Judul: Visualisasi K-Means clustering pada data potensi pertanian desa di Bogor  menggunakan MapServer
Abstrak: Badan Pusat Statistik (BPS) melakukan survei potensi desa yang menghasilkan data potensi/keadaan meliputi keadaan sosial, ekonomi, penggunaan lahan, sarana dan prasarana sampai level desa/kelurahan. Penelitian perlu dilakukan untuk menganalisis data potensi desa khususnya yang berhubungan dengan pertanian. Salah satunya dengan mengaplikasikan teknik data mining agar diperoleh suatu informasi atau pengetahuan sebagai penunjang pengambilan keputusan untuk pembangunan sektor pertanian. Penelitian ini menggunakan salah satu teknik data mining yaitu teknik clustering dengan menggunakan algoritme K-Means dan hasil clustering divisualisasikan dalam bentuk sistem informasi geografis berbasis web. Data yang digunakan dalam penelitian ini adalah data potensi desa Jawa Barat tahun 2006 khususnya daerah Bogor
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Judul: Sistem Informasi Geografis Berbasis Web untuk Produksi Kedelai di Indonesia Menggunakan K-Means Clustering
Abstrak: Information concerning areas that are potential for soybean production is not provided in an interactive information system that can be easily accessed by public. Nowadays, information about soybean production in all districts in Indonesia is displayed in the tabular form in the website http://aplikasi.deptan.go.id/bdsp. For that, in this study, a web-based geographic information system (GIS) was developed to manage and visualize soybean production in all districts in Indonesia. K-means clustering was performed to group data on production, productivity and harvested areas of soybean to make the coloring process become easier in GIS. The best clustering was obtained with 4 clusters and the sum square error (SSE) were 2.07, 1.53, and 0.0037 for data on production, productivity, and harvested areas of soybean, respectively. The GIS was developed using OpenGeo Suite 3.0 as the geospatial tool for managing and providing information about soybean production in Indonesia in forms of maps, tables, and graphs based on the results of k-means clustering.
Keyword: soybean production, k-means, clustering, geographic information system

Judul: Durability of Specific Immunoglobulin (Ig) Y Againts Influenza and Covid-19 in Sunscreen
Abstrak: The benefit of specific immunoglobulin Y (Ig Y) as an active ingredient in personal care products such as sunscreen has not been properly studied. Our study aims to evaluate the reliability of specific IgY against influenza and the COVID-19 virus in a sample sunscreen product. Specific IgY influenza and COVID-19 viruses were inserted in the sample sunscreen at two concentrations of 0.1% and 0.25%. Three treatments were observed: control (C) sunscreen without IgY, treatment 1 (T1) sunscreen with 0.1% IgY, and treatment 2 (T2) sunscreen with 0.25% IgY. Organoleptic observations were carried out to monitor changes in aroma, color, and texture, and sunscreen sampling was done every week for 6 weeks. The durability of IgY was evaluated using an enzyme-linked immunosorbent assay (ELISA) and a neutralization assay. Organoleptic observation from weeks 1 to 6 showed consistency in its aroma, color, and texture. Enzyme-linked immunosorbent assay and neutralization assay (NA) results of the T1 and T2 groups showed negative results except for sample T1 at week 5, which showed a positive result in the Influenza A ELISA. Based on the results, it seems that IgY concentrations of 0.1% or 0.25% were not optimal. However, this negative result might be due to low concentration of the IgY and the presence of beeswax, which inhibits IgY and causes it to dissolve in distilled water, thus preventing it from being detected in the assay.
Keyword: Immunoglobulin Y, Sunscreen, Influenza, COVID-19, Biological Activity