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Landung Sudarmana
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Pengukuran Getaran Aliran Material Lahar Dingin Memanfaatkan Jaringan Sensor Nirkabel dan Uji Statistik Hasil Percobaan Agung Priyanto; Landung Sudarmana; Harjono
Politeknosains Vol 19 No 1 (2020): Jurnal Politeknosains Volume 19 Nomor 1 - Maret 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Politeknik Pratama Mulia Surakarta

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Abstract

Lahar events have been major threats following volcano eruptions. The absence of power grid and communication line in remote areas near the volcano, where the lahar events initiate, makes the sensors deployment a difficult thing to do. Sensors, like cameras and other sensing methods, usually can only be deployed in areas where power grid presents, that is, near residential areas, far enough from where lahar event initiates. Thus, the prediction of lahar event takes longer time to make, because of delayed information received by the lahar event mitigation center, and this may be too late. Vibration sensor utilizing an accelerometer integrated with autonomous, power efficient wireless sensor network is a conclusion for the need. The statistical tests for the laboratorium scale experiment results have been made. A validated method of data analysis that has been chosen fits the data pattern. Furthermore, a significant information that can be used as a parameter for the lahar event early warning system can be achieved.
Penerapan Metode Arima Box-Jenkins Untuk Peramalan Konsumsi Listrik Titik Rahmawati; Landung Sudarmana; Agung Priyanto
Politeknosains Vol 19 No 1 (2020): Jurnal Politeknosains Volume 19 Nomor 1 - Maret 2020
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LPPM) Politeknik Pratama Mulia Surakarta

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Abstract

Electric energy consumption in Indonesia is increasing following the growth of national economy. The rise of activities that need electric energy must be well managed and anticipated. Thus, forecasting of electricity demand in the near future should be considered. One of forecasting methods that has often been used is ARIMA (Autoregressive Integrated Moving Average) time series. This paper aims to explain how to use ARIMA method to forecast electricity energy consumption in a particular area along with its accuracy. The data source supplied to the method is secondary data from PLN (Perusahaan Listrik Negara). For period of 5 years of forecasting, the result shows that the best model of ARIMA method is ARIMA (0,1,0). MAPE (Mean Absolute Percentage Error) value of the model is 0.33%, meaning that the accuracy will be 99.67%.
Co-Authors Agung Priyanto Harjono Titik Rahmawati