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All Journal JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Representamen INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Celebes Computer Science Journal Jurnal Teknik Informatika (JUTIF) Patria Artha Journal of Community Jurnal Penelitian Ilmu Sosial dan Eksakta Journal International Inspire Education Technology (JIIET) SABAJAYA Jurnal Pengabdian Kepada Masyarakat International Journal of Multidisciplinary Research of Higher Education (IJMURHICA)
DENGEN, ALVIANUS
Teknik Elektro, Fakultas Teknik, Universitas Teknologi Sulawesi, Indonesia
Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences

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Journal : Jurnal Teknik Informatika (JUTIF)

 1 
IMPLEMENTATION OF EIGENFACE ALGORITHM FOR IDENTIFICATION OF ANOPHELES IN SMARTPHONES Alvianus Dengen
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 1 (2022): JUTIF Volume 3, Number 1, February 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.1.158

Abstract

The development of smartphones as tools used in research provides many benefits in several fields, including education, health, and agriculture. Digital image research developed in mobile apps can help us choose the best decision so that the results are by what has been planned. One of the developments in entomology is entomology research that uses digital imagery. In the dataset activity, researchers used the anopheles’s wings type as much as 22 image data. Fifteen types of Anopheles were used by the researcher with 100 experiments as test data. Image training and identification have the same process, taking pictures from a gallery or directly using the camera from an Android device. Preprocessing step in applications includes 1) converting image pixels to 100x100 pixels, then this pixel size becomes the standard of use in applications. 2) Convert an image to a binary using a threshold algorithm; this event is commonly called the Image Binaryization Process. Images derived from the threshold process are converted into one-dimensional vectors. Training Image and image identification using the Eigenface algorithm. The basic principle of the Eigenface algorithm is to quote the unique information of each image and then compare it to the image in the dataset. Identification with anopheles applications results in a good accuracy value with a success rate of 94.29%, with FMR value = 4.62% and FNMR = 2.78%.
Co-Authors Andu, Cristine Purnamasari Bayarmaa, Tsolmon Budiawan, Budiawan Lista Litta, Lista Qarnila Ridhaniah Rahman Ridwan Adi Setiabudi Saputra, Wahyuddin Tone, K. Tserendorj, Baatar