specificity, and 100% AUC value.
Co-Authors Harkamsyah Andrianof Irwansyah , Joni Jelita, Rika Melisa Suardi Nestelrody, Milson Okta Andrica Putra Purnajaya , Akhmad Rezki Sayuti, Muhammad Tesvara, Eva