Klasifikasi Indeks Standar Pencemaran Udara (ISPU) di DKI Jakarta Menggunakan Algoritma Random Forest

Daniswara, Dimas Dzaky (2024) Klasifikasi Indeks Standar Pencemaran Udara (ISPU) di DKI Jakarta Menggunakan Algoritma Random Forest. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

Air quality is one of the most important factors affecting human health and well-being. Polluted air can cause various respiratory, cardiovascular and cancer diseases. As the capital city of Indonesia, Jakarta is the province in Indonesia that has the highest level of air pollution, this has an impact on the decline in air quality in Jakarta. One way to inform the public about air quality is by using the Air Pollutant Standard Index (ISPU). ISPU is a unitless number that describes the ambient air quality conditions at a particular location. ISPU is calculated based on the concentration of several air pollutant parameters such as; particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3). To classify ISPU, a method is needed that can learn patterns from sensor data that measure the concentration of air pollutants. Therefore, the author would like to conduct research on the comparison of Random Forest and Support Vector Machine algorithms. This research was conducted using data on the DKI Jakarta air pollution standard index (ISPU) in 2021 with a total of 1837 data. The available data is divided into train data and test data, where 80% is used as train data and 20% as test data. After data division, model training is carried out using train data and model testing using test data. The model was also tested for validation using k-fold cross validation. In testing and validation using the Random Forest algorithm, the model accuracy rate and validation average are superior with a percentage of 99% and 95%. Meanwhile, the Support Vector Machine algorithm obtained model accuracy and average validation with a percentage of 94% and 91%.

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorDiyasa, I Gede Susrama MasNIDN0019067008UNSPECIFIED
Thesis advisorDamaliana, Aviolla TerzaNIDN0002089402UNSPECIFIED
Subjects: T Technology > T Technology (General)
Divisions: Faculty of Computer Science
Depositing User: Dimas Dzaky Daniswara
Date Deposited: 19 Jan 2024 10:16
Last Modified: 19 Jan 2024 10:16
URI: http://repository.upnjatim.ac.id/id/eprint/20273

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