Desain Dan Pengembangan Sistem Monitoring Beban Listrik Alternating Current (Ac) Terpakai Menggunakan Jaringan Syaraf Tiruan Berbasis Internet Of Things (Iot) Pada Bangunan Rumah Tangga

Astika, Veronica Maulin (2021) Desain Dan Pengembangan Sistem Monitoring Beban Listrik Alternating Current (Ac) Terpakai Menggunakan Jaringan Syaraf Tiruan Berbasis Internet Of Things (Iot) Pada Bangunan Rumah Tangga. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Manajemen energi listrik pada rumah tangga membutuhkan informasi yang akurat tentang
pola konsumsi peralatan listrik yang digunakan. Sehingga, dapat membantu konsumen
menghemat energi, mengontrol penggunaan dengan mengalihkan penggunaan ke jam-jam
di luar jam sibuk, dan mengurangi biaya listrik. Salah satu cara untuk membantu konsumen
menghemat energi listrik adalah dengan mengklasifikasikan beban listrik Alternating
Current (AC) terpakai dengan teknologi IoT serta mengetahui Tarif Adjusment. Pada
penelitian ini, dilakukan simulasi menggunakan Jaringan Syaraf Tiruan untuk menentukan
nilai optimum dalam penentuan klasifikasi beban listrik Alternating Current (AC) terpakai.
Berdasarkan perancangan JST yang dilakukan, diperoleh akurasi output sebesar 91.93%.
Sedangkan untuk pengujian, diperoleh nilai akurasi sebesar 83.33%. Hasil olah JST tersebut
di kirimkan ke ThingSpeak agar dapat dilakukan monitoring oleh user. Adapun hasil
monitoring biaya listrik telah sesuai dengan Tarif Tenaga Listrik - PT PLN (Persero) pada
Bulan Juni-Juli 2021. Hasil uji transmisi data didapatkan rata-rata waktu delay 1-2 detik
untuk mengirim data antara alat monitoring dengan ThingSpeak. Dengan diadakannya
penelitian ini, peneliti berharap dapat membantu konsumen untuk memantau pemakaian
beban listrik serta menghitung biaya listrik pada tempat tinggal
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Electrical energy management in households requires accurate information about the consumption patterns of the electrical equipment used. Thus, it can help consumers save energy, control usage by shifting usage to off-peak hours, and reduce electricity costs. One way to help consumers save electrical energy is to classify the Alternating Current (AC) electricity load used with IoT technology and find out the Adjustment Rate. In this study, a simulation was carried out using an artificial neural network to determine the optimum value in determining the classification of used alternating current (AC) electrical loads. Based on the ANN design, the output accuracy is 91.93%. As for testing, obtained an accuracy value of 83.33%. The results of the ANN are sent to ThingSpeak for monitoring by the user. The results of monitoring electricity costs are in accordance with the Electricity Tariff - PT PLN (Persero) in June-July 2021. The results of the data transmission test obtained an average delay time of 1-2 seconds to send data between the monitoring tool and ThingSpeak. By holding this research, researchers hope to help consumers to monitor the use of electricity loads and calculate the cost of electricity in their homes.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Jaringan Syaraf Tiruan, Internet of Things, beban listrik
Subjects:	Q Science > QA Mathematics > QA76.625 Internet programming. Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) Q Science > QC Physics T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK351 Electric measurements.
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Veronica Maulin Astika
Date Deposited:	30 Aug 2021 03:41
Last Modified:	30 Aug 2021 03:41
URI:	http://repository.its.ac.id/id/eprint/90408

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