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Journal : Jurnal Ipteks Terapan : research of applied science and education

COMPARATIVE ANALYSIS OF PRODUCTION PREDICTION OF SILUNGKANG SONGKET AND PANDAI SIKEK SONGKET WITH MAMDANI FUZZY INFERENCE SYSTEM (FIS) METHOD Devia Kartika; Rima Liana Gema
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 14 No. 3 (2020): Re Publish Issue
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (440.241 KB) | DOI: 10.22216/jit.v14i3.106

Abstract

Fuzzy logic is widely applied in various fields, such as industry, communications, etc. Fuzzy logicwas developed to solve an obscure problem. The problem that arises in the production at MSMEsSongket Silungkang and Songket Pandai Sikek at this time is that there is no system used as areference in determining the amount of production in the future. Where this method can utilizedemand and supply data in the past which is then processed with fuzzy stages so as to produceproduction figures. The government has prioritized the development of the Silungkang songkethandicraft business, which is a regional specialty, in order to enter the export market. In the earlystages, the priority of the regional government was to increase the production of craftsmen byfacilitating coaching for micro, small and medium enterprises (MSMEs), especially those engaged insongket crafts, to continue to be developed by increasing quality and creativity. By applying theFuzzy Inference System method in predicting the production of Songket Silungkang KotaSawahlunto and Songket Pandai Sikek Kota Agam can help several parties such as the government,micro, small and medium enterprises in making efforts to handle and make good decisions towardsincreasing the production of Songket MSMEs in each region. and can provide a comparison of thepredicted results of production for the coming period so that it can produce the optimal number ofsongket based on market demand.
COMPARATIVE ANALYSIS OF PRODUCTION PREDICTION OF SILUNGKANG SONGKET AND PANDAI SIKEK SONGKET WITH MAMDANI FUZZY INFERENCE SYSTEM (FIS) METHOD Devia Kartika; Rima Liana Gema
Jurnal Ipteks Terapan Vol. 14 No. 3 (2020): Re Publish Issue
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (440.241 KB) | DOI: 10.22216/jit.v14i3.106

Abstract

Fuzzy logic is widely applied in various fields, such as industry, communications, etc. Fuzzy logicwas developed to solve an obscure problem. The problem that arises in the production at MSMEsSongket Silungkang and Songket Pandai Sikek at this time is that there is no system used as areference in determining the amount of production in the future. Where this method can utilizedemand and supply data in the past which is then processed with fuzzy stages so as to produceproduction figures. The government has prioritized the development of the Silungkang songkethandicraft business, which is a regional specialty, in order to enter the export market. In the earlystages, the priority of the regional government was to increase the production of craftsmen byfacilitating coaching for micro, small and medium enterprises (MSMEs), especially those engaged insongket crafts, to continue to be developed by increasing quality and creativity. By applying theFuzzy Inference System method in predicting the production of Songket Silungkang KotaSawahlunto and Songket Pandai Sikek Kota Agam can help several parties such as the government,micro, small and medium enterprises in making efforts to handle and make good decisions towardsincreasing the production of Songket MSMEs in each region. and can provide a comparison of thepredicted results of production for the coming period so that it can produce the optimal number ofsongket based on market demand.
EAR IMAGE SEGMENTATION WITH EDGE DETECTION METHOD ON CANNY AND LAPLACE ALGORITHMS Sri Rahmawati; Wifra Safitri; Devia Kartika
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 16 No. 4 (2022): Jurnal Ipteks Terapan : research of applied science and education
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (874.49 KB) | DOI: 10.22216/jit.v16i4.1764

Abstract

Technology in identifying ear shapes is the most important step in an automatic ear shape identification system. The purpose of this paper is to introduce an approach to image segmentation, color by determining the pixel values in the database and scanning results, the similarity results are formed, the error value of each image. The method used is color segmentation based on RGB(red, green, blue) values, edge detection with the canny and laplace methods and the results of the segmentation. The results obtained are that the program that has been created can identify the shape of the ear image in the database compared to the scanning results using the segmentation method and calculate the number of image pixels between the database image and the scanned image where the minimum number of pixels for the ear shape image in the database is 452 pixels, while the total the maximum pixels is 3028 pixels. For the image of the shape of the ear the result of scanning the minimum number of pixels is 419 pixels and the maximum number of pixels is 2742 pixels. The percentage of identification results for the shape of the ear has an average similarity level: 92%, the results of this study show a very high level of accuracy. The percentage of error in identifying the shape of the ear has an average error rate of: 8%, the results of this study indicate a very low error rate. a conclusion that comparing one image with another image will get a very high level of accuracy in the canny image results are better because the edge detection is clearer and the noise is less. While image laplace is worse because there is a lot of noise