Basheer Al-Sadawi
University of Kufa

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Journal : Indonesian Journal of Electrical Engineering and Computer Science

Multi-objective attendance and management information system using computer application in industry strip Ahmed Hazim Alhilali; Nabeel Salih Ali; Mohammed Falih Kadhim; Basheer Al-Sadawi; Haider Alsharqi
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp371-381

Abstract

Information technology has played a vital factor in a competitive advantage for various business firms recently. Hence, catching up Investment of IT in most of the traditional industries for competitiveness purposes due to the relationship between organizational performance and IT use. In this study, attendanceand management information system (AMIS) was presented in the industry field based on multi-modules. Modules are management information, time- scheduling and attendance, and employee self- service module. The system used VB.NET environment for programming perspective as well MS SQL server for database storage. The system is secure and robust recordkeeping, keep employee up to date via self- service access, easy to use (simplified) and powerful time and attendance, active work schedules to make an employee happy and keep workers in the loop, as well, review and exporting different reports for staff manager, supervisor, and employee such as absence, vacation, time-off, employee wages, and etc.
Corpus-based technique for improving Arabic OCR system Ahmed Hussain Aliwy; Basheer Al-Sadawi
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 1: January 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i1.pp233-241

Abstract

An optical character recognition (OCR) refers to a process of converting the text document images into editable and searchable text. OCR process poses several challenges in particular in the Arabic language due to it has caused a high percentage of errors. In this paper, a method, to improve the outputs of the Arabic Optical character recognition (AOCR) Systems is suggested based on a statistical language model built from the available huge corpora. This method includes detecting and correcting non-word and real words error according to the context of the word in the sentence. The results show that the percentage of improvement in the results is up to (98%) as a new accuracy for AOCR output.