Penerapan Teknologi CNN Dalam Proses Pendeteksi Kematangan Buah Stroberi

Zahrotul Ilmi Wijayanti
Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan In... 📅 2024 Vol 2, No 3 🔗 DOI: 10.61132/uranus.v2i3.192
Abstract
The process of manually identifying fruits to determine ripe and unripe can affect the production and quality of the food and beverages themselves. The CNN method is able to group images and analyze images based on objects. Therefore, it is necessary to conduct research using the CNN method on the ripeness of strawberries. This study aims to determine the level of maturity of strawberries during harvest time. The accuracy graph shows that the model is not only capable of learning the training data well but can also generalize well to the validation data. In contrast, the validation accuracy graph starts from 0.825 in the 0th epoch and rises consistently until it reaches 0.975 in the 30th epoch. Both charts remained stable above those values throughout the training period. Overall, the development of the CNN model for the detection of strawberry ripeness resulted in excellent performance. The model achieved the lowest loss of 0.0383 and an accuracy as high as 98% on the validation data, demonstrating a strong ability to accurately predict between ripe and unripe strawberries.
Keywords
Strawberry Fruit; Image Processing; CNN (Convolution Neural Network)
How to Cite

Zahrotul Ilmi Wijayanti (2024). Penerapan Teknologi CNN Dalam Proses Pendeteksi Kematangan Buah Stroberi. Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika, 2(3). https://doi.org/10.61132/uranus.v2i3.192

Zahrotul Ilmi Wijayanti, "Penerapan Teknologi CNN Dalam Proses Pendeteksi Kematangan Buah Stroberi," Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika, vol. 2, no. 3, 2024.

Zahrotul Ilmi Wijayanti. "Penerapan Teknologi CNN Dalam Proses Pendeteksi Kematangan Buah Stroberi." Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika, vol. 2, no. 3, 2024.

Zahrotul Ilmi Wijayanti. "Penerapan Teknologi CNN Dalam Proses Pendeteksi Kematangan Buah Stroberi." Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika 2, no. 3 (2024).

Zahrotul Ilmi Wijayanti (2024) 'Penerapan Teknologi CNN Dalam Proses Pendeteksi Kematangan Buah Stroberi', Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika, 2(3). doi: 10.61132/uranus.v2i3.192.

Zahrotul Ilmi Wijayanti. Penerapan Teknologi CNN Dalam Proses Pendeteksi Kematangan Buah Stroberi. Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika. 2024;2(3).

Artikel Terkait

Perancangan Alat Penerjemah Bahasa Isyarat Ke Suara Berbasis Sensor Flex, Sensor Mpu6050, dan Raspberry Pi

Zauqy Launu Hayya; Farady Alif Fiolana; Diah Arie Widhining

Digitalisasi Profil Usaha Siomay Batagor Bogarasa Melalui Perancangan Website Berbasis Odoo

Erika Fitriyani; Sri Bekti Handayani

Apliksi E-Absensi Berbasis Web untuk Efisiensi Rekapitulasi Data Kehadiran di PLN ULP Tanjug Balai

Rahmadani Fitri Panjaitan

Penggunaan Transfer Learning untuk Peningkatan Akurasi Deteksi Penyakit Tanaman Bunga

Enteng Hardiansyah; Lailan Sofinah Haharap; Muhammad Farros Atiqi

High-Accuracy Real-Time Soft Failure Detection in Optical Access Networks Using Hybrid Isolation Forest and One-Class SVM

Egi Rangga Maulana

Analisis Dampak AI terhadap Keterlibatan Politik Digital Pemuda Menggunakan SEM

Ruspandi Ruspandi
Tren Sitasi Jurnal