Bastami, Ahmad Alfian and Sumari, Arwin Datumaya Wahyudi and Rahmad, Cahya (2020) KLASIFIKASI MUTU DAGING KELAPA BERDASARKAN WARNA DAN TEKSTUR UNTUK PRODUKSI WINGKO YANG BERKUALITAS MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) (STUDI KASUS PADA UD. PUTRA AGUNG). Diploma thesis, Jurusan Teknologi Informasi.
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Abstract
Bastami, Ahmad Alfian. “Klasifikasi Mutu Daging Daging Kelapa Berdasarkan Warna dan Tekstur Untuk Produksi Wingko yang Berkualitas Menggunakan Metode Support Vector Machine (SVM) (Studi Kasus Pada UD. Putra Agung).”. Pembimbing: (1) Kolonel Lek. Dr. Ir. Arwin Datumaya Wahyudi Sumari, S.T., M.T., IPM., ASEAN Eng. (2) Cahya Rahmad, ST., M.Kom., Dr. Eng. Skripsi, Program Studi Teknik Informatika, Jurusan Teknologi Informasi, Politeknik Negeri Malang, 2020. Mutu daging kelapa adalah faktor utama yang menentukan kualitas produksi wingko baik yang berasal dari kelapa muda atau kelapa tua dari varietas genjah. Dalam upaya menjaga kualitas produksi wingko kelapa, diperlukan teknik dalam memilih daging kelapa yang bermutu tinggi secara konsisten dengan bantuan teknologi. Dalam penelitian ini telah dibangun sebuah sistem pencitraan digital berbasis Kecerdasan Artifisial untuk pemilihan daging kelapa bermutu. Pemilihan tersebut didasarkan pada warna dan tekstur dengan memanfaatkan Support Vector Machine (SVM) sebagai pengklasifikasi, dan fusi informasi. Pengolahan citra digital menggunakan kombinasi metode Hue, Saturation, Value (HSV) dan metode Gray-Level Co-Occurrence Matrix (GLCM) sebagai pengekstraksi fitur warna dan fitur energi. Kedua macam fitur tersebut difusikan menjadi fitur tunggal guna mempercepat klasifikasi oleh SVM sebagai landasan pemilihan daging kelapa. Dengan menggunakan sistem ini, pemilihan daging kelapa bermutu berhasil mencapai akurasi sebesar 50%. Dalam penelitian ini juga ditemukan bahwa ketidak tepatan pelabelan memberi dampak signifikan pada akurasi pemilihan daging kelapa. Kata Kunci : daging kelapa, fusi informasi, Kecerdasan Artifisial, pemilihan daging kelapa bermutu, pengolahan citra digital, SVM. Bastami., Ahmad Alfian. “Color And Texture-Based Coconut Meat Quality Selection For Qualified Wingko Production Using Support Vector Machine (SVM) And Information Fusion: (Case Study On UD. Putra Agung)”. Advisors: (1) Kolonel Lek. Dr. Ir. Arwin Datumaya Wahyudi Sumari, S.T., M.T., IPM., ASEAN Eng., (2) Cahya Rahmad, ST., M.Kom., Dr. Eng. Thesis, Informatics Management Study Program, Department of Information Technology, State Polytechnic of Malang, 2020. The quality of coconut meat is a primary factor which determines the quality of wingko production whether that comes from young coconut or old one from the Genjah variety. In the effort of maintaining the quality of coconut wingko production, a technique for selecting high quality coconut meat in a consistent way with the aid of technology is needed. In this research, an Artificial Intelligence-based digital imaging system for selecting quality coconut meat has been developed. The selection is based on color and texture by utilizing Support Vector Machine (SVM) as classifier and information fusion. The digital image processing uses the combination of Hue, Saturation, Value (HSV) and Gray-Level Co-Occurrence Matrix (GLCM) methods as color and energy feature extractors. Both features are fused to obtain a single feature to accelerate SVM classification as the basis for selection of the coconut meat. By using this system, the selection of quality coconut meat was successful to achieve the accuracy as much as 50%. In this research it was also found that incorrectly labeling gives significant impact to the accuracy of coconut meat selection. Keywords: Artificial Intelligence, coconut meat, digital image processing, information fusion, quality coconut meat selection, SVM.
Item Type: | Thesis (Diploma) |
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Uncontrolled Keywords: | daging kelapa, fusi informasi, Kecerdasan Artifisial, pemilihan daging kelapa bermutu, pengolahan citra digital, SVM. |
Subjects: | A Computer Science > Computer Programming A Computer Science > Artificial Intelligence A Computer Science > Applied Computer Science |
Divisions: | Jurusan Teknologi Informasi > Teknik Informatika |
Depositing User: | Ahmad Alfian Bastami |
Date Deposited: | 25 Dec 2020 14:51 |
Last Modified: | 25 Dec 2020 14:51 |
URI: | http://repota.jti.polinema.ac.id/id/eprint/382 |
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