scholarly journals Analisis Morfometrik dan Klasifikasi Bentuk Lutjanus spp. Berdasarkan Gambar Digital

2020 ◽  
Vol 12 (2) ◽  
pp. 194
Author(s):  
Muhammad Ikhwani Saputra ◽  
Ishak Ariawan ◽  
Riad Sahara

Lutjanus spp is a genus of the Lutjanidae family. The number of Lutjanus spp in waters around the world are 72 species. For this amount, 33 of them living on Indonesian waters. According to the IUCN List (2020), about ten species have decreased in population. One of the causes that population decline in several species is, the recording of capture fisheries has very limited production data. This is caused by the difficulty of identification in the field, which results in the overfishing of certain species. The identification process can be carried out based on morphometric features. Geometric morphometrics can be explaining morphological variations objectively and accurately. There are several methods used to represent the shape of an image in general. Namely point linking, complex coordinate, tangent angle, contour curvature, and triangle-area representation.Lutjanus spp by calculating the value of landmark positions, landmark curvature, changes in landmark angle, landmark distance, and landmark inclination. The results of feature extraction were used to classify Lutjanus spp (Lutjanus argentimaculatus, Lutjanus bohar, Lutjanus carponotatus, Lutjanus fulviflamma, and Lutjanus sebae). The results of this study indicate that the morphometric geometric approach can extract the feature values of the position of landmarks, a curvature of landmarks, changes in the angle of the landmark, distance of landmark, and the inclination of the landmark. The classification results using the Support Vector Machine (SVM) classification technique can distinguish Lutjanus spp with an accuracy rate of 65.03%. Thus, the application of SVM can be used to classify Lutjanus spp species, which will be useful in the identification process. Keywords: clasificasion, identification, morphometric geometric, Lutjanus spp, support vector machine. AbstrakLutjanus spp. adalah salah satu marga dari famili Lutjanidae. Jumlah spesies Lutjanus spp di perairan seluruh dunia yaitu 72 spesies. Dari 72 spesies tersebut 33 diantaranya hidup di perairan Indonesia. Menurut IUCN (2020) sekitar 10 spesies mengalami penurunan populasi. Salah satu penyebab menurunnya populasi pada beberapa spesies yaitu pencatatan data produksi perikanan tangkap masih sangat terbatas. Hal ini disebakan oleh sulitnya identifikasi di lapangan sehingga mengakibatkan overfishing pada spesies tertentu. Proses identifikasi dapat dilakukan berdasarkan ciri morphometrik. Geometri Morfometrik dapat menjelaskan variasi morfologi secara objektif dan akurat. Ada beberapa metode yang digunakan dalam merepresentasi bentuk suatu citra secara umum. yaitu point linking, complex coordinate, tangent angle, contour curvature, serta triangle-area representation. Pendekatan morphometric geometric pada penellitian ini digunakan untuk mengekstraksi fitur bentuk Lutjanus spp. dengan menghitung nilai posisi landmark, kelengkungan landmark, perubahan sudut landmark, jarak landmark, dan kemiringan landmark. Hasil ekstraksi fitur digunakan untuk mengklasifikasikan spesies Lutjanus spp. (Lutjanus argentimaculatus, Lutjanus bohar, Lutjanus carponotatus, Lutjanus fulviflamma, dan Lutjanus sebae). Hasil penelitian ini menunjukkan, bahwa pendekatan Geometri Morfometrik dapat melakukan ekstraksi nilai fitur posisi landmark, kelengkungan landmark, perubahan sudut landmark, jarak landmark, dan kemiringan landmark.  Adapun hasil klasifikasi menggunakan teknik klasifikasi Support Vector Machine (SVM) mampu membedakan spesies Lutjanus spp. dengan tingkat akurasi sebesar 65.03%. Dengan demikian, penerapan SVM dapat digunakan untuk melakukan klasifikasi terhadap spesies Lutjanus spp yang akan bermanfaat pada proses identifikasi.Kata kuncis: klasifikasi, identifikasi, geometri morfometrik, spesies lutjanus spp., support vector machine. 

2020 ◽  
Author(s):  
V Vasilevska ◽  
K Schlaaf ◽  
H Dobrowolny ◽  
G Meyer-Lotz ◽  
HG Bernstein ◽  
...  

2019 ◽  
Vol 15 (2) ◽  
pp. 275-280
Author(s):  
Agus Setiyono ◽  
Hilman F Pardede

It is now common for a cellphone to receive spam messages. Great number of received messages making it difficult for human to classify those messages to Spam or no Spam.  One way to overcome this problem is to use Data Mining for automatic classifications. In this paper, we investigate various data mining techniques, named Support Vector Machine, Multinomial Naïve Bayes and Decision Tree for automatic spam detection. Our experimental results show that Support Vector Machine algorithm is the best algorithm over three evaluated algorithms. Support Vector Machine achieves 98.33%, while Multinomial Naïve Bayes achieves 98.13% and Decision Tree is at 97.10 % accuracy.


2011 ◽  
Vol 131 (8) ◽  
pp. 1495-1501
Author(s):  
Dongshik Kang ◽  
Masaki Higa ◽  
Hayao Miyagi ◽  
Ikugo Mitsui ◽  
Masanobu Fujita ◽  
...  

Author(s):  
Ryoichi ISAWA ◽  
Tao BAN ◽  
Shanqing GUO ◽  
Daisuke INOUE ◽  
Koji NAKAO

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