Identification of Sea Urchins in the Melonguane Coastal Area using Multilayer Perceptron Neural Network


Andar Alwein Pinilas(1); Luther Alexander Latumakulita(2*); Djoni Hatidja(3); Yaulie Deo Rindengan(4); Quido Conferti Kainde(5);

(1) Sam Ratulangi University
(2) Sam Ratulangi University
(3) Sam Ratulangi University
(4) Sam Ratulangi University
(5) Universitas Negeri Manado
(*) Corresponding Author

  

Abstract


Sea urchins (Echinoidea) are marine biota that is found in Indonesian waters and there are 950 types of sea urchins scattered throughout the world. This study aims to classify types of sea urchins based on the characteristics contained in sea urchin images using the Multilayer Perceptron Neural Network (MLP-NN) method with 3 classification classes. 120 sea urchin image data were taken from the Melonguane beach area, Talaud Islands Regency, North Sulawesi Province. In the MLP-NN stage, training, validation, and testing processes are carried out by applying 8-fold cross-validation, and the system performance shows the lowest accuracy of 93.33%, the highest 100%, and an average of 98.33%. The experimental results indicate that MLP-NN can classify sea urchins with good performance.


Keywords


classification; Sea urchin; Multi Layer Perceptron

  
     

Article Metrics

Abstract view: 149 times
     

Digital Object Identifier

  

Cite

References


Karmana, O., dan Fitriana, R., 2007. Cerdas Belajar Biologi. Grafindo Media Pratama, Bandung. 338 halaman.

Lalombombuida, S., M. Langoy, dan D. Y. Katili, 2019. Keanekargaman Echidodermata di Pantai Paranti Desa Tabang, Kecamatan Rainis Kabupaten Kepulauan Talaud Provinsi Sulawesi Utara. Jurnal Perikanan dan Kelautan Tropis, 10(2), 39-50.

Muliantara, A., dan I. M. Widiartha, 2011. Penerapan Multi Layer Perceptron dalam Anotasi Image secara Otomatis. Jurnal Ilmu Komputer, 4(2), 9-15.

Latumakulita, L. A., and T. Usagawa, 2017. "A combination of backpropagation neural network on fuzzy inference system approach in Indonesia scholarship selection process: Case study: Bidik misi scholarship selection," 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), pp. 1309-1314.

Latumakulita, L. A., and T. Usagawa, 2018. Indonesia Scholarship Selection Model Using a Combination of Back-Propagation Neural Network and Fuzzy Inference System Approaches. International Journal of Intelligent Engineering and Systems, 11(3), 79-80.

Mairi, V. G. N., A. L. Latumakulita, dan T. S. Deiby, 2021. Sistem Identifikasi Jenis Ikan Karang Lokal Taman Nasional Bunaken Menggunakan Metode Backpropagation Neural Network . Proceeding KONIK (Konferensi Nasional Ilmu Komputer), 5(1), 307311.

Santoso, H. M,. D. A. Larasati, dan Muhathir, 2020. Wayang Image Classification using MLP Method and GLCM FeatureExtraction. Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE), 1(2), 111-119.

Purnama, N., I. K. G. D. Putra, dan P. A. Bayupati, 2014. Klasifikasi Website Menggunakan Algoritma Multilayer Perceptron. Jurnal Teknologi Elektro, 13(2), 8-15.

Nurhadi, dan Yanti, F., 2016. Buku ajar taksonomi invertebrata/ oleh, Drs. Nurhadi, M.Si. & Febri Yanti, M.Pd. Deepublish, Yogyakarta. 115 halaman.

Toha, A. H. A., 2006. Manfaat Bulu Babi (Echinoidea), dari Sumber Pangan Sampai Organisme Hias. Jurnal Ilmu-ilmu Perairan dan Perikanan Indonesia, 13(1), 77-82.

Purnama, N., I. K. G. D. Putra, dan P. A. Bayupati, 2014. Klasifikasi Website Menggunakan Algoritma Multilayer Perceptron. Jurnal Teknologi Elektro, 13(2), 8-15.

Fachrie, M., dan A. P. Wibowo, 2018. Jaringan Saraf Tiruan Untuk Memprediksi Kinerja SATPAM. Jurnal Informatika dan Komputer (JIKO), 3(1), 46-51.

Widjaya, A., L., Hiryanto, dan T., Handhayani, 2017. Prediksi masa studi mahasiswa dengan voting feature interval 5 pada aplikasi konsultasi akademik online. Journal of Computer Science and Information Systems, 1(1), 25-33.

Karsito, Susanti, S., 2019. Klasifikasi Kelayakan Peserta Pengajuan Kredit Rumah dengan Algoritma Nave Bayes di Perumahan Azzura Residencia. Jurnal Teknologi Pelita Bangsa, 9(3), 43-48.

Yuniarto, S. M., dan A. E. Sarwoko, 2020. Implementasi Metode K-Nearest Neighbor untuk Diagnosis Kanker Kolorektal dengan Biomarker Micro-RNA, Jurnal Masyarakat Informatika, 11(1), pp. 35-48.

Arini, L. K. Wardhani, dan D. Octaviano, 2020. Perbandingan Seleksi Fitur Term Frequency & Tri-Gram Character Menggunakan Algoritma Nave Bayes Classifier (Nbc) Pada Tweet Hashtag #2019gantipresiden. KILAT, 9(1), 103 114.


Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Andar Alwein Pinilas, Luther Alexander Latumakulita, Djoni Hatidja Hatidja

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

 ILKOM Jurnal Ilmiah indexed by

doaj_logoDimensions_logoCROSSREF_logoROAD_logoPKP_Index_logoGoogle_Scholar_logosinta_logogaruda_logoonesearch_logoBASE_logoWordcat_logo

___________________________________________________________
ILKOM Jurnal Ilmiah
ISSN 2548-7779
Published by Prodi Teknik Informatika FIK Universitas Muslim Indonesia
W : https://fikom.umi.ac.id/
E : jurnal.ilkom@umi.ac.id

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0