At present, plastic is a material that is needed by the community at large, where the impact is also very extraordinary after the plastic is used in everyday life which can cause serious problems if the management is not done properly. The problem of plastic waste does not only occur in the city of Semarang, but also in other cities, so that the Ministry of Environment and Forestry has implemented a paid plastic bag program in the short term. But this is only to deal with problems in the short term. In the long run, it will not solve the problem of "plastic waste", because the policy actually encourages people to buy plastic which, of course, will add a new burden for the community to buy it. Based on the above problems, it is necessary to utilize this plastic waste to be made into road pavement materials such as in the manufacture of Asphal Concrette Wearing Course, by making 5 mixed variations ranging from (2 to 10)% of the weight of the aggregate . This research was initiated through a survey process, material procurement, testing of stacking materials, making test specimens, testing specimens. The results of the research can show that the type of Thermosetting plastic waste has a significant influence on the Asphalt Concrete mixture AC-WC heat mixture, including: Density, Marshall Stability, Flow, VIM, VMA, MQ and the remaining Marshall Stability tend to show an increase, moderate VFA and VIMrefusal Density values tend to show a decrease. Thus the plastic waste from the Thermosetting type can be used as a partial replacement of the aggregate for the Asphalt Concrete mixture AC-WC heat mixture with a plastic waste content is limited to a maximum of 10% and at an optimum asphalt content of 5.55%. Thus this research is expected to be of benefit to the industry and the people of Semarang in relation to the use of plastic waste for road pavement.
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>
Uncontrolled erosion would cause considerable damages, such as soil fertility decline, water structures damage and reservoirs sedimentation. As the data for the sedimentation rate are limited, several models have been developed to predict the surface erosion and the rate of sedimentation. However, the availability of sufficient, diverse and extensive data is needed for the implementation of the models, both for the model calibration and the verification. The result of the analysis shows that both of the Water Tank Models that represent the erosion-sedimentation rate process, in which Water Tank 1 being the three-tank cascade system and Water Tank 2 being two-tank cascade system, are not optimum. This can be observed from the values of volume error (VE), relative error (RE), root-mean-square error (RMSE) and correlation coefficient (R) that show the effect of 1.5 hours of rain period in the sedimentation rate. The field condition shows considerable sedimentation, on the other hand, the models’ simulations show decreasing sedimentation rates. The optimum model’s parameters for Water Tank 1 and Water Tank 2 are 924.51%-1049.26% for the relative error, 50.81% - 121.42% for the volume error, 0.9 for the correlation coefficient and 6703.59-17,297.85 for the root-mean-square error. The parameters and constant’s values of the models are different relative to the drainage basins’ condition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.