South Sumatera songket woven cloth is one of the cultural assets of South Sumatera Province which is usually used at weddings and other traditional ceremonies. One of the villages which is famous as a producer of songket cloth is a Penyandingan Village. The songket cloth industry in Penyandingan Village experienced a decline in turnover of up to 60% during the Covid-19 pandemic. This is supported by the lack of knowledge of society regarding marketing strategies and technology in marketing products. For this reason, Shopee market management training is needed for songket cloth craftsmen and the Penyandingan Village society through the Sriwijaya University Thematic Community Service team program so that the marketing of songket fabrics can reach a wide market and be able to compete with other products. The method used is the lecture method including data collection planning and implementation of activities. The research analysis uses descriptive analysis to provide a general description of the implementation of the Shopee marketplace training. After the training was carried out, Penyandingan Village society was able to understand the material and apply it directly using the Shopee application, and could be applied on a sustainable scale so that sales of songket cloth could increase. AbstrakKain tenun songket Sumatera Selatan merupakan salah satu aset budaya dari Provinsi Sumatera Selatan yang biasanya digunakan pada acara pernikahan dan upacara adat lainnya. Desa Penyandingan merupakan salah satu desa sebagai penghasil kain tenun songket di Sumatera Selatan. Selama masa pandemi Covid-19, industri kain tenun songket di Desa Penyandingan mengalami penurunan pemesanan sehingga kehilangan omzet sampai 60% dari biasanya. Hal ini didukung dengan minimnya pengetahuan masyarakat penyandingan mengenai strategi pemasaran dan teknologi dalam memasarkan produk. Untuk itu diperlukan pelatihan pengelolaan marketplace Shopee bagi pengrajin kain songket dan masyarakat Desa Penyandingan melalui program tim pengabdian KKN Tematik Universitas Sriwijaya. Kegiatan ini bertujuan memberikan pemahaman dan pengetahuan pemanfaatan marketplace
Diabetic Retinopathy is a effect of diabetes. It results abnormalities in the retinal blood vessels. The abnormalities can cause blurry vision and blindness. Automatic retinal blood vessels segmentation on retinal image can detect abnormalities in these blood vessels, actually resulting in faster and more accurate segmentation results. The paper proposed an automatic blood vessel segmentation method that combined Otsu Thresholding with image enhancement techniques. In image enhancement, it combined CLAHE with Top-hat transformation to improve image quality. The study used DRIVE dataset that provided retinal image data. The image data in dataset was generated by the fundus camera. The CLAHE and Top-hat transformation methods were applied to rise the contrast and reduce noise on the image. The images that had good quality could help the segmentation process to find blood vessels in retinal images appropriately by a computer. It improved the performance of the segmentation method for detecting blood vessels in retinal image. Otsu Thresholding was used to segment blood vessel pixels and other pixels as background by local threshold. To evaluation performance of the proposed method, the study has been measured accuracy, sensitivity, and specificity. The DRIVE dataset's study results showed that the averages of accuracy, sensitivity, and specificity values were 94.7%, 72.28%, and 96.87%, respectively. It indicated that the proposed method was successful and well to work on blood vessels segmentation retinal images especially for thick blood vessels.
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