Identifikasi Kadar Semen dan Pasir Melalui CitraPermukaanMenggunakan Teknik Blok Citra

Gasim, Gasim and Sudiadi, Sudiadi and Desy Iba Ricoida, Desy Iba Ricoida and Rusbandi, Rusbandi and Rizani Teguh, Rizani Teguh (2020) Identifikasi Kadar Semen dan Pasir Melalui CitraPermukaanMenggunakan Teknik Blok Citra. JATISI (Jurnal Teknik Informatika dan Sistem Informasi), 7 (2). pp. 188-199. ISSN ISSN 2407- 4322, E- ISSN 2503-2933

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Abstract

This research raises the topic of identifying the types of cement and sand mixtures on dry material using artificial intelligence. This is done because the comparison of the mixture between cement and sand is very influential on the quality of the material produced. Several experimental models affect the level of recognition accuracy. In this study the experimental model used was the image block and LBP image techniques, with a mixture of cement and sand used was 1: 1, 1: 1.5, 1: 2, 1: 2.5, 1: 3, and 1: 3.5. The recognition method used is Artificial Neural Network (ANN) with back propagation algorithm. The number of ANN training samples is 600 samples, and 120 samples for testing. This research uses image block technique before feature extraction is carried out. The features used are the mean, standard deviation, entropy, skewness, and kurtosis of LBP images. ANN training results get a three-layer hidden architecture, with testing showing an accuracy rate of 80% recognition.

Item Type:	Article
Uncontrolled Keywords:	Campuran semen pasir, Teknik blok citra, JST, LBP
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User:	Mrs Ni Made Yunia Dwi Savitri
Date Deposited:	18 Nov 2022 07:26
Last Modified:	18 Nov 2022 07:26
URI:	http://eprints.triatmamulya.ac.id/id/eprint/1858

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