KLASIFIKASI CITRA DIGITAL UNTUK PENILAIAN MUTU PADA QUALITY CONTROL KUE KASTENGEL MENGGUNAKAN METODE CNN

Ad-Duali, Muhammad Fajrin Aswad (2026) KLASIFIKASI CITRA DIGITAL UNTUK PENILAIAN MUTU PADA QUALITY CONTROL KUE KASTENGEL MENGGUNAKAN METODE CNN. Undergraduate thesis, Universitas Nusantara PGRI Kediri.

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Abstract

Penelitian ini dilatarbelakangi oleh masalah inkonsistensi dan subjektivitas quality control manual pada produksi kue kastengel skala rumahan (home made) yang berpotensi menurunkan kredibilitas usaha. Untuk mengatasi hal tersebut, dikembangkan sistem klasifikasi mutu berbasis web bernama VISKA (Vision Kastengel Analyzer) menggunakan metode Convolutional Neural Network (CNN) yang mampu menilai kelayakan produk secara objektif serta menolak objek asing (Out-of-Distribution). Sistem ini dibangun menggunakan pendekatan waterfall melalui tahapan preprocessing, pelatihan model, dan evaluasi performa. Berdasarkan hasil pengujian pada empat kategori kelas (Grade A, Grade B, Grade C, dan Non Kastengel), konfigurasi arsitektur terbaik dicapai oleh model RGB dengan resolusi 128 x 128 piksel yang menghasilkan akurasi keseluruhan sebesar 99,21%. Hasil evaluasi fungsional dan non-fungsional membuktikan bahwa sistem VISKA memiliki kinerja klasifikasi yang sangat akurat dan berfungsi optimal sesuai kebutuhan lini produksi.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Klasifikasi, Convolutional Neural Network (CNN), Kastengel
Subjects: 100 Mathematics and natural science > 123 Computer science
410 Engineering science > 457 Computer engineering
410 Engineering science > 458 Technical information
410 Engineering science > 459 Computer science
410 Engineering science > 461 Information systems
410 Engineering science > 462 Information technology
410 Engineering science > 463 Software engineering
Divisions: Fakultas Teknik dan Ilmu Komputer > S1-Teknik Informatika
Depositing User: MUHAMMAD FAJRIN ASWAD AD-DUALI
Last Modified: 05 Aug 2026 06:30
URI: http://repository.unpkediri.ac.id/id/eprint/26425

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