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All Journal Pixel : Jurnal Ilmiah Komputer Grafis Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Media Sisfo
Setyawan Wibisono
unisbank semarang
Computer Science & IT Education

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Journal : Elkom: Jurnal Elektronika dan Komputer

 1 
Implementasi AHP-WASPAS Untuk Pemilihan Internet Service Provider (ISP) dirgantara krisna gaesa; Setyawan Wibisono
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.992

Abstract

Internet Service Provider (ISP) is a company that provides internet services. The ISP network is a national and international scale network so that customers can be connected globally. There are many factors that must be considered in selecting an ISP, making choosing an ISP a difficult task. Factors that influence ISP selection include cost, bandwidth, coverage area and type of connection. ISP providers offer a variety of advantages that make it difficult for customers to choose the right provider. The method applied in determining ISP providers is the AHP method used for weighting criteria while the WASPAS method is used for evaluating ISP providers with the criteria of cost, bandwidth, coverage area and type of connection. The rating process using the WASPAS method uses four assessment criteria, namely cost with a weight of 0.54, bandwidth with a weight of 0.38, coverage area with a weight of 0.05 and type of connection with a weight of 0.03. The final results of the ranking show that ISPs with low cost, large bandwidth and wide coverage areas will make these ISPs the best choice, this is because the criteria for cost, bandwidth and coverage area have high weight. Conversely, ISPs with high costs and small coverage areas will be the worst choices in the ranking list.
Implementasi AHP-WASPAS Untuk Pemilihan Internet Service Provider (ISP) dirgantara krisna gaesa; Setyawan Wibisono
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 1 (2023): Juli : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i1.992

Abstract

Internet Service Provider (ISP) is a company that provides internet services. The ISP network is a national and international scale network so that customers can be connected globally. There are many factors that must be considered in selecting an ISP, making choosing an ISP a difficult task. Factors that influence ISP selection include cost, bandwidth, coverage area and type of connection. ISP providers offer a variety of advantages that make it difficult for customers to choose the right provider. The method applied in determining ISP providers is the AHP method used for weighting criteria while the WASPAS method is used for evaluating ISP providers with the criteria of cost, bandwidth, coverage area and type of connection. The rating process using the WASPAS method uses four assessment criteria, namely cost with a weight of 0.54, bandwidth with a weight of 0.38, coverage area with a weight of 0.05 and type of connection with a weight of 0.03. The final results of the ranking show that ISPs with low cost, large bandwidth and wide coverage areas will make these ISPs the best choice, this is because the criteria for cost, bandwidth and coverage area have high weight. Conversely, ISPs with high costs and small coverage areas will be the worst choices in the ranking list.
KLASIFIKASI JENIS JAMUR MENGGUNAKAN METODE NEURAL NETWORK DENGAN FITUR INCEPTION-V3 Okka Hermawan Yulianto; Setyawan Wibisono
Elkom : Jurnal Elektronika dan Komputer Vol 16 No 2 (2023): Desember : Jurnal Elektronika dan Komputer
Publisher : STEKOM PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/elkom.v16i2.1281

Abstract

Mushrooms are very diverse with characteristics of each type, there are 1,433,800 types of mushrooms that have not been recognized. In this study, researchers used the Neural Network and Deep Learning Inception V3 methods as a feature extraction process in images to classify mushroom images based on genus with the Orange Data Mining application. There are 9 genera of mushrooms used in this study, namely Agaricus, Amanita, Boletus, Cortinarius, Entoloma, Hygrocybe, Lactarius, Russula, and Suillus. The total dataset used is 2,700, with 300 images for each genus. The test uses the cross-validation method which is applied to the confusion matrix to get precision, recall, F1-score, and accuracy values. In this study, the final classification results were obtained with an accuracy of 82.5% and the genus Boletus mushroom obtained the best results with an accuracy of 98.9%.
Co-Authors dirgantara krisna gaesa Mohamad Riza Darmawan Muhammad Auva Al-Marom Okka Hermawan Yulianto