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All Journal Jurnal RESISTOR (Rekayasa Sistem Komputer) International Journal Of Computer, Network Security and Information System (IJCONSIST)
Hendra Maulana
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Computer Science & IT Electrical & Electronics Engineering Energy Engineering

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Classification of color features in butterflies using the Support Vector Machine (SVM) Dhian Satria Yudha Kartika; Hendra Maulana
IJCONSIST JOURNALS Vol 2 No 02 (2021): March
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (381.57 KB) | DOI: 10.33005/ijconsist.v2i02.50

Abstract

Research in digital images is expanding widely and includes several sectors. One sector currently being carried out research is in insects; specifically, butterflies are used as a dataset. A total of 890 types of butterflies divided into ten classes were used as a dataset and classified based on color. Ten types of butterflies include Danaus plexippus, Heliconius charitonius, Heliconius erato, Junonia coenia, Lycaena phlaeas, Nymphalis antiopa, Papilio cresphontes, Pieris rapae, Vanessa atalanta, Vanessa cardui. The process of extracting color features on butterfly wings uses the RGB method to become HSV color space with color quantization (CQ). The purpose of adding CQ is that the computation process is carried out faster without reducing the image's information. In the color feature extraction process, the image is converted into 3-pixel sizes and normalized. The process of normalizing the dataset has the aim that the value ranges in the dataset have the same value. The 890 butterfly dataset was classified using the Support Vector Machine (SVM) method. Based on this research process, the accuracy of the 256x160 pixel size is 72%, the 420x315 pixel is 75%, and the 768x576 pixel is 75%. The test results on a system with a 768x576 pixel get the highest results with a precision value of 74.6%, a recall of 72%, and an f-measure of 73.2% Keywords—image processing; classification; butterflies; color features; features extraction
Implementasi AES 256 Untuk Pengamanan Data Pada Supply Chain Management BUMDes Sarining Winangun Kukuh Made Hanindia Prami Swari; Hendra Maulana; I Putu Susila Handika; I Kadek Susila Satwika
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 6 No. 1 (2023): Jurnal RESISTOR Edisi April 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v6i1.1332

Abstract

SCM (Supply Chain Management) merupakan suatu metode atau pendekatan proses pengintegrasian informasi dari aliran rantai dalam memperoleh bahan mentah yang dilanjutkan kegiatan transformasi sehingga menjadi produk dalam proses, sehingga menjadi produk jadi. Hal utama dari konsep SCM ini yaitu bagaimana mengurangi kesia siaan produk dan bagaimana caranya mengoptimalkan nilai produk tersebut pada rantai pasok yang berkaitan. Supply Chain Management mengutamakan arus barang antar perusahaan dari hulu ke hilir (dari perusahaan ke toko) dan melibatkan supplier sampai dengan pelanggan. Dalam penelitian ini bertujuan untuk mengembangkan Sistem SCM untuk mempermudah manajemen rantai pasok pada BUMDes Sarining Winangun Kukuh, khususnya pada unit usaha pertokoan. Dimana sistem yang akan dikembangkan terintegrasi dengan sistem lain, yakni sistem akuntansi BUMDes. Sehingga seluruh proses bisnis pada unit usaha pertokoan BUMDes Sarining Winangun Kukuh, yakni proses keluar masuk barang, maupun proses keuangannya akan seluruhnya tercatat pada sistem berbasis web. Untuk mengamankan data yang terlibat dalam proses SCM, maka dilakukan pula implementasi AES 256, dan berdasarkan hasil pengujian menggunakan black box dapat dinyatakan bahwa SCM yang dikembangkan pada penelitian telah memenuhi seluruh fungsionalitas sistem dengan rata-rata waktu enkripsi selama 0.00001518 detik dan rata-rata waktu dekripsi selama 0.00001518 detik.
Co-Authors Dhian Satria Yudha Kartika Fetty Tri Anggraeny I Putu Susila Handika Made Hanindia Prami Swari Mohamad Ilham Prasetyo Raharjo Satwika, I Kadek Susila