Open AccessClassification Of Alcohol Type Using Gas Sensor And K-Nearest Neighbor
Author(s) -
Munaf Ismail,
Sri Arttini Dwi Prasetyowati
Publication year - 2022
Publication title -
jurnal nasional teknik elektro
Language(s) - English
Resource type - Journals
eISSN - 2407-7267
pISSN - 2302-2949
DOI - 10.25077/jnte.v11n1.989.2022
Subject(s) - isopropyl alcohol , alcohol , methanol , ethanol , block (permutation group theory) , block diagram , microcontroller , software , process (computing) , k nearest neighbors algorithm , computer science , chemistry , analytical chemistry (journal) , mathematics , artificial intelligence , chromatography , engineering , computer hardware , operating system , organic chemistry , electrical engineering , combinatorics
Ethanol, isopropyl and methanol belong to the same alcohol group. The latter is commonly used as an industrial solvent, not for personal consumption. Many traditional alcoholic drink sellers often mix alcoholic beverages, which are commonly called as oplosan, this mixed drink is very dangerous for human if it contains methanol. Based on this problem, it is necessary to make a measuring device for the alcohol content in the liquid to classify the alcohol type. The design of this gas sensor-based alcohol classification system and method consists of a series of hardware and software applications. The block diagram of the alcohol classification system measures the ethanol and methanol substances in each alcoholic drink using the MQ3 gas sensor and WeMos as a data acquisition device and microcontroller. The computer was used to process the acquisition data from the gas sensor being used then calculates the K-Nearest Neighbor (K-NN) to obtain the prediction results. The K-NN system testing consists of testing the effect of the K value and testing its accuracy. The result of testing the effect of the K value produces 100% optimum accuracy at the values namely K=1, K=3, K=5, K=10 and 55% on K=20.