Design Design the temperature and humidity classification of the workspace by using a decision tree model.
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Nov 3, 2020
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Abstract
Design the temperature and humidity classification of the workspace by using a decision tree model. Based on the standard table of technical planning procedures for energy conservation in buildings, the optimal comfortable temperature is in the range of 22.8 oC - 25.8 oC with a threshold of 28 oC and humidity of 70%. By utilizing the decision tree classifier, the temperature and humidity of the room detected by the DHT11 sensor are classified based on a model that has been created using Raspberry Pi 3 and the node red. This research was carried out in the ATMI Industrial Polytechnic computer laboratory which is also used as an applied research laboratory in collaboration with industry in the field of automation software development. This research succeeded in making a classification tool for temperature and humidity of the workspace by using a decision tree model that produces a status of cold, cool comfortable, optimal comfort, warm comfort and heat with a predicted level of 0.983.
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Setiady, W., & Apatya, Y. A. (2020). Design Design the temperature and humidity classification of the workspace by using a decision tree model. Electro Luceat, 6(2), 169-178. https://doi.org/10.32531/jelekn.v6i2.228
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This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
References
[1] Talarosa, Basaria, Menciptakan kenyamanan termal dalam bangunan, Jurnal Sistem Teknik Industri Volume 6 No. 3 Juli 2005, hal. 148 – 158. Tersedia : https://www.researchgate.net/profile/Basaria_Talarosha/publication/42362832_Menciptakan_Kenyamanan_Thermal_Dalam_Bangunan/links/54e293e00cf2edaea09319da/Menciptakan-Kenyamanan-Thermal-Dalam-Bangunan.pdf
[2] (2020) Decission Trees. [Online]. Tersedia : https://scikit-learn.org/stable/modules/tree.html
[3] Andi Setiawan , Denis, Sistem Klasifikasi Jenis Karat Menggunakan Metode Decission Tree Berbasis Raspberry Pi, Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3, Februari 2019, hal. 2114~2120. Tersedia : http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/4479/2142
[4] Hamidah, Mimi, Implementasi Decision Tree pada Penentuan Kondisi Ruang Berasap Menggunakan Multi-Sensor Berbasis Arduino Uno, Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer e-ISSN: 2548-964X Vol. 3, No. 4, April 2019, hal 3845-3854. Tersedia : http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/download/5049/2385/
[5] Pratama, Septian Angga, Realisasi Alat Ukur Suhu Dan Kelembapan Berbasis Raspberry Pi, JURNAL TEKNOLOGI TERPADU Vol.7 No.1 April 2019, hal. 62-65. Tersedia : https://jurnal.poltekba.ac.id/index.php/jtt/article/download/636/pdf
[6] Tahir, Frenki, Monitor Kualitas Udara Berbasis Web Menggunakan Raspberry Pi dan Modul Wemos D1, JURNAL TEKNIK Vol.18, No. 1 Juni 2020 hal 35-44. Tersedia : https://jt.ft.ung.ac.id/index.php/jt/article/view/57/41
[7] (2020) Node Red website. [Online]. Tersedia : https://nodered.org/
[8] Mulyono, Sri, Penggunaan Node-RED pada Sistem Monitoring dan Kontrol Green House berbasis Protokol MQTT, Jurnal Transistor Elektro dan Informatika (TRANSISTOR EI) Vol. 3, No. 1, Mei 2018, hal. 31-44. Tersedia : http://jurnal.unissula.ac.id/index.php/EI/article/view/3055/2217
[9] Mulyono, Sri, Sistem IoT Terintegrasi Menggunakan Flow Based Programming dengan Protokol MQTT dan Time Series DB, Jurnal Transistor ElektrodanInformatika(TRANSISTOR EI) Vol. 3, No. 1, Mei 2018, hal. 9-20. Tersedia : http://jurnal.unissula.ac.id/index.php/EI/article/view/3070/2195
[10] Hayyu Wiguna, Esa, Rancang Bangun Sistem Monitoring Ketinggian Air Dan Kelembaban Tanah Pada Penyiram Tanaman Otomatis Dengan Hmi (Human Machine Interface) Berbasis Raspberry Pi Menggunakan Software Node-Red, Gema Teknologi Vol 19 No. 3, April 2017, hal. 1-6. Tersedia : https://ejournal.undip.ac.id/index.php/gema_teknologi/article/download/21878/14612
[11] (2020) Node Red Contrib DHT sensor. [Online]. Tersedia : https://flows.nodered.org/node/node-red-contrib-dht-sensor
[12] (2020) Node Red Contrib Machine Learning. [Online]. Tersedia : https://flows.nodered.org/node/node-red-contrib-machine-learning
[2] (2020) Decission Trees. [Online]. Tersedia : https://scikit-learn.org/stable/modules/tree.html
[3] Andi Setiawan , Denis, Sistem Klasifikasi Jenis Karat Menggunakan Metode Decission Tree Berbasis Raspberry Pi, Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3, Februari 2019, hal. 2114~2120. Tersedia : http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/view/4479/2142
[4] Hamidah, Mimi, Implementasi Decision Tree pada Penentuan Kondisi Ruang Berasap Menggunakan Multi-Sensor Berbasis Arduino Uno, Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer e-ISSN: 2548-964X Vol. 3, No. 4, April 2019, hal 3845-3854. Tersedia : http://j-ptiik.ub.ac.id/index.php/j-ptiik/article/download/5049/2385/
[5] Pratama, Septian Angga, Realisasi Alat Ukur Suhu Dan Kelembapan Berbasis Raspberry Pi, JURNAL TEKNOLOGI TERPADU Vol.7 No.1 April 2019, hal. 62-65. Tersedia : https://jurnal.poltekba.ac.id/index.php/jtt/article/download/636/pdf
[6] Tahir, Frenki, Monitor Kualitas Udara Berbasis Web Menggunakan Raspberry Pi dan Modul Wemos D1, JURNAL TEKNIK Vol.18, No. 1 Juni 2020 hal 35-44. Tersedia : https://jt.ft.ung.ac.id/index.php/jt/article/view/57/41
[7] (2020) Node Red website. [Online]. Tersedia : https://nodered.org/
[8] Mulyono, Sri, Penggunaan Node-RED pada Sistem Monitoring dan Kontrol Green House berbasis Protokol MQTT, Jurnal Transistor Elektro dan Informatika (TRANSISTOR EI) Vol. 3, No. 1, Mei 2018, hal. 31-44. Tersedia : http://jurnal.unissula.ac.id/index.php/EI/article/view/3055/2217
[9] Mulyono, Sri, Sistem IoT Terintegrasi Menggunakan Flow Based Programming dengan Protokol MQTT dan Time Series DB, Jurnal Transistor ElektrodanInformatika(TRANSISTOR EI) Vol. 3, No. 1, Mei 2018, hal. 9-20. Tersedia : http://jurnal.unissula.ac.id/index.php/EI/article/view/3070/2195
[10] Hayyu Wiguna, Esa, Rancang Bangun Sistem Monitoring Ketinggian Air Dan Kelembaban Tanah Pada Penyiram Tanaman Otomatis Dengan Hmi (Human Machine Interface) Berbasis Raspberry Pi Menggunakan Software Node-Red, Gema Teknologi Vol 19 No. 3, April 2017, hal. 1-6. Tersedia : https://ejournal.undip.ac.id/index.php/gema_teknologi/article/download/21878/14612
[11] (2020) Node Red Contrib DHT sensor. [Online]. Tersedia : https://flows.nodered.org/node/node-red-contrib-dht-sensor
[12] (2020) Node Red Contrib Machine Learning. [Online]. Tersedia : https://flows.nodered.org/node/node-red-contrib-machine-learning