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All Journal Jurnal Ilmiah Informatika Komputer Jurnal Ilmiah Teknologi dan Rekayasa Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal Ilmiah Matrik Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB)
Dessy Tri Anggraeni
Universitas Gunadarma
Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Other

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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
STEEL BOX GIRDER BRIDGE COMPONENT TRACEABILITY SYSTEM USING TREE STRUCTURE DIAGRAM AT PT BUKAKA TEKNIK UTAMA Condro Wibawa; Metty Mustikasari; Dessy Tri Anggraeni
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 1 (2023): JUTIF Volume 4, Number 1, February 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.1.662

Abstract

The International Organization for Standardization (ISO) through ISO 9001:2015requires every product to have product traceability. In response to these challenges, PT Bukaka Teknik Utama developes the Traceability System in the Steel Box Girder Bridge products. Traceability System built by adopting Tree Structure Diagram Concept to describe production system process currently runs. The production process start from identify raw material, cutting process, sub-assembly process, and assembly process. This concept is then translated into Relational Database by applying Parent-Child Concept. The result of this Traceability System is the system able to issue a list of product traceability including raw material information, sub-contractor/employee who work on them, etc, quickly and accurately. System testing was carried out using the black box method, where of the 37 items tested all functioned properly. Tests were also carried out to determine the accuracy and speed of the system compared to the manual method. Of the 10 tests carried out, the system traceability is exactly the same as the manual method with an average processing time of 3 seconds, compared to the manual method, which is 97.6 seconds.
COMPARISON OF IMAGE SEGMENTATION METHOD IN IMAGE CHARACTER EXTRACTION PREPROCESSING USING OPTICAL CHARACTER RECOGINITON Condro Wibawa; Dessy Tri Anggraeni
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 3 (2023): JUTIF Volume 4, Number 3, June 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.3.956

Abstract

Today, there are many documents in the form of digital images obtained from various sources which must be able to be processed by a computer automatically. One of the document image processing is text feature extraction using OCR (Optical Character Recognition) technology. However, in many cases OCR technology are unable to read text characters in digital images accurately. This could be due to several factor such as poor image quality or noise. In order to get accurate result, the image must be in a good quality, so that digital image need to be preprocessed. The image preprocessing method used in this study are Otsu Thressholding Binarization, Niblack, and Sauvola methods. While the OCR technology used to extract the character is Tesseract library in Python. The test results show that direct text extraction from the original image gives better results with a character match rate average of 77.27%. Meanwhile, the match rate using the Otsu Thressholding method was 70.27%, the Sauvola method was 69.67%, and the Niblack method was only 35.72%. However, in some cases in this research the Sauvola and Otsu methods give better results.
Co-Authors Ahmad Maulana Condro Wibawa Khalidah Khalidah Metty Mustikasari Metty Mustikasari Qomariyah Qomariyah Rafly Alamsyah Setia Wirawan Vinna Mariska Wijaya Kusuma