DETEKSI TEMU RUAS DAUN SIRIH MENGGUNAKAN ALGORITMA THINNING

Authors

  • Tia Tanjung Sistem Informasi Universitas BSI Bandung
  • Kadinar Novel. Sistem Informasi STMIK Bani Saleh Bekasi

DOI:

https://doi.org/10.33480/pilar.v13i1.160

Keywords:

algorithms thinning, image processing, detection

Abstract

Society is still a lot need the best solution to select an appropriate treatment to address a variety of perceived grievances, from medical treatment to the treatment of non-medical or often called traditional medicine, betel leaves as one of the plants that are useful to be a cure for certain diseases and betel leaves public trust to be used as a treatment appointment is betel leaf segments. Processing betel leaves on a large scale is needed to determine the ease of retrieval of betel leaf segments. The purpose of the research is to utilize image processing algorithms thinning. The method used consists of betel leaf image acquisition, image changes to a grayscale, edge detection comprising Prewitt, Robert, Sobel and thinning. Furthermore, the analysis of the results of research showing the most thinning algorithm is good to get that appointment betel segment.

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Author Biography

Tia Tanjung, Sistem Informasi Universitas BSI Bandung

Tia Tanjung. Pati, 11 Juni 1991. D3 Manajemen Informatika Akademi Bina Sarana Informatika “BSI Yogyakarta”, S1 Sistem Informasi “Universitas BSI Bandung”, dan sedang dalam masa studi Magister Ilmu Komputer STMIK Nusa Mandiri Jakarta. Saat ini  bekerja sebagai Dosen di Universitas BSI Bandung. Bidang keilmuan yang sedang ditekuni adalah software engineering. Buku yang pernah dipublish dan digunakan sebagai bahan bacaan oleh satu kegiatan adalah “Himasi Inspirasiku”. Kegiatan dalam hal mengajar adalah satu amanah yang tak pernah lelah untuk dijadikan semangat di langkah kedepan.

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Published

2018-03-15

How to Cite

Tanjung, T., & Novel., K. (2018). DETEKSI TEMU RUAS DAUN SIRIH MENGGUNAKAN ALGORITMA THINNING. Jurnal Pilar Nusa Mandiri, 13(1), 151–155. https://doi.org/10.33480/pilar.v13i1.160