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All Journal Berkala Penelitian Teknologi Kulit, Sepatu, dan Produk Kulit
Latifah Listyalina
Department of Plastic and Rubber Processing Technology, Politeknik ATK Yogyakarta, 55188, Special Distric of Yogyakarta, Indonesia

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ANTIBACTERIAL ACTIVITY OF SAMBILOTO (ANDROGRAPHIS PANICULATA, NEES) ETHANOL EXTRACT AGAINST STAPHYLOCOCCUS AUREUS Naimah Putri; Latifah Listyalina
Berkala Penelitian Teknologi Kulit, Sepatu, dan Produk Kulit Vol. 22 No. 1 (2023): Berkala Penelitian Kulit, Sepatu dan Produk Kulit
Publisher : Politek ATK Yogyakarta Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58533/852kk888

Abstract

The use of traditional plants can be used as natural antibacterial in preventing and treating infectious wound diseases caused by Staphylococcus aureus. One of the plants that can be used is bitter leaf. Sambiloto leaves contain several substances that can be used as antibacterial including alkaloids, flavonoids, saponins and tannins. The purpose of this study were to determine the lowest concentration of bitter leaf extract (Andrographis paniculata, Nees) which can inhibit and kill Staphylococcus aureus field isolates in vitro by dilution method. This research was expected to provide information on the benefits of bitter leaf as a drug that can be used in the treatment of infections against Staphylococcus aureus. This study used the dilution method which included Minimum Inhibitory Concentration (MIC) and Minimum Bacteriocid Concentration (MBC). The test results showed that bitter leaf extract (Andrographis paniculata, Nees) had the ability to inhibit the growth of Staphylococcus aureus starting at a concentration of 25% and had the ability to kill Staphylococcus aureus starting at a concentration of 50%.
EXPLORATION OF LANTUNG WOOD LEATHER WITH DESIGN THINKING METHOD FOR PRODUCT DEVELOPMENT OF LANTUNG BENGKULU MSMEs Mochammad Charis Hidayahtullah; Eka Legya; Yuafni; Sugiyanto; Naimah Putri; Fauzi Ashari; Latifah Listyalina; Wahyu Ratnaningsih
Berkala Penelitian Teknologi Kulit, Sepatu, dan Produk Kulit Vol. 21 No. 2 (2022): Berkala Penelitian Kulit, Sepatu dan Produk Kulit
Publisher : Politek ATK Yogyakarta Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58533/1fp7hf54

Abstract

Indonesia is one of the countries that have contributed to the apparel, leather, and textile industry in the international market. Not only that, but Indonesian MSME handicrafts are also one of the commodities that can increase the country's foreign exchange, one of which is the lantung bark craft from Bengkulu. However, the creative industry is constantly facing competition with the entry of cheap products from China that get easy access with the increasing e-commerce technology. Providing value for the Lantung Bengkulu MSME products to compete locally and globally, one of the steps is to apply the Design Thinking Method and take the distinctive character of the stylized Serawai Tribe Weaving in the exploration process. The results of this study have obtained data that 47 Bengkulu women consumers as much as 89.4% like the results of the re-design and exploration of lantung shoes that have been designed. In determining the selling price of MSME Lantung Bengkulu should also set a price range of Rp. 110.000 to Rp. 500.000 because it corresponds to the purchasing power of female consumers in Bengkulu. The results of this study directly contribute to providing product value to the typical Bengkulu Lantung MSMEs. The Design Thinking method has been successfully increasing the value of the Lantung Bengkulu MSME products, this method can be applied to similar research to develop local MSMEs in Indonesia.
IDENTIFICATION OF TIRE RUBBER FEASIBILITY WITH CNN RESNET-50 MODEL Latifah Listyalina
Berkala Penelitian Teknologi Kulit, Sepatu, dan Produk Kulit Vol. 21 No. 2 (2022): Berkala Penelitian Kulit, Sepatu dan Produk Kulit
Publisher : Politek ATK Yogyakarta Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58533/xrbhhm62

Abstract

In this study, the authors designed an algorithm based on a convolutional neural network that is capable of automatically classifying tire rubber eligibility according to the appearance of the tire on the tire image. The proposed algorithm will be built through several stages as follows. In the first stage, tire image acquisition will be carried out which will be the input of the designed algorithm. Furthermore, the acquired image will be divided into two sets, namely training and testing sets. The training set contains tire images that will be used at the training stage of several convolutional neural network architectures to be able to and classify them to the appropriate level of feasibility. The training phase will be carried out in a number of epohs, and at each epoh, the cross entropy loss function value will be calculated which expresses the performance of the convolutional neural network architecture in classifying tire images. In this study, the author has designed an algorithm based on deep learning that is capable of automatically classifying tire eligibility. The proposed algorithm has been built through several stages such as tire image acquisition, training of several CNN models, especially ResNet-50. The CNN architecture test is trained to classify tire images from the test set. In addition, the accuracy value has also been calculated which shows the percentage of the number of tire images that are successfully classified correctly to the total number of tire images in the test set, which is an accuracy of 88.31%.
Co-Authors Eka Legya Fauzi Ashari Mochammad Charis Hidayahtullah Naimah Putri Sugiyanto Wahyu Ratnaningsih Yuafni