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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmiah Kursor Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science (JOINTECS) Jurnal Kreativitas PKM Jurnal Mantik Bakti Cendana: Jurnal Pengabdian Masyarakat Patria : Jurnal Pengabdian Kepada Masyarakat Jurnal Mandala Pengabdian Masyarakat Insyst : Journal of Intelligent System and Computation Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Pada Masyarakat Indonesia (JPPMI) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Atma Inovasia
Adri Gabriel Sooai
Ilmu Komputer Universitas Katolik Widya Mandira
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Journal : Jurnal Ilmiah Kursor

 1 
OPTIMIZING LANTANA CLASSIFICATION: HIGH-ACCURACY MODEL UTILIZING FEATURE EXTRACTION Sooai, Adri Gabriel; Mau, Sisilia Daeng Bakka; Siki, Yovinia Carmeneja Hoar; Manehat, Donatus Joseph; Sianturi, Shine Crossifixio; Mondolang, Alicia Herlin
Jurnal Ilmiah Kursor Vol. 12 No. 2 (2023)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v12i2.347

Abstract

As an invasive and poisonous plant, Lantana has become a pest in the agricultural world. Still, on the other hand, it becomes an ornamental plant with different positive potentials. Lantana flower datasets are not yet widely available for open image classification research, given that the research needs are still broad in remote sensing. This study aims to provide a model with classifier accuracy that outperforms similar studies and Lantana datasets for classification needs using several algorithms that can be run on small source computers. This study used five types of lantana colors, red, white, yellow, purple, and orange, as the primary dataset, which had 411 instances. VGG16 assisted feature extraction in preparing datasets for the data training using three classifiers: decision tree, AdaBoost, and k-NN. 2-fold cross-validation, 5-fold cross-validation, and a self-organizing map are used to help validate each process. The experiment to measure the classifier's performance resulted in a good figure of 99.8% accuracy for 2-fold cross-validation, 100% for 5-fold cross-validation, and a primary dataset of lantana interest that can be accessed freely on the IEEE Data port. This study outperformed other related studies in terms of classifier accuracy.
Co-Authors Adi Nugroho Adrianus Ketmoen Adrianus Ketmoen Agustinus Bimo Gumelar Alfry Aristo Jansen Sinlae Alicia Herlin Mondolang Aloysius Djalo Ambrosius Faofeto Ambrosius Faofeto Anggelinus Nadut Anselmus Boy Baunsele Aris Winaya Atyanta Nika Rumaksari Atyanta. N. Rumaksari Benediktus Anindito Boelan, Erly G. Budihardja Murtianta Chantika Elisabeth Hermanus4 Corazon Olivia Sianturi Didimus Dedi Dhosa Donatus Joseph Manehat Dwiandri, Fransiskus Asisi Aditya Dyana Sarvasti Emerensiana Ngaga Erly G. Boelan Fanani, Nurul Zainal Fransiskus Asisi Aditya Dwiandri Frengky Tedy Gerardus Diri Tukan Gloria Song Abimanyu Gunawan Dewantoro Hartanto Kusuma Wardana Henny Angri Manafe Hildegardis Missa Ignatius Pricher Agung Nirwanto Samane Khamid Khamid Khamid Khamid Laniwati, Melania Lenciani Seran Lukas Bambang Setyawan Maftuchah Maftuchah Maria Augustin Lopes Amaral Mariano Albertho Dewa Dewa Do Nascimento Mauridhi Hery Purnomo Mauridhi Hery Purnomo Maximus M Taek Meolbatak, Emiliana Metan Merpiseldin Nitsae Mochammad Mizanul Achlaq Moh Noor Al-Azam Mondolang, Alicia Herlin Natalia Magdalena Rafu Mamulak Nurul Zainal Fanani Paskalis Andrianus Nani Paskalis Andrianus Nani Patrisius Batarius Paul L Tahalele Paulina Aliandu Perdana, Muhammad Ilham Ratumakin, Paulus A. K. L. Riksakomara, Edwin Sardina Ndukang Shine Crossifixio Sianturi Sianturi, Shine Crossifixio Sisilia Daeng Bakka Mau Sudiarti, Yeyen Surya Sumpeno Taek, Maximus M. Wiwik Anggraeni Yoaclina D. Ninu Yolinda Yanti Sonbay Yovinia Carmeneja Hoar Siki