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In the process of making ceramic tiles, there is a combustion process using a kiln manufacture or oven. To ensure the combustion process goes well, 39 parameters are monitored on the kiln engine which must be monitored manually based on the data generated by the image on the kiln engine. The process of monitoring these parameters is ineffective due to human error or negligence and other human traits that result in losses for the company. Therefore, a system is needed to store the parameter data of the ceramic tile combustion engine which can be stored in a database. After analyzing the kiln, the sensor recorder that displays parameter data can be accessed via a LAN (Local Area Network), but the data generated is in the form of an image, not in the form of alphanumeric digital data. The image data obtained need to be translated into alphanumeric data as a data source. Through the introduction of optical character recognition (OCR) with the template matching method, the image is converted into alphanumeric data so that it can be stored in a database. From the results of this study, the prototype system made obtained an accuracy of 100.00% for the conversion of image data to alphanumeric data.


Digital Image Optical Character Recognition Numerical Data Kiln Manufacture

Article Details

How to Cite
A. H. Hananto, E. Novalia, and G. Brotosaputro, “Changing Data Image Into Numeric Data on Kiln Manufacture Machinery Use Optical Character Recognition (OCR)”, bit-cs, vol. 3, no. 2, pp. 53-58, Jul. 2022.


  1. Arnofiandi, M. S. (2020) ‘Rancang Bangun Tungku Pemanas Dalam Proses Metalurgi Serbuk’, Pembelajaran Olah Vokal di Prodi Seni Pertunjukan Universitas Tanjungpura Pontianak, 28(2), pp. 1–43.
  2. Chaudhuri, A., Mandaviya, K., Badelia, P., and Ghosh, Soumya K. (2017) Optical character recognition systems, Studies in Fuzziness and Soft Computing.
  3. Putra, D. (2010) ‘Pengolahan Citra Digital’. Yogyakarta: C.V ANDI OFFSET (Penerbit Andi), p. 420.
  4. Hossain, M. A. and Afrin, S. (2019) ‘Optical Character Recognition based on Template Matching’, Global Journal of Computer Science and Technology, 19(2)
  5. Andono, P. N., Sutojo, T. and Muljono (2017) Pengolahan Citra Digital. Yogyakarta: PENERBIT ANDI.
  6. NUNAMAKER, B. BUKHARI, S., BORTH, D. and DENGEL, A. (2016) ‘A TESSERACT-BASED OCR FRAMEWORK FOR HISTORICAL DOCUMENTS LACKING GROUND-TRUTH TEXT German Research Center for Artifical Intelligence (DFKI) Kaiserslautern , Germany Univeristy of Kaiserslautern , Gemany’, IEEE International Conference on Image Processing (ICIP), pp.