PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS (Studi pada Kepolisian Daerah Sulawesi Tenggara)
Data of traffic accident in Southeast Sulawesi has increased every year. Therefore, traffic accident in Southeast Sulawesi needs to get more effective handling. Effective handling related to right policies about the management and traffic engineering. It should be supported by knowledge based on a t...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2014
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| _version_ | 1826047921224679424 |
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| author | , Natalis Ransi , Drs. Edi Winarko, M.Sc., Ph.D. |
| author_facet | , Natalis Ransi , Drs. Edi Winarko, M.Sc., Ph.D. |
| author_sort | , Natalis Ransi |
| collection | UGM |
| description | Data of traffic accident in Southeast Sulawesi has increased every year.
Therefore, traffic accident in Southeast Sulawesi needs to get more effective
handling. Effective handling related to right policies about the management and
traffic engineering. It should be supported by knowledge based on a traffic
accidents database. One of the knowledge that may be got is the characteristic of
severity (dead, seriously injured, lightly injured) of the traffic accident.
This research is to apply Classification based on Predictive Association
Rules (CPAR) algorithm in data base traffic accident, Southeast Sulawesi Police
Department between in the period of 2010 to 2012. CPAR algorithm produces Class
Association Rules (CARs) which is used to describe knowledge about the
characteristics of severity of the traffic accident victims.
The results of experiment shows that the main cause of traffic accident were
human factors (driving under the influence of alcohol and driving exceed the
maximum speed) and environmental physical factors (damage road and elbow
road). Types of accidents (single and head-on) and accidents involving motor cycles
contribute potentially that the victims died. Testing the accuracy using 10-fold cross
validation shows that the average accuracy of CPAR algorithm is 48,75% that is
higher than PRM algorithm 41.13%. |
| first_indexed | 2024-03-13T23:18:47Z |
| format | Thesis |
| id | oai:generic.eprints.org:127910 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:18:47Z |
| publishDate | 2014 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1279102016-03-04T08:05:00Z https://repository.ugm.ac.id/127910/ PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS (Studi pada Kepolisian Daerah Sulawesi Tenggara) , Natalis Ransi , Drs. Edi Winarko, M.Sc., Ph.D. ETD Data of traffic accident in Southeast Sulawesi has increased every year. Therefore, traffic accident in Southeast Sulawesi needs to get more effective handling. Effective handling related to right policies about the management and traffic engineering. It should be supported by knowledge based on a traffic accidents database. One of the knowledge that may be got is the characteristic of severity (dead, seriously injured, lightly injured) of the traffic accident. This research is to apply Classification based on Predictive Association Rules (CPAR) algorithm in data base traffic accident, Southeast Sulawesi Police Department between in the period of 2010 to 2012. CPAR algorithm produces Class Association Rules (CARs) which is used to describe knowledge about the characteristics of severity of the traffic accident victims. The results of experiment shows that the main cause of traffic accident were human factors (driving under the influence of alcohol and driving exceed the maximum speed) and environmental physical factors (damage road and elbow road). Types of accidents (single and head-on) and accidents involving motor cycles contribute potentially that the victims died. Testing the accuracy using 10-fold cross validation shows that the average accuracy of CPAR algorithm is 48,75% that is higher than PRM algorithm 41.13%. [Yogyakarta] : Universitas Gadjah Mada 2014 Thesis NonPeerReviewed , Natalis Ransi and , Drs. Edi Winarko, M.Sc., Ph.D. (2014) PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS (Studi pada Kepolisian Daerah Sulawesi Tenggara). UNSPECIFIED thesis, UNSPECIFIED. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=68221 |
| spellingShingle | ETD , Natalis Ransi , Drs. Edi Winarko, M.Sc., Ph.D. PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS (Studi pada Kepolisian Daerah Sulawesi Tenggara) |
| title | PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS
(Studi pada Kepolisian Daerah Sulawesi Tenggara) |
| title_full | PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS
(Studi pada Kepolisian Daerah Sulawesi Tenggara) |
| title_fullStr | PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS
(Studi pada Kepolisian Daerah Sulawesi Tenggara) |
| title_full_unstemmed | PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS
(Studi pada Kepolisian Daerah Sulawesi Tenggara) |
| title_short | PENGAPLIKASIAN ALGORITMA CLASSIFICATION BASED ON PREDICTIVE ASSOCIATION RULES UNTUK ANALISA KARAKTERISTIK KECELAKAAN LALU LINTAS
(Studi pada Kepolisian Daerah Sulawesi Tenggara) |
| title_sort | pengaplikasian algoritma classification based on predictive association rules untuk analisa karakteristik kecelakaan lalu lintas studi pada kepolisian daerah sulawesi tenggara |
| topic | ETD |
| work_keys_str_mv | AT natalisransi pengaplikasianalgoritmaclassificationbasedonpredictiveassociationrulesuntukanalisakarakteristikkecelakaanlalulintasstudipadakepolisiandaerahsulawesitenggara AT drsediwinarkomscphd pengaplikasianalgoritmaclassificationbasedonpredictiveassociationrulesuntukanalisakarakteristikkecelakaanlalulintasstudipadakepolisiandaerahsulawesitenggara |