Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Askia Sani
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Kelompok Penyakit Tanaman Apel Menggunakan Metode K-Means Berbasis Web Askia Sani; Nurul Hidayat; Ratih Kartika Dewi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 8 (2018): Agustus 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1021.456 KB)

Abstract

The state of a good apple plant can be detected by identifying the disease in apples. One method to detect apple disease can be done with K-Means. Application of apple plant disease grouping using this android based K-Means method can make it easier to detect the apple plant penyakti, this application is based on android so that users can easily run this application anywhere and anytime with the user's mobile phone. This is where the discussion is about building a detection sistem application that users can use to detect the presence of pests in apple plantations. Application of diganosa sistem of apple plant disease can display diagnosis result quickly and precisely based on the symptoms entered by user. To make the diagnosis become very valid, then the data of symptoms included into decision support sistem is a symptom data, must be complete meaning of symptoms that can lead to a disease must be entered in full, because conclusion of diagnosis result (percentage) shown counted Automatically by the sistem using K-Means.
Co-Authors Nurul Hidayat Ratih Kartika Dewi