Rice is an agricultural commodity that is a staple food in Indonesia with hundreds of types of rice that have different characteristics. The type of rice can be distinguished from color and shape. The main feature that is dominant and can distinguish each type of rice is the color and shape. This feature is the main key in identifying types of rice. Identification is done by comparing the similarity of rice images using the value of color and shape features. The similarity can be determined through the difference in feature values between the query image and the database image. The closer the difference is to zero, the higher the level of similarity. The degree of similarity will affect the accuracy of image recognition at the time of identification. In this study, an analysis of the accuracy of image identification and measurement of computation time was carried out. Improved identification accuracy using the weighting of color and shape feature values. Extraction of the two value features using the invariant moment and color moment. Preprocessing before extraction using Grayscale, resize, edge Enhancement, Histogram Equalization. Clustering of rice image data using K-Means clustering. The results showed that the accuracy of identification with 400 rice image test data, reached more than 95% in the weighting scheme Ws (weighted Shape) = 40% and Wc (weighted color) = 60% with an average computing time of 5 milliseconds at 10 the cluster.
The image has the features of shape, color and texture that are vary. Each feature has a different performance in supporting the accuracy of information retrieval using a process approach to CBIR (Content-Based Image Retrieval). On the image with different objects different performance will be generated on each feature. For example, that the performance features of the form of the more dominant compared features color and texture on the image with the face, while the object on the image with the object of interest feature is more dominant than the features of texture and shape. In this research was conducted on the analysis of the performance features of the shape, color and texture in supporting the accuracy of a search using the approach of CBIR (Content Based Image Retrieval). The method used are invariant moment, color moment and GLCM (Grey Level Co-occurrence Matrix). The results showed that the best search accuracy is 95%, where the features of shape has a performance by 50%, 30% color feature and texture feature by 20% with 600test image with object database face.
<p>UMKM Koveksi Baju Muslim adalah Mitra pada program Pengabdian Kepada Masyarakat yang berlokasi di Desa Nalumsari Jepara. UMKM ini memproduksi dan menjual segala macam baju muslim, mulai dari hijab, dress, sampai dengan asesoriesnya. UMKM juga menerima pesanan dengan custom khusus yang didesain dari pemesan maupun desain permintaan pemesan. Permasalahan yang dihadapi oleh mitra adalah dalam masih terbatasnya jangkauan pemasaran yaitu masih menggunakan pemasaran konvensional. Belum memiliki katalog produk baik digital maupun hardcopy agar pelanggan dan calon pelanggan dapat melihat- lihat produk beserta spesifikasinya dengan mudah. Solusi untuk mengatasi permasalahan adalah akan dilakukan rancang bangun katalog produk digital dan media pemasaran on-line berbasis web dan update informasi web pemasaran. Target dari pogram kegiatan pengabdian kepada masyarakat ini adalah meningkatnya jumlah produk dipajang pada ruang pemasaran online dan omzet penjualan meningkat lebih dari 10%, menggunakan aplikasi web untuk memperluas jangkauan pemasaran, menghasilkan prosiding atau Artikel pada jurnal, video kegiatan dan publikasi pada media massa.</p>
<p><em>This research purposes to analyze the impact of production added value from textile industries and logistic service to textile export value in Central Java. The secondary data used are an export statistic and regional domestic product total, and logistics service between 2010 and 2017. The result shows that, first, production added value has negatively influence to textile export value. Second, logistic service has a positive effect on export value. It implies that textile export value may result in order demand. In addition, logistics service has the main role to boost up textile export.</em></p>
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