cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Rizal Furqan Ramadhan
Contact Email
admin@rizaniamedia.com
Phone
+6285257563813
Journal Mail Official
admin@rizaniamedia.com
Editorial Address
RT 10 RW 04 Desa Pucanganak Kec.Tugu Kab. Trenggalek
Location
Kab. trenggalek,
Jawa timur
INDONESIA
Jurnal Ilmiah Informatika dan Komputer
Published by CV.RIZANIA MEDIA PRATAMA
ISSN : -     EISSN : 30474752     DOI : https://doi.crossref.org/10.69533
Core Subject : Science,
Computer Science & IT
INFORMATECH : Jurnal Ilmiah Informatika dan Komputer (E-ISSN : 3047-4752) merupakan Jurnal nasional dengan akses terbuka yang menerbitkan artikel hasil penelitian di bidang Teknik Informatika dan Ilmu Komputer. Ruang Lingkup Jurnal meliputi Kecerdasan Buatan (Artificial Intellegence), Sistem Informasi, Robotika, Jaringan Komputer, Pengolahan Citra (Image Processing), Aplikasi Mobile, Data Mining dan bidang ilmu informatika lainnya. Jurnal INFORMATECH dikelola dan dipublikasikan oleh Rumah Jurnal RIZANIA MEDIA PRATAMA. Jurnal ini diterbitkan sebagai sarana dan wadah para dosen, ilmuan, peneliti maupun pakar bidang Teknik Informatika dan Ilmu Komputer mempublikasikan hasil-hasil penelitiannya untuk menunjang Tugas dan Program Tri Dharma Perguruan Tinggi secara Umum. Jurnal INFORMATECH terbit dua kali dalam setahun pada bulan Juni dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 61 Documents
 3   4   5   6   7 
Implementation of Edge Detection Using the Sobel Operator on Papaya Leaf Images Yuda Apriansyah; Khairi, Nouval; Haikal Habibi Siregar; Supiyandi; Aidil Halim Lubis
Jurnal Ilmiah Informatika dan Komputer Vol. 2 No. 2 (2025): Desember 2025
Publisher : CV.RIZANIA MEDIA PRATAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69533/ma9w7b36

Abstract

Recent advances in digital image processing and computer vision have enhanced feature extraction techniques for plant identification based on leaf morphology. Edge detection is a fundamental operation that highlights intensity discontinuities corresponding to object boundaries. This study implements the Sobel operator to perform edge detection on tropical leaf images using an experimental–computational approach. The workflow involves grayscale conversion, horizontal and vertical Sobel filtering, and gradient magnitude computation implemented in Python using the OpenCV library. Experimental evaluation demonstrates that the Sobel operator effectively delineates primary leaf contours and preserves morphological consistency, despite reduced performance under non-uniform illumination and noisy conditions. These results confirm that the Sobel operator remains a reliable preprocessing technique for leaf-based feature extraction and classification, offering a computationally efficient baseline for future integration with machine learning-based plant recognition systems.

Page 7 of 7 | Total Record : 61

 3   4   5   6   7 

Filter by Year

2024 2025


Reset
Filter By Issues
All Issue Vol. 2 No. 2 (2025): Desember 2025 Vol. 2 No. 1 (2025): June 2025 Vol. 1 No. 2 (2024): Desember 2024 Vol. 1 No. 1 (2024): Juni 2024