Article Per Year (5 Year)
p-Index From 2020 - 2025
0.751
P-Index
This Author published in this journals
All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) SENTIA 2017 Petir Jurnal Informatika Polinema (JIP)
Dyah Ayu Irawati
Unknown Affiliation
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Library & Information Science

Published : 17 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Petir

 1 
Optimalisasi Image Thresholding pada Optical Character Recognition Pada Sistem Digitalisasi dan Pencarian Dokumen Ridwan Rismanto; Arief Prasetyo; Dyah Ayu Irawati
PETIR Vol 13 No 1 (2020): PETIR (Jurnal Pengkajian Dan Penerapan Teknik Informatika)
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (717.378 KB) | DOI: 10.33322/petir.v13i1.659

Abstract

The administration activity in an institute is largerly done by using a paper based mailing and document as a media. Therefore, a great effort needs to be performed in the case of management and archiving, in the form of providing storage space through the categorizing system. Digitalization of document by scanning it into a digital image is one of the solution to reduce the effort to perform the work of archiving and categorizing such document. It also provide searching feature in the form of metadata, that is manually written during the digitalization process. The metadata can contains the title of document, summary, or category. The needs to manually input this metadata can be solved by utilizing Optical Character Recognition (OCR) that converts any text in the document into readable text storing in the database system. This research focused on the implementation of the OCR system to extract text in the scanned document image and performing optimization of the pre-processing stage which is Image Thresholding. The aim of the optimization is to increase OCR accuracy by tuning threshold value of given value sets, and resulting 0.6 as the best thresholding value. Experiment performed by processing text extraction towards several scanned document and achieving accuration rate of 92.568%.
Co-Authors Adithya Gilang Maulana Aisy Muhammad R Anugrah Nur Rahmanto Ari Mahardika Ahmad Nafis Arief Prasetyo Astiningrum, Mungki Bagus Rahmadhian Budi Harijanto, Budi Deddy Kusbianto P Deddy Kusbianto Purwoko A Ekojono Ekojono Elistya Rahma Dinda Faisal Rahutomo Fitri Maharany Harry Yanuar Herlina Jayadianti Herlina Prastiwi Luqman Affandi Prastiwi, Herlina Rawansyah Rawansyah Ridwan Rismanto Ridwan Rismanto Riza Ivanadi Padeka Putri Rosiani, Ulla Delfana Rudy Ariyanto Sari Anggraeni Sulton Ginanjar Abdullah Susi Susanti Vandi Chamdika Yanu Ramdhani Saputra Yuri Ariyanto