PREDIKSI KUALITAS AIR SUNGAI CILIWUNG DENGAN MENGGUNAKAN ALGORITMA POHON KEPUTUSAN

Mohammad Haekal, . (2020) PREDIKSI KUALITAS AIR SUNGAI CILIWUNG DENGAN MENGGUNAKAN ALGORITMA POHON KEPUTUSAN. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

To predict the water quality of the Ciliwung river, data processing of monitoring results has been done online monitoring using the Data Mining Method. In this method, the monitoring data is first made in the form of a Microsoft Excel table, then processed into a Decision Tree called a Decision Tree Algorithm using the WEKA application. The Decision Tree method was chosen because it is simpler, easier to understand, and has a very high level of accuracy. The amount of data from the monitoring of the quality of the treated Ciliwung river is 5,476 data. The results of clarification with the Decision Tree, from 5,476 data obtained the amount of data that indicates the Ciliwung river is not polluted as many as 1,059 data or as much as 19.3242%, and which indicates polluted as much as 4,417 data or 80.6758%. Furthermore, the data from the monitoring results were evaluated using 4 test options, namely the Use Training Set, Supplied Test Set, Cross-Validation 10-folds Set, and 66.0% Split Percentage. The results of the evaluation with the 4 test options used all show a very high degree of accuracy, which is above 99%. From the data of this research it can be predicted that the Ciliwung river is indicated as a polluted river when referring to the Republic of Indonesia Government Regulation, number 82,the year 2001 and it is also known that the use of the WEKA application with Decree Tree Algorithm to process monitoring data by taking three the parameters (pH, Dissolved Oxygen and Nitrate) are very accurate and precise.

Item Type:	Thesis (Skripsi)
Additional Information:	[No.Panggil : 1410511008] [Pembimbing 1 : Henki Bayu Seta] {Pembimbing 2 : Mayanda Mega Santoni] [Penguji 1 ; Titin Pramiyati] [Penguji 2 : Bambang Triwahyono]
Uncontrolled Keywords:	River Water Quality Monitoring, Data Processing, Data Mining, Decision Trees, WEKA Application.
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Divisions:	Fakultas Ilmu Komputer > Program Studi Informatika (S1)
Depositing User:	Mohammad Haekal
Date Deposited:	13 Jan 2022 02:22
Last Modified:	13 Jan 2022 02:22
URI:	http://repository.upnvj.ac.id/id/eprint/6507

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