Ajeng Islamia Putri
Universitas Sriwijaya

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Pemanfaatan marketplace shopee sebagai strategi untuk meningkatkan pemasaran kain songket Anita Desiani; Irmeilyana Irmeilyana; Ajeng Islamia Putri; Enyta Yuniar; Nur Avisa Calista; Siddiq Makhalli; Ali Amran
Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Vol 4, No 2 (2021): Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS)
Publisher : University of Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/jipemas.v4i2.9222

Abstract

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.
Contrast Enhancement for Improved Blood Vessels Retinal Segmentation Using Top-Hat Transformation and Otsu Thresholding Muhammad Arhami; Anita Desiani; Sugandi Yahdin; Ajeng Islamia Putri; Rifkie Primartha; Husaini Husaini
International Journal of Advances in Intelligent Informatics Vol 8, No 2 (2022): July 2022
Publisher : Universitas Ahmad Dahlan

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Abstract

Diabetic Retinopathy is a diabetes complication that usually results in abnormalities in the retinal blood vessels of the eye, resulting in blurry vision, including blurry vision and blindness. Automatic segmentation of blood vessels in retinal images 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, including Contrast Limited Adaptive Histogram Equalization (CLAHE) and Top-hat transformation for the retinal image. The retinal image data used in the study were the Digital Retinal Images for Vessel Extraction (DRIVE) dataset generated by the fundus camera. The CLAHE and Top-hat transformation methods were used to increase the contrast of the retinal image and reduce noise so that blood vessels could be highlighted appropriately and the segmentation process could be facilitated. Otsu Thresholding was used to distinguish between blood vessel pixels and background pixels. The performance evaluation measures of the methods used are accuracy, sensitivity, and specificity. The DRIVE dataset's study results showed that the average accuracy, sensitivity, and specificity values were 94.7%, 72.28%, and 96.87%, respectively, indicating that the proposed method was successful through blood vessels segmentation retinal images, especially for thick blood vessels.