Pemanfaatan Yolo untuk Pengenalan Kesegaran Buah Mangga
DOI:
https://doi.org/10.30736/jti.v7i1.747Keywords:
mangga, identifikasi, yoloAbstract
Buah merupakan salah satu kebutuhan selain makanan pokok, tidak hanya dikalangan tertentu saja, tapi disemua kalangan. Indonesia menjadi penghasil mangga terbesar keempat di dunia. Sehingga diperlukan suatu sistem yang dapat secara otomatis mengidentifikasi kebusukan dan kesegaran dari 3 jenis buah Mangga menggunakan pengolahan gambar, memperbaiki teknik penyortiran dan penilaian yang tidak ilmiah yang dilakukan secara manual, sehingga bisa meningkatkan kualitas jual mangga dengan menggunakan algoritma YOLO. Penelitian ini menggunakan 3 jenis mangga yang terdiri dari mangga golek, gedong, dan manalagi, dan melakukan uji coba dengan beberapa sekenario yaitu semua gambar mangga segar, semua gambar mangga busuk, dan semua gambar mangga segar dan busuk. Hasil dari penelitian menunjukkan beberapa uji coba yang dilakukan, maka didapatkan nilai rata-rata precision, recall, dan f1- score Skenario pertama yaitu mangga segar semua didapatkan tingkat akurasi 80%, precision 82%, dan recall 87%, didapatkan F1-score 84%. Kemudian sknario yang kedua yaitu mangga busuk semua didapatkan tingkat akurasi 76%, precision 76%, dan recall 87%, didapatkan F1-score 81%. Dan yang ketiga yaitu mangga segar dan busuk, didapatkan tingkat akurasi 73%, precision 66%, dan recall 81%, didapatkan F1-score 73%. dapat disimpulkan bahwa hasil penelitian ini masih tergolong underfitting. Hal ini dikarenakan masih butuh banyak dataset yang lebih banyak dan variannya yang mempunyai ciri-ciri yang ada kemiripan masing-masing kelasnya.Downloads
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