Febri Liantoni
Teknik Informatika, Fakultas Teknologi Informasi, Institut Teknologi Adhi Tama Surabaya

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Adaptive Ant Colony Optimization on Mango Classification Using K-Nearest Neighbor and Support Vector Machine Febri Liantoni; Luky Agus Hermanto
Journal of Information Systems Engineering and Business Intelligence Vol. 3 No. 2 (2017): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (726.262 KB) | DOI: 10.20473/jisebi.3.2.75-79

Abstract

Abstract— Leaves recognition can use an image edge detection method. In this research, the classification of mango gadung and manalagi will be performed. In the preprocess stage edge detection method using adaptive ant colony optimization method. The use of adaptive ant colony optimization method aims to optimize the process of edge detection of a mango leaves the bone image. The application of ant colony optimization method on mango leaves classification has successfully optimized the result of edge detection of a mango leaves the bone structure. Results showed edge detection using adaptive ant colony optimization method better than Roberts and Sobel method. The result an experiment of mango leaves classification with k-nearest neighbor method get accuracy value equal to 66,25%, whereas with the method of support vector machine obtained accuracy value equal to 68,75%.Keywords— Edge Detection, Ant Colony Optimization, Classification, K-Nearest Neighbor, Support Vector Machine
Image Retrival Pada Obyek Lingga Yoni Di Situs Peninggalan Sejarah Trowulan Mojokerto Hendro Nugroho; Febri Liantoni
INTEGER: Journal of Information Technology Vol 1, No 1 (2016): Maret 2016
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2016.v1i1.55

Abstract

This study contains about Image Retrieval system image on Lingga Yoni at historical sites Trowulan. In the area Trowulan is a legacy of work Majapahit era where the majority of people it is a Hindu, so many relics found in the form of Linga Yoni which serves as the worship of Lord Shiva. Data retrieval image Yoni Linga Linga Yoni as many as 50 images using a digital camera, and the image size Lingga Yoni 200 x 300 pixels in BMP file format. Stages Image Retrieval system on the study include segmentation stages: (1) Smoothing using the method Pas Low Filter to soften the image of the noise; (2) the extraction step texture by using Region Growing by altering the RGB color image is converted into to facilitate the HSL color groups; (3) Region Region Merging Growing did for the incorporation of color image corresponding to the object Linga Yoni; (4) to get to extraction stage form was originally looking for edge detection using Canny edge; (5) the image is converted into binary form to the morphology using opening and closing. At Stages Image Retrieval 50 Linga Yoni image texture extraction step performed using the 4 corners of each feature value GLCM with Different Inverse Moment IDM to revise the results of Image Retrieval using methods Precision and Recall.