International Journal of Computer
Trends and Technology

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Volume 33 | Number 1 | Year 2016 | Article Id. IJCTT-V33P120 | DOI : https://doi.org/10.14445/22312803/IJCTT-V33P120

Correlation Measurement Between UNSPSC and KBLI 2009 Based on Classification

Edi Wahyu Widodo, Tri Harsono, Ali Ridho Barakbah

Citation :

Edi Wahyu Widodo, Tri Harsono, Ali Ridho Barakbah, "Correlation Measurement Between UNSPSC and KBLI 2009 Based on Classification," International Journal of Computer Trends and Technology (IJCTT), vol. 33, no. 1, pp. 93-98, 2016. Crossref, https://doi.org/10.14445/22312803/ IJCTT-V33P120

Abstract

Electronic world have penetrated almost all fields, including in the field of procurement of goods and services by the government in Indonesia. Since 2007 in Indonesia has implemented the electronic procurement (e-procurement) of goods and services. In the procurement of goods and services that are now running, there is no classification or standard of goods and services as well as existing enterprises. In order to become more professional in auction, it is necessary to implement the classification. Classification of goods and services in accordance with the UNSPSC and business classification in Indonesia using KBLI edition 2009 to find which the business classification according to the UNSPSC to be in the auction, used methods of correlation measurements with text mining, allowing to find appropriate business classifications.

Keywords

UNSPSC, KBLI 2009, E-Tendering, Text Mining, Correlation Measurements.

References

[1] LKPP Indonesia http://lpse.lkpp.go.id
[2] UNSPSC http://www.unspsc.org
[3] Head of The Central Statistics Regulation Number 57 of 2009.
[4] Munindar P. Singh, “The Practical Handbook of Internet Computing”, CHAPMAN & HALL/CRC Computer and Information Science Series, 2005.
[5] Ian H. Witten, “Text Mining”, Computer Science, University of Waikato, Hamilton, New Zealand, 2005.
[6] Vikram Singh and Balwinder Saini, “An Effective Tokenization Algorithm For Information Retrieval Systems”, Departement of Computer Engineering, National Institute of Technology Kurukshetra, Haryana, India, 2014.
[7] Tanu Verma and Renu and Deepti Gaur, “Tokenization and Filtering Process in RapidMiner”, International Journal of Applied Information System (IJAIS), 2014.
[8] Text Mining Online http://www.textminingonline.com
[9] Joel Larocca Neto and Alexandre D. Santos and Celso A.A. Kaestner and Neto Alexandre and D. Santos and Celso A. A and Kaestner Alex and Alex A. Freitas, “Document Clustering and Text Summarization”, Pontificia Universidade Catolica do Parana, Postgraduate Program in Applied Computer Science, Brazil, 2000.
[10] Martin Hepp, Joerg Leukel, and Volker Schmitz, “A Quantitative Analysis of Product Categorization Standards: Content, Coverage, and Maintenance of eCl@ss, UNSPSC, eOTD, and the RosettaNet Technical Dictionary”, Springer, 2006
[11] Leo Obrst Robert E. Wray Howard Liu, “Leo Obrst Robert E. Wray Howard LiuOntological Engineering for B2B ECommerce”, Proceedings of the international conference on Formal Ontology in Information Systems, 2001
[12] Bjornar Larsen and Chinatsu Aone, “Fast and effective text mining using linear-time document clustering”, Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, 1999
[13] Weiguo Fan, Linda Wallace, Stephanie Rich, Zhongju Zhang, “Tapping the power of text mining”, Magazine Communications of the ACM - Privacy and security in highly dynamic systems, Volume 49 Issue 9, September 2006
[14] Tuomo Kakkonen and Tabish Mufti, “Developing and applying a company, product and business event ontology for text mining”, Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, 2011
[15] Yue Dai, Tuomo Kakkonen, Erkki Sutinen, “MinEDec: a Decision-Support Model That Combines Text-Mining Technologies with Two Competitive Intelligence Analysis Methods”, International Journal of Computer Information Systems and Industrial Management Applications, 2011
[16] Kalesha, Pattan, M. Babu Rao, and Ch Kavitha. "Efficient Preprocessing and Patterns Identification Approach for Text Mining." INTERNATIONAL JOURNAL OF COMPUTER TRENDS & TECHNOLOGY 1.6: 124-129.
[17] Saritha, A., and N. NaveenKumar. "Effective Classification of Text." International Journal of Computer Trends 0 20: 40-60.
[18] Ababneh, Jafar, et al. "Vector space models to classify Arabic text." International Journal of Computer Trends and Technology (IJCTT) 7.4 (2014): 219-223.