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Supervised Learning from Data Mining on Process Data Loggers on Micro-Controllers

Saputra, Adi Dwifana (2023) Supervised Learning from Data Mining on Process Data Loggers on Micro-Controllers. Sinkron : Jurnal dan Penelitian Teknik Informatika.

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Abstract

Abstract: In processing data science, data is needed as input. Sometimes the data
needed is not available in public data, this is where the purpose of this research was
made. The acquisition process is very important to process information into data.
After that, the data is processed to make a decision. Microcontrollers in controlling
conditions, such as temperature, and humidity are very common devices, and many
studies have been carried out. Sometimes discussing it just shows how to serialize
and save it on online platforms, like firebase, tinger.io and many other online
platforms. So that the process of storing data on external or online platforms is an
advantage for platform providers, where platform providers don't need to do
business and get data for free. This is unnoticed by researchers who have produced
microcontroller devices. The many platforms for storing data range from hardware
and software. Some tools are paid or open source. This research uses software that
is open source. Because using open source-based tools will be easy to develop and
for further research purposes. The development of further research by entering the
code into the microcontroller system or what is called an embedded system. Data is
a very valuable asset. Because data is one of the most important components in
processing data science. And better take care of the data logger. This study uses a
microcontroller and ultrasonic distance sensor and potentiometer. The method from
the results of the logger (dataset) is used for classification using the support vector
machine and decision tree algorithms. Accuracy with the support vector machine
reaches 97% and the decision tree reaches 100% accuracy.

Keywords: Arduino; Data Logger; Data Science; Distance Sensor; Micro-
Controller Device; Potentiometer;

Item Type: Article
Subjects: -|- SUBJEK PRADITA -|- > Fakultas Sains dan Teknologi > Magister Teknologi Informasi
Depositing User: Pradita Librarian
Date Deposited: 01 Nov 2024 04:22
Last Modified: 01 Nov 2024 04:22
URI: https://repository.pradita.ac.id/id/eprint/468

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