1Jurusan Teknik Elektro, Universitas Borneo Tarakan, Jl. Amal Lama No.1 Tarakan, Indonesia 77123, Indonesia
2Program Studi Teknik Elektro, Fakultas Teknik, Universitas Borneo Tarakan, Tarakan, Indonesia 77123, Indonesia
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@article{JTSISKOM14529, author = {Sumardi Sumardi and Syahfrizal Tahcfulloh}, title = {Metode k-means clustering dan morfologi berbasis computer vision dan analisis regresi untuk aplikasi sistem grading udang Vaname}, journal = {Jurnal Teknologi dan Sistem Komputer}, volume = {11}, number = {1}, year = {2024}, keywords = {analisa regresi;k-means clustering;morfologi;sistem grading udang}, abstract = {Penentuan mutu udang secara konvensional menggunakan visual mata memiliki beberapa kelemahan, salah satunya adalah tingkat persepsi manusia yang berbeda-beda. Solusi yang ditawarkan adalah menggunakan teknologi computer vision dalam menentukan ukuran udang berdasarkan citra yang ditangkap kamera. Penelitian ini bertujuan untuk menerapkan kombinasi metode dari pengelompokan k-rata-rata dan morfologi untuk menentukan ukuran udang Vaname yaitu berdasarkan perbandingan area dalam dimensi piksel dari hasil olah citra dengan teknologi computer vision terhadap massa dalam dimensi gram. Analisis regresi digunakan untuk mendapatkan persamaan yang mengkonversi antar nilai piksel tersebut ke dalam massa udang. Keefektifan kombinasi metode ini dibandingkan dengan hanya menggunakan metode pengelompokkan k-rata-rata dan nilai ambang. Hasil evaluasi dari metode yang diusulkan menunjukkan bahwa nilai RMSE yang diperoleh sebesar 0,68 yang lebih baik dari dua metode terdahulu berturut-turut adalah 0,73 dan 2,89. Sementara akurasi sistemnya untuk pengukuran massa diperoleh sebesar 93,64%, akurasi ukuran/besar sebesar 93,37% dan akurasi klaster dari ukuran sebesar 95,45%.}, issn = {2338-0403}, doi = {10.14710/jtsiskom.2023.14529}, url = {https://jtsiskom.undip.ac.id/article/view/14529} }
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