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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Outline Journal of Community Development
Amelia, Syahputri
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Humanities Computer Science & IT Economics, Econometrics & Finance Education Environmental Science Social Sciences

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Website Development and Logo Design Education in Serdang Village, Meranti Subdistrict, Asahan Regency Fitriani, Annisa; Amelia, Syahputri; Abdillah BB, M; Siregar, Raja Syahmuda; Tuahta, Alexander
Outline Journal of Community Development Vol. 3 No. 2: November 2025
Publisher : Outline Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61730/72dmt987

Abstract

This study aims to develop a village website and provide logo design education for the residents of Serdang Village, Meranti Subdistrict, Asahan Regency. The primary objective of this initiative is to create a digital platform that facilitates information dissemination, promotes local potential such as agricultural products and MSME (Micro, Small, and Medium Enterprises) products, and strengthens digital-based public services. Additionally, the study focuses on enhancing the creative skills of the community, particularly small business owners, through basic graphic design training and logo creation as a visual identity and product branding strategy. The methodology employed in this research is a participatory qualitative approach, combining observation, interviews, and training activities. The website development was conducted collaboratively with village officials to ensure alignment with local needs, while the logo design education was delivered through workshops that included practical sessions on design software usage and creative idea development. Data analysis was carried out descriptively to evaluate the effectiveness of the program. The results indicate that the developed village website functions effectively as both an information dissemination medium and a promotional tool for village potential. Meanwhile, the logo design education successfully enhanced participants’ knowledge and skills in understanding the importance of branding through visual design. Overall, this study demonstrates that digital literacy and creative education can empower village communities, improve the quality of public services, and strengthen the competitiveness of local products in the digital era.
ANALISIS TINGKAT KEPARAHAN COVID-19 DI SUATU NEGARA MENGGUNAKAN METODE K-MEDOID CLUSTERING Amelia, Syahputri; Yusri, Eldo; Irwansyah, Bambang; Andira, Ayu; Sukri, Muhammad; Yafi, Muhammad Fauzan; Affandi, Muhammad
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 9, No 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5787

Abstract

Abstract: This study aims to classify the severity of COVID-19 cases based on patient and region data using the K-Medoid Clustering method. COVID-19 has varying degrees of symptom severity, requiring cluster analysis to identify severity patterns to support decision-making in healthcare resource allocation and policy formulation. The data used included the number of positive cases, recovered cases, deaths, the average age of patients, and comorbidity levels. The results showed that the K-Medoid method was able to effectively cluster the data. In the raw dataset, the percentage of patients not infected with COVID-19 was 62.62%, while the percentage of infected patients was 37.38%. Based on sample characteristics, non-obese patients accounted for 74.54%, obese patients 25.46%, and patients with a combination of obesity and cardiovascular disease 0.57%. Keywords: Covid-19, Severity, K-Medoid Clustering, Data Mining Abstrak: Penelitian ini bertujuan untuk mengelompokkan tingkat keparahan kasus COVID-19 berdasarkan data pasien dan wilayah menggunakan metode K-Medoid Clustering. COVID-19 memiliki variasi tingkat keparahan gejala, sehingga diperlukan analisis klaster untuk mengidentifikasi pola keparahan yang mendukung pengambilan keputusan dalam alokasi sumber daya kesehatan dan perumusan kebijakan. Data yang digunakan meliputi jumlah kasus positif, kasus sembuh, kasus meninggal, usia rata-rata pasien, serta tingkat komorbiditas. Hasil penelitian menunjukkan bahwa metode K-Medoid mampu melakukan pengelompokan data secara efektif. Pada dataset mentah, persentase pasien tidak terjangkit COVID-19 sebesar 62,62%, sedangkan pasien terjangkit sebesar 37,38%. Berdasarkan karakteristik sampel, pasien non-obesitas memiliki persentase 74,54%, pasien obesitas 25,46%, dan pasien dengan kombinasi obesitas serta penyakit kardiovaskular sebesar 0,57%. Kata Kunci : Covid-19, Tingkat Keparahan, K-Medoid Clustering, Data Mining
Co-Authors Abdillah BB, M Affandi, Muhammad Annisa Fitriani, Annisa Ayu Andira Irwansyah, Bambang Muhammad Sukri Siregar, Raja Syahmuda Tuahta, Alexander Yafi, Muhammad Fauzan Yusri, Eldo