Power consumption of PLN customers from household sector is quite large. It comes from the use of household appliances, such as refrigerators, televisions, dispensers, lights and air conditioners. The customers assume that their electricity usage is wasteful, but unfortunately it couldn’t be known in detail which household electrical appliances spend the most electricity. So that, difficult for the customers to monitor the power usage of each household electrical equipments. Regarding to this issue, this research focused on making a prototype of a household electrical power usage monitoring system. This system can be used by PLN customers of households sector to find out which household appliances use large power, so that the customers can manage the use of household appliances. In implementing that monitoring, it needs a capable wattmeter devices to measure the power usage of household electronic equipments The results of this measurement electric current, voltage, and power data measured through sensors. Those measurement data is sent to the database server system monitoring through the internet of things (IoT) device so that monitoring can be done through the system in a real time. This study produced a prototype of household electronic equipments power usage monitoring system based on IoT.
PLN customer power consumption from the household sector is quite large, originating from the use of household appliances, such as refrigerators, televisions, dispensers, lamps and air conditioners. When users feel that their electricity usage is wasteful, they do not know in detail which household electrical appliances consume the most electricity. At this time customers still find it difficult to monitor the power usage of every household electrical appliance. So it is not known which equipment consumes large amounts of electrical energy. For this reason, a monitoring system for household electrical power usage is needed. This system can be used by PLN household sector customers to find out which household appliances use large power, so customers can manage the use of household appliances. To do this monitoring, a wattmeter device is needed that is able to measure the power use of household electronic equipment. The results of this measurement are measured current data through the current sensor. So that monitoring can be done through the system in real time, the measurement data is sent to the monitoring system database server via the internet of things (IoT) devices. Data generated from the monitoring system can be analyzed using prediction techniques, to obtain information about the length of time the availability of electrical energy has been purchased by the customer. One algorithm that can be used to predict the use of household electrical power is the CART algorithm. This research aims to build a monitoring system for power usage for each IoT -based household appliances. This research aims to build a monitoring system for power usage for each IoT-based household appliances. The second objective of this research is to apply CART algorithm to predict the power usage of household appliances.
The use of electricity in household sector has increased, especially during the Covid-19 pandemic. The large number of activities carried out in home such as Work from Home, online schools, and online businesses caused difficulty to monitor the electricity consumption. The absence of electricity usage provisions affects the electricity monitoring process. Hence it takes a real time monitoring application of electricity consumption. Fuzzy subtractive clustering is an unsupervised method to form the number and center of clusters according to data conditions. This method serves to classify the household electricity users with the parameters used, is the amount of usage in rupiah and electric power. The grouping results from this method help users to monitoring electricity consumption in real time. The output describes the level of high, medium and low user electricity consumption. Based on the test results, the best Silhouette Coefficient value is 0.8322535 and three clusters are formed, with an accept ratio is 0.5, a reject ratio of 0.15, a radius of 1.7 and a squash factor of 0.5 hence a high level of use is obtained with an average value of the number of uses in IDR 655,993, power 2757 VA, medium level 240,553, 1071 VA and low level 46,479, 675 VA
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