Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model

Melva Hilda Stephanie Situmorang; Bahrul Ilmi Nasution; Muhammad Erza Aminanto; Yudhistira Nugraha; Juan Intan Kanggrawan

doi:10.1145/3575882.3575916

Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model

Melva Hilda Stephanie Situmorang, Bahrul Ilmi Nasution, Muhammad Erza Aminanto, Yudhistira Nugraha, Juan Intan Kanggrawan

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

Abstract

This study aims to compare the Air Pollution Index (API) clustering between fuzzy c-means (FCM) with gaussian mixture model. This study used air quality data on each parameter in 2019-2020 from five monitoring stations, that is Bundaran HI (DKI1), Kelapa Gading (DKI2), Jagakarsa (DKI3), Lubang Buaya (DKI4), and Kebon Jeruk (DKI5). Determination of the optimum cluster number on Fuzzy C-Means based on Partition Coefficient (PC), Classification Entropy (CE), Separation Index (SI), Silhouette Index, and Effectiveness. The optimum cluster number in the Gaussian Mixture Model is based on BIC and Silhouette Index values. Almost all Silhouette values on Fuzzy C-Means are more significant than the Silhouette Gaussian Mixture Model. Fuzzy C-Means is more suitable for clustering Jakarta Air Pollution Index (API) than The Gaussian Mixture Model method.

Original language	English
Title of host publication	Proceeding - The 9th International Conference on Computer, Control, Informatics and Its Applications
Editors	Foni Setiawan M.Kom
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	174-178
Number of pages	5
ISBN (Electronic)	9781450397919
DOIs	https://doi.org/10.1145/3575882.3575916
Publication status	Published - 2023
Externally published	Yes
Event	International Conference on Computer, Control, Informatics and Its Applications 2022: Digital Transformation Towards Sustainable Society for Post Covid-19 Recovery - Online, Indonesia Duration: 22 Nov 2022 → 23 Nov 2022 Conference number: 9th https://dl.acm.org/doi/proceedings/10.1145/3575882 (Proceedings) https://conference.brin.go.id/ic3ina2022/ (Website)

Conference

Conference	International Conference on Computer, Control, Informatics and Its Applications 2022
Abbreviated title	IC3INA 2022
Country/Territory	Indonesia
Period	22/11/22 → 23/11/22
Internet address	https://dl.acm.org/doi/proceedings/10.1145/3575882 (Proceedings) https://conference.brin.go.id/ic3ina2022/ (Website)

Keywords

Air Pollution Index (API)
Fuzzy C-Means
Gaussian Mixture Models
Silhouette Index

Access to Document

10.1145/3575882.3575916

Cite this

Situmorang, M. H. S., Nasution, B. I., Aminanto, M. E., Nugraha, Y., & Kanggrawan, J. I. (2023). Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model. In F. S. M.Kom (Ed.), Proceeding - The 9th International Conference on Computer, Control, Informatics and Its Applications (pp. 174-178). Association for Computing Machinery (ACM). https://doi.org/10.1145/3575882.3575916

Situmorang, Melva Hilda Stephanie ; Nasution, Bahrul Ilmi ; Aminanto, Muhammad Erza et al. / Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model. Proceeding - The 9th International Conference on Computer, Control, Informatics and Its Applications. editor / Foni Setiawan M.Kom. New York NY USA : Association for Computing Machinery (ACM), 2023. pp. 174-178

@inproceedings{a468c6b0af2c4b26b1668a2899bcdb2e,

title = "Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model",

abstract = "This study aims to compare the Air Pollution Index (API) clustering between fuzzy c-means (FCM) with gaussian mixture model. This study used air quality data on each parameter in 2019-2020 from five monitoring stations, that is Bundaran HI (DKI1), Kelapa Gading (DKI2), Jagakarsa (DKI3), Lubang Buaya (DKI4), and Kebon Jeruk (DKI5). Determination of the optimum cluster number on Fuzzy C-Means based on Partition Coefficient (PC), Classification Entropy (CE), Separation Index (SI), Silhouette Index, and Effectiveness. The optimum cluster number in the Gaussian Mixture Model is based on BIC and Silhouette Index values. Almost all Silhouette values on Fuzzy C-Means are more significant than the Silhouette Gaussian Mixture Model. Fuzzy C-Means is more suitable for clustering Jakarta Air Pollution Index (API) than The Gaussian Mixture Model method.",

keywords = "Air Pollution Index (API), Fuzzy C-Means, Gaussian Mixture Models, Silhouette Index",

author = "Situmorang, {Melva Hilda Stephanie} and Nasution, {Bahrul Ilmi} and Aminanto, {Muhammad Erza} and Yudhistira Nugraha and Kanggrawan, {Juan Intan}",

note = "Publisher Copyright: {\textcopyright} 2022 ACM.; International Conference on Computer, Control, Informatics and Its Applications 2022 : Digital Transformation Towards Sustainable Society for Post Covid-19 Recovery, IC3INA 2022 ; Conference date: 22-11-2022 Through 23-11-2022",

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doi = "10.1145/3575882.3575916",

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pages = "174--178",

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booktitle = "Proceeding - The 9th International Conference on Computer, Control, Informatics and Its Applications",

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address = "United States of America",

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Situmorang, MHS, Nasution, BI, Aminanto, ME, Nugraha, Y & Kanggrawan, JI 2023, Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model. in FS M.Kom (ed.), Proceeding - The 9th International Conference on Computer, Control, Informatics and Its Applications. Association for Computing Machinery (ACM), New York NY USA, pp. 174-178, International Conference on Computer, Control, Informatics and Its Applications 2022, Indonesia, 22/11/22. https://doi.org/10.1145/3575882.3575916

Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model. / Situmorang, Melva Hilda Stephanie; Nasution, Bahrul Ilmi; Aminanto, Muhammad Erza et al.
Proceeding - The 9th International Conference on Computer, Control, Informatics and Its Applications. ed. / Foni Setiawan M.Kom. New York NY USA: Association for Computing Machinery (ACM), 2023. p. 174-178.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

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T1 - Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model

AU - Situmorang, Melva Hilda Stephanie

AU - Nasution, Bahrul Ilmi

AU - Aminanto, Muhammad Erza

AU - Nugraha, Yudhistira

AU - Kanggrawan, Juan Intan

N1 - Conference code: 9th

PY - 2023

Y1 - 2023

N2 - This study aims to compare the Air Pollution Index (API) clustering between fuzzy c-means (FCM) with gaussian mixture model. This study used air quality data on each parameter in 2019-2020 from five monitoring stations, that is Bundaran HI (DKI1), Kelapa Gading (DKI2), Jagakarsa (DKI3), Lubang Buaya (DKI4), and Kebon Jeruk (DKI5). Determination of the optimum cluster number on Fuzzy C-Means based on Partition Coefficient (PC), Classification Entropy (CE), Separation Index (SI), Silhouette Index, and Effectiveness. The optimum cluster number in the Gaussian Mixture Model is based on BIC and Silhouette Index values. Almost all Silhouette values on Fuzzy C-Means are more significant than the Silhouette Gaussian Mixture Model. Fuzzy C-Means is more suitable for clustering Jakarta Air Pollution Index (API) than The Gaussian Mixture Model method.

AB - This study aims to compare the Air Pollution Index (API) clustering between fuzzy c-means (FCM) with gaussian mixture model. This study used air quality data on each parameter in 2019-2020 from five monitoring stations, that is Bundaran HI (DKI1), Kelapa Gading (DKI2), Jagakarsa (DKI3), Lubang Buaya (DKI4), and Kebon Jeruk (DKI5). Determination of the optimum cluster number on Fuzzy C-Means based on Partition Coefficient (PC), Classification Entropy (CE), Separation Index (SI), Silhouette Index, and Effectiveness. The optimum cluster number in the Gaussian Mixture Model is based on BIC and Silhouette Index values. Almost all Silhouette values on Fuzzy C-Means are more significant than the Silhouette Gaussian Mixture Model. Fuzzy C-Means is more suitable for clustering Jakarta Air Pollution Index (API) than The Gaussian Mixture Model method.

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KW - Gaussian Mixture Models

KW - Silhouette Index

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BT - Proceeding - The 9th International Conference on Computer, Control, Informatics and Its Applications

A2 - M.Kom, Foni Setiawan

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

T2 - International Conference on Computer, Control, Informatics and Its Applications 2022

Y2 - 22 November 2022 through 23 November 2022

ER -

Situmorang MHS, Nasution BI, Aminanto ME, Nugraha Y, Kanggrawan JI. Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model. In M.Kom FS, editor, Proceeding - The 9th International Conference on Computer, Control, Informatics and Its Applications. New York NY USA: Association for Computing Machinery (ACM). 2023. p. 174-178 doi: 10.1145/3575882.3575916

Air pollution index (API) analysis at Jakarta in 2019-2020 using Fuzzy C-Means and Gaussian Mixture Model

Abstract

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Keywords

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