Pemanfaatan Canny Edge Detection untuk Pembacaan OMR Survey 7 Kebiasaan Anak Indonesia Hebat

Authors

  • Friendly Friendly Politeknik Negeri Medan
  • Harizahayu Harizahayu Politeknik Negeri Medan
  • Purwa Hasan Putra Politeknik Negeri Medan

DOI:

https://doi.org/10.55123/insologi.v5i1.6705

Keywords:

Canny Edge Detection, OMR, Digital Data Reader

Abstract

The 7 Kebiasaan Anak Indonesia Hebat program is one of the priority program of the Ministry of Primary and Secondary Education of the Republic of Indonesia. It aims to develop students with strong academic ability, good behavior, and strong character. The program is implemented in all primary and secondary schools, and thus large amounts of data must be summarized for monthly reports. Urban schools often use Google Forms or digital applications to record students’ activities, while schools in smaller towns or rural areas still rely on paper forms. Limited access to smartphones and internet connections among parents makes online data collection difficult. Consequently, teachers must manually summarize data using spreadsheet applications, increasing their workload—especially when managing many students. This study proposes the use of Canny Edge Detection to automate data processing from OMR (Optical Mark Recognition) sheets. By scanning or photographing filled OMR sheets, the system can accurately read and convert students’ responses into digital data. This method allows teachers to digitize the reporting process and reduce manual work. Using this method, the accuracy of reading the OMR sheets can reach 81% while the need of informing the parents to fill the form correctly since some tested data shown recall data reached 68%.

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Author Biography

Friendly Friendly, Politeknik Negeri Medan

Teknologi Rekayasa Multimedia Grafis, Politeknik Negeri Medan, Medan, Indonesia

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Published

2026-02-10

How to Cite

Friendly, F., Harizahayu, H., & Purwa Hasan Putra. (2026). Pemanfaatan Canny Edge Detection untuk Pembacaan OMR Survey 7 Kebiasaan Anak Indonesia Hebat. INSOLOGI: Jurnal Sains Dan Teknologi, 5(1), 1–10. https://doi.org/10.55123/insologi.v5i1.6705