RECOGNITION OF REALTIME BASED PRIMITIVE GEOMETRY OBJECTS USING PERCEPTRON NETWORK

  • Cut Lika Mestika Sandy (1) Universitas Islam Kebangsaan Indonesia
  • Taufik Ismail Simanjuntak (2) Universitas Tjut Nyak Dhien
  • Ajulio Padly Sembiring (3) Politeknik Negeri Medan
  • Reyhan Achmad Rizal (4) Universitas Prima Indonesia
  • Ona Rizal Fahmi (5*) Universitas Malikussaleh

  • (*) Corresponding Author
Keywords: Primitive Geometry, Real Time, Perceptron.

Abstract

The purpose of this study is to analyze the perceptron model on pattern recognition of primitive geometric objects in real time based on video images. The samples used in this study were cubes, prisms, tubes and balls. The system was built using the Delphi 7 programming language with pre-processing stages system training includes the process of calculating matrix values from the original image, then proceed with the grayscale and edge detection processes using convolution with a kernel, namely the sobel operator and then the matrix results from the edge detection process are transformed using a perceptron network to obtain energy from the image of the object, then the resulting energy The transformation is stored in the database as a system test reference pattern recognition energy. Measurement of system performance evaluation in this study uses two parameters, namely detection rate and false positive rate. The recognition rate of primitive geometric objects using the perceptron network model in this study reaches 60.00% to 80.00%. The detection rate percentage shows that this model can be used as a supporting approach for the recognition of geometric objects in video.

References

Agriyanto, Sayudi, Iwan Setiawan, and Agus Susanta. 2021. “Representasi Spasial Siswa Pada Materi Geometri Ruang Selama Pembelajaran Matematika Realistik Berbasis Etnomatematika Bengkulu.” Jurnal Pendidikan Matematika Raflesia 06(02):1–14.

Butar-Butar, Juli Loisiana, Ferdinand Sinuhaji, Agus Susanto Ginting, and Rafael Abadiken Sitepu. 2022. “Penggunaan Aplikasi Geogebra Sebagai Media Pembelajaran Geometri Di SMP Negeri 1 Berastagi.” Jurnal Pengabdian Masyarakat Bestari 1(6):401–8. doi: 10.55927/jpmb.v1i6.1097.

Devi Eka Wardani Meganingtyas. 2021. “Pemanfaatan Software Cabri, GeoGebra, Dan SketchUp Sebagai Media Visualisasi Konsep Matematika Pada Materi Geometri Ruang.” Jurnal Riset Pendidikan Matematika Jakarta 3(1):67–75. doi: 10.21009/jrpmj.v3i1.20122.

Ikashaum, Fertilia, Juitaning Mustika, Endah Wulantina, and Edo Dwi Cahyo. 2021. “Analisis Kesalahan Representasi Simbolik Mahasiswa Pada Soal Geometri Analitik Bidang.” Al-Khwarizmi : Jurnal Pendidikan Matematika Dan Ilmu Pengetahuan Alam 9(1):57–68. doi: 10.24256/jpmipa.v9i1.1701.

Jelatu, Silfanus, Maria Lim, and Maria Yasinta Ngoe. 2019. “Pengenalan Bentuk Geometri Bagi Anak Usia Dini Dan Sekolah Dasar Kelas Rendah Melalui Origami.” Jurnal Pengabdian Pada Masyarakat 4(2):195–202. doi: 10.30653/002.201942.134.

Joko Suratno, Ida Kurnia Waliyanti. 2022. “PEMBUATAN ORNAMEN GEOMETRIS DENGAN SOFTWARE GEOMETRI INTERAKTIF.” Jurnal Pendidikan Guru Matematika 2(3):12–26.

Mega Teguh Budiarto, Rudianto Artiono. 2019. “Dalam Pembelajarannya.” J U M A D I K A II(1):1–13.

Musthofa, Muhammad Ulinnuha, Zufida Kharirotul Umma, and Anik Nur Handayani. 2017. “Analisis Jaringan Saraf Tiruan Model Perceptron Pada Pengenalan Pola Pulau Di Indonesia.” Jurnal Ilmiah Teknologi Informasi Asia 11(1):89. doi: 10.32815/jitika.v11i1.56.

Nur’aini, Indah Linda, Erwin Harahap, Farid H. Badruzzaman, and Deni Darmawan. 2017. “Pembelajaran Matematika Geometri Secara Realistis Dengan GeoGebra.” Matematika 16(2):1–6. doi: 10.29313/jmtm.v16i2.3900.

Nurjanah, Nurjanah, and Anggi Juliana. 2020. “Hambatan Didaktis Siswa SMP Dalam Penyelesaian Masalah Geometri Berdasarkan Kemampuan Persepsi Ruang.” Kreano, Jurnal Matematika Kreatif-Inovatif 11(2):236–44. doi: 10.15294/kreano.v11i2.26752.

Purba, Depanri, Saniman Saniman, and Ardianto Pranata. 2022. “Implementasi Perceptron Untuk Mendiagnosa Kerusakan Mesin Fotocopy.” Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) 1(4):314. doi: 10.53513/jursi.v1i4.5292.

Ramadhani, Irfan, Selly Handik Pratiwi, and Anik Nur Handayani. 2017. “Analisis Jaringan Saraf Tiruan Pengenalan Pola Huruf Hiragana Dengan Model Jaringan Perceptron.” Jurnal Ilmiah Teknologi Informasi Asia 11(1):45. doi: 10.32815/jitika.v11i1.41.

Rizal, Reyhan Achmad, Nurlela Octavia Purba, Lidya Aprilla Siregar, Kristina Sinaga, and Nur Azizah. 2020. “Analysis of Tuberculosis (TB) on X-Ray Image Using SURF Feature Extraction and the K-Nearest Neighbor (KNN) Classification Method.” Jaict 5(2):9. doi: 10.32497/jaict.v5i2.1979.

Rizal, Reyhan Achmad, Mario Susanto, and Andy Chandra. 2020. “Classification Of Borax Content In Tomato Sauce Through Images Using GLCM.” SinkrOn 4(2):6. doi: 10.33395/sinkron.v4i2.10508.

Wulandari, Tia Ayu, and Naufal Ishartono. 2022. “Analisis Kemampuan Representasi Matematika Siswa SMA Dalam Menyelesaikan Soal Geometri Berdasarkan Level Berpikir Van Hiele.” JNPM (Jurnal Nasional Pendidikan Matematika) 6(1):97. doi: 10.33603/jnpm.v6i1.5330.

Published
2023-03-03
How to Cite
Sandy, C., Simanjuntak, T., Sembiring, A., Rizal, R., & Fahmi, O. (2023). RECOGNITION OF REALTIME BASED PRIMITIVE GEOMETRY OBJECTS USING PERCEPTRON NETWORK. Jurnal Techno Nusa Mandiri, 20(1), 1 - 7. https://doi.org/10.33480/techno.v20i1.4104
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