PREDICTING THE AMOUNT OF PETROLEUM AND NATURAL GAS PRODUCTION WITH WEIGHTED MOVING AVERAGE ALGORITHM

SETIAWAN, HANIF PANDU (2019) PREDICTING THE AMOUNT OF PETROLEUM AND NATURAL GAS PRODUCTION WITH WEIGHTED MOVING AVERAGE ALGORITHM. Other thesis, UNIKA SOEGIJAPRANATA SEMARANG.

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Abstract

Data on Petroleum and Natural Gas production in Indonesia every year changes irregularly. The data can be seen on the website of the Badan Pusat Statistik (BPS), www.bps.go.id in the Mining tab section. It is feared that the unpredictable amount can disrupt natural resources in the surrounding area which lead to environmental damage. Therefore, the irregular data can be used to predict the amount of petroleum production and natural gas for the next year with the help of the WMA (Weighted Moving Average) Algorithm. The workings of this calculation are to give weight in such a way that the total amount is equal to one, the weight is given to each data used, the weight is most heavily charged to the latest data because it is relevant for predictions. From several other Moving Average algorithms such as Simple Moving Average (SMA) and Exponential Moving Average (EMA), the Weighted Moving Average (WMA) algorithm has the least Mean Squared Error (MSE). From several experiments with other Algorithms, other weight, and some amount of data. The WMA algorithm with 2 years of data uses weight 0.1 and 0.9 which gets the smallest MSE value, ie the value of MSE of petroleum is only 0.0382 and the MSE value of gas is only 0.0218. The smaller value of MSE’s calculation shows the more accurate predictions. The final result of this project is an application to simplify predicting the amount of Petroleum and Natural Gas Production in Indonesia for the next year. The operation is quite easy, the user only imports data and then clicks the button as instructed. These data are stored in CSV format and then imported to the MySql database to start the calculation process. The programming language used is php Keyword: Predicting, Peroleum, Natural Gas, Weighted Moving Average, PHP

Item Type: Thesis (Other)
Subjects: 000 Computer Science, Information and General Works
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: Mr Lucius Oentoeng
Date Deposited: 22 Nov 2019 01:14
Last Modified: 10 Nov 2020 07:17
URI: http://repository.unika.ac.id/id/eprint/20039

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