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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Record and Library Journal E-Dimas: Jurnal Pengabdian kepada Masyarakat AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Prosiding Seminar Nasional Sains dan Teknologi Terapan IJEEIT : International Journal of Electrical Engineering and Information Technology Jurnal Teknologi Informasi dan Multimedia Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Informatika Teknologi dan Sains (Jinteks) IJCOSIN : Indonesian Journal of Community Service and Innovation Submit : Jurnal Ilmiah Teknologi Informasi dan Sains
Yesy Diah Rosita
Faculty Of Informatics, Institut Teknologi Telkom Purwokerto, Indonesia
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : Record and Library Journal

 1 
Potholes Road Classification by Shape and Area Features Rosita, Yesy Diah; Sugianto, Sugianto
Record and Library Journal Vol 5, No 1 (2019)
Publisher : D3 Teknisi Perpustakaan Fakultas Vokasi Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (553.423 KB) | DOI: 10.20473/rlj.V5-I1.2019.72-79

Abstract

Background of the study: Generally, during the rainy season, many potholes asphalt road are found. The high rainfall results in the fragile contour of the asphalt road and triggers a traffic accident. In the last decade, the development of potholes asphalt road detection has various method approaches.Purpose:  The research used precision to get a performance of the system.Method: In this study, the development system can classify potholes asphalt road by a simple algorithm. It also considers the time and space complexity.Findings: The algorithms as possible and only uses the handy-camera device to capture data which the level of performance as good as the results of previous research. Capturing data is also various distances with 450 point angles. For classification steps, the system applied two main features, area and shape feature of the object. The used parameters for these features are the length of major and minor axis object. It used to calculate area and eccentricity values.Conclusion: In conclusion, the experiment result reaches 81.696% of the 1125 frames used.
LSTM NETWORK AND OCR PERFORMANCE FOR CLASSIFICATION OF DECIMAL DEWEY CLASSIFICATION CODE Rosita, Yesy Diah; Sukmaningtyas, Yanuarini Nur
Record and Library Journal Vol 6, No 1 (2020)
Publisher : D3 Perpustakaan Fakultas Vokasi Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/rlj.V6-I1.2020.45-56

Abstract

Background of the study: Giving book code by a librarian in accordance with the Decimal Dewey Classification system aims to facilitate the search for books on the shelf precisely and quickly. Purpose: The first step in giving code to determine the class of books is the principal division which has 10 classes.Method: This study proposed Optical Character Recognition to read the title text on the book cover, preprocessing the text, and classifying it by Long Short-Term Memory Neural Network. Findings: In general, a librarian labeled a book by reading the book title on the book cover and doing book class matching with the book guide of DDC. Automatically, the task requires time increasingly. We tried to classify the text without OCR and utilize OCR which functions to convert the text in images into text that is editable. BY the experimental result, the level of classification accuracy without utilizing OCR is higher than using OCR. Conclusion: The magnitude of the accuracy is 88.57% and 74.28% respectively. However, the participation of OCR in this classification is quite efficient enough to assist a beginner librarian to overcome this problem because the accuracy difference is less than 15%.
Co-Authors Abdul Khamid Adi Surya Jinggo Pratama Aditya Dwi Putro Wicaksono Andi Prademon Yunus Andi Saputra, Wahyu Ardiantoro, Luki Aulia Desy Nur Utomo Billy Coster Junior Daniel Happy Putra Dany Candra Febrianto Erita Devy Prastika Fajar Indra Kurniawan Gatra Cahya Ramadhan Gugut Indartak Hanum, Dinarta Hastungkoro, Arya Widya Jayanti, Rani Luki Ardiantoro M.Irfan Hanafi Maslikhatul Aini Maulana Ardillan Arendra Mimin Fatchiyatur Rohmah Mohammad Joevan Handyyansyah Nur Ainiyah Pratama Bagus W Ronny Makhfuddin Akbar Ronny Makkhfuddin Akbar Soffa Zahara Sugianto Sugianto Yanuarini Nur Sukmaningtyas Yeni Susanti Yusril Adil Hidayat