An End-to-End Optical Character Recognition Pipeline for Indonesian Identity Card

Chandra, Andreas; Stefanus, Ruben

doi:10.1109/icoict52021.2021.9527436

Cited by 4 publications

(1 citation statement)

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“…User has trouble to verify identity card, failed face verification, encounter a server time out and request to fix the application. The developer's team can enhance the verify identity feature with several technique such as retinex algorithm [32], [33] and an end-to-end optical character recognition pipeline [34] to improve service quality of their e-government platform. Retinex Algorithms is built for Chinese citizens with 96.50% recognition accuracy of the identity card.…”

Section: Digital Korlantas Applicationmentioning

confidence: 99%

Evaluation of Indonesia’s police public service platforms through sentiment and thematic analysis

Melani Puspasari,

Zharif Mustaqim,

Tri Utami

et al. 2024

IJ-AI

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The Indonesian national police (Polri) offer public services through mobile apps: Digital korlantas polri (DigiKorlantas) and samsat digital nasional (SIGNAL). Sentiment analysis gauges public perceptions, serving as a basis for e-government evaluation using user ratings and comments from app stores. Keyword relevance is assessed via feature extraction and Naïve Bayes classification. Thematic analysis is implemented using N-grams methods to identify the factors affecting the effectiveness based on user experiences. The accuracy of the model reaches 81.09% where it indicates a high performance. DigiKorlantas acquires slightly more negative reviews in comparation with positive reviews which are 51% and 49% respectively. In contrast, positive sentiment is dominant on SIGNAL which reach 58%, compared with negative sentiment that in 42%. N-grams reveal similar review patterns for both apps. Some of the solutions are Korlantas Polri should enhance the verification functionality with several techniques such as retinex algorithms or optical character recognition pipeline and increase the capacity of supporting server then releasing an updated version of application to address errors or bugs. This analysis can be alternative evaluation by the Polri to measure the success of the application and find out the continuous improvement of the process and the system.

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Section: Digital Korlantas Applicationmentioning

confidence: 99%