Model CNN LeNet dalam Rekognisi Angka Tahun pada Prasasti Peninggalan Kerajaan Majapahit

CNN LeNet Model for Year Digit Recognition on Relic Inscriptions of Majapahit Kingdom

Tri Septianto -  Sekolah Tinggi Teknik Surabaya, Indonesia
Endang Setyati -  Sekolah Tinggi Teknik Surabaya, Indonesia
*Joan Santoso -  Sekolah Tinggi Teknik Surabaya, Indonesia
Received: 4 Jun 2018; Published: 31 Jul 2018.
Open Access Copyright (c) 2018 Jurnal Teknologi dan Sistem Komputer
The object of the inscription has a feature that is difficult to recognize because it is generally eroded and faded. This study analyzed the performance of CNN using LeNet model to recognize the object of year digit found on the relic inscriptions of Majapahit Kingdom. Object recognition with LeNet model had a maximum accuracy of 85.08% at 10 epoch in 6069 seconds. This LeNet's performance was better than the VGG as the comparison model with a maximum accuracy of 11.39% at 10 epoch in 40223 seconds.

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Keywords
LeNet recognition performance; inscription digit recognition; CNN performance comparison; VGG recognition performance

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