Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity
Indonesian government agencies under the Ministry of Energy and Mineral Resources still use manual methods in determining and selecting proposals for operational activities to be carried out. This study uses the Decision Support System (DSS) method, namely Fuzzy Multiple Attribute Decision Decision...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Politeknik Elektronika Negeri Surabaya
2019-06-01
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| Series: | Emitter: International Journal of Engineering Technology |
| Subjects: | |
| Online Access: | https://emitter.pens.ac.id/index.php/emitter/article/view/317 |
| _version_ | 1818945377678655488 |
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| author | Rolly Maulana Awangga Syafrial Fachri Pane Khaera Tunnisa |
| author_facet | Rolly Maulana Awangga Syafrial Fachri Pane Khaera Tunnisa |
| author_sort | Rolly Maulana Awangga |
| collection | DOAJ |
| description | Indonesian government agencies under the Ministry of Energy and Mineral Resources still use manual methods in determining and selecting proposals for operational activities to be carried out. This study uses the Decision Support System (DSS) method, namely Fuzzy Multiple Attribute Decision Decision (Fmadm) and K-Means Clustering method in managing Operational Plan activities. Fmadm to select the best alternative from a number of alternatives, alternatives from this study proposed activity proposals, then ranking to determine the optimal alternative. The K-Means Clustering Method to obtain cluster values for alternatives on the criteria for activity dates, types of activities, and activity ceilings. The last iteration of the Euclidian distance calculation data on k-means shows that alternatives that have the smallest centroid value are important proposal criteria and the largest centroid value is an insignificant proposal criteria. The results of the collaboration of the Fmadm and K-Means Clustering methods show the optimal ranking of activities (proposal activities) and the centroid value of each alternative. |
| first_indexed | 2024-12-20T07:58:09Z |
| format | Article |
| id | doaj.art-3ab0afa94741484fb66b0c4fdd506aaa |
| institution | Directory Open Access Journal |
| issn | 2355-391X 2443-1168 |
| language | English |
| last_indexed | 2024-12-20T07:58:09Z |
| publishDate | 2019-06-01 |
| publisher | Politeknik Elektronika Negeri Surabaya |
| record_format | Article |
| series | Emitter: International Journal of Engineering Technology |
| spelling | doaj.art-3ab0afa94741484fb66b0c4fdd506aaa2022-12-21T19:47:36ZengPoliteknik Elektronika Negeri SurabayaEmitter: International Journal of Engineering Technology2355-391X2443-11682019-06-017110.24003/emitter.v7i1.317317Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management ActivityRolly Maulana Awangga0Syafrial Fachri Pane1Khaera TunnisaPoliteknik Pos IndonesiaPoliteknik Pos IndonesiaIndonesian government agencies under the Ministry of Energy and Mineral Resources still use manual methods in determining and selecting proposals for operational activities to be carried out. This study uses the Decision Support System (DSS) method, namely Fuzzy Multiple Attribute Decision Decision (Fmadm) and K-Means Clustering method in managing Operational Plan activities. Fmadm to select the best alternative from a number of alternatives, alternatives from this study proposed activity proposals, then ranking to determine the optimal alternative. The K-Means Clustering Method to obtain cluster values for alternatives on the criteria for activity dates, types of activities, and activity ceilings. The last iteration of the Euclidian distance calculation data on k-means shows that alternatives that have the smallest centroid value are important proposal criteria and the largest centroid value is an insignificant proposal criteria. The results of the collaboration of the Fmadm and K-Means Clustering methods show the optimal ranking of activities (proposal activities) and the centroid value of each alternative.https://emitter.pens.ac.id/index.php/emitter/article/view/317Activity proposalOperational management of activitiesFmadmK-means clustering. |
| spellingShingle | Rolly Maulana Awangga Syafrial Fachri Pane Khaera Tunnisa Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity Emitter: International Journal of Engineering Technology Activity proposal Operational management of activities Fmadm K-means clustering. |
| title | Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity |
| title_full | Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity |
| title_fullStr | Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity |
| title_full_unstemmed | Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity |
| title_short | Collaboration FMADM And K-Means Clustering To Determine The Activity Proposal In Operational Management Activity |
| title_sort | collaboration fmadm and k means clustering to determine the activity proposal in operational management activity |
| topic | Activity proposal Operational management of activities Fmadm K-means clustering. |
| url | https://emitter.pens.ac.id/index.php/emitter/article/view/317 |
| work_keys_str_mv | AT rollymaulanaawangga collaborationfmadmandkmeansclusteringtodeterminetheactivityproposalinoperationalmanagementactivity AT syafrialfachripane collaborationfmadmandkmeansclusteringtodeterminetheactivityproposalinoperationalmanagementactivity AT khaeratunnisa collaborationfmadmandkmeansclusteringtodeterminetheactivityproposalinoperationalmanagementactivity |