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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Nazhif Afkar Hanif
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Rancangan Sistem Klasifikasi Kesuburan Tanah pada Tanaman Pangan berdasarkan pH dan Kelembapan berbasis Arduino Nano menggunakan Metode K-NN dan Aplikasi Android Nazhif Afkar Hanif; Mochammad Hannats Hanafi Ichsan; Agung Setia Budi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 8 (2022): Agustus 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Soil is one of the planting media. The soil has several main factors for plant growth, including moisture and soil acidity.The level of soil moisture and soil acidity can determine the fertility of the soil and also suitable crops for planting on the soil.Some of the existing tools can mostly only determine the level of soil moisture or acidity, without telling the level of soil fertility and also the plants that are suitable for planting on the soil.From these problems, I conducted research to create a system that can detect the level of soil fertility and suitable plants on the soil based on the level of humidity and acidity of the soil.This system uses two kinds of sensors, namely a soil moisture sensor and also a soil pH sensor.These two sensors are connected to an Arduino Nano microcontroller that is operated using an Android application.The results of this study are in the form of a tool that can detect the level of soil fertility and also the type of plants that are suitable on the soil based on the level of humidity and acidity and an Android application that is connected to the tool using Bluetooth as a medium interface on this system.The grouping of soil and plants is carried out using the k-Nearest Neighbors (k-NN) method.In this study, the selection of the classification method used k-NN because the data used was secondary data and the purpose of this method was to classify objects based on attributes and test data so that it was suitable for my research that have 90% accuration..
Co-Authors Agung Setia Budi Mochammad Hannats Hanafi Ichsan