KUALITAS PERANGKAT LUNAK: MODULARITAS PUSTAKA TEXT PRE-PROCESSING

Authors

  • Dian Sa'adillah Maylawati Sekolah Tinggi Teknologi Garut
  • Hamdan Sugilar UIN Sunan Gunung Djati Bandung
  • Rully Agung Yudhiantara UIN Sunan Gunung Djati Bandung

DOI:

https://doi.org/10.15575/jp.v1i2.11

Keywords:

kualitas perangkat lunak, modularitas, pustaka perangkat lunak, text pre-processing

Abstract

Perangkat lunak yang baik harus mencapai kualitas yang baik pula. Termasuk pustaka (library) dan komponen perangkat lunak yang akan dipanggil pada perangkat lunak lainnya. Terdapat beberapa faktor kualitas yang dapat dicapai pustaka perangkat lunak, antara lain fleksibilitas, modularitas, interoperabilitas, dan portabilitas. Penelitian ini bertujuan untuk mengukur faktor kualitas modularitas dari pustaka text pre-processing untuk Bahasa Indonesia. Metodologi pembangunan pustaka menggunakan Waterfall dengan menerapkan Unified Modelling Language (UML) sebagai model perangkat lunak. Pustaka text pre-processing dibangun dengan bahasa pemrograman Java dengan masukan berupa koleksi dokumen teks dan keluaran berupa Himpunan Frequent Word Itemset (HFWI) sebagai representasi teks terstruktur. Modularitas pustaka diukur dengan menggunakan metriks Coupling between Object Classes (CBO) dan Lack of Cohesion in Methods (LCOM). Hasil pengukuran dan evaluasi modularitas pustaka menunjukkan bahwa modularitas pustaka sudah dicapai dengan kohesi yang cukup tinggi dan kopling yang rendah. Kohesi yang cukup tinggi ditunjukkan dengan nilai LCOM 0.381, sedangkan kopling yang rendah ditunjukkan dengan nilai CBO 1.045.

References

Alvaro, A., 2010. A Software Component Quality Framework. ACM SIGSOFT Software ENgineering Notes, November.35(1).

Carpineto, C., Osinski, S., Romani, G. & Weiss, D., 2009. A Survey of Web Clustering Engines. ACM Computing Survey, July.41(3).

Choi, Y. e. a., 2008. Practical S/W Component Quality Evaluation Model. s.l., s.n.

Doucet, A., 2005. Advance Document Description, a Sequential Approach, Finland: Academic Dissertation, Departement of Computer Science, Series of Publication A. Report A-2005-2, University of Helsinki.

Han, J. & Kamber, M., 2006. Data Mining: Concepts and Techniques. Second ed. Simon Fraser University: Morgan Kaufmann Publisher.

Helena, A., 1999. Knowledge Discovery in Document by Extracting Frequent Word Sequence. Library Trends, 48(1), pp. 160-181.

Honloor, A., 2011. Sequential Pattern and Temporal Patterns for Text MIning, New York: Graduate Faculty of Rensselaer Polytechnic Intitute, Major Subject: Computer Science.

Mahgoub, H., Rosner, D., Ismail, N. & Torkey, F., 2008. Text Mining Technique Using Association Rules Extraction. International Journal of Information and Mathematical Science, 4(1), pp. 21-28.

Maylawati, D. S., 2015. Pembangunan Library Pre-processing untuk Text Mining dengan Representasi Himpunan Frequent Word Itemset. Studi Kasus Bahasa Gaul Indonesia, Bandung: Bandung Institute of Technology.

Maylawati, D. S., Irfan, M. & Zulfikar, W. B., 2016. Comparison between BIDE, PrefixSpan, and TRuleGrowth for Mining of Indonesian Text. Medan, IOP Conference Series.

Maylawati, D. S., Ramdhani, M. A., Rahman, A. & Darmalaksana, W., 2017. Incremental technique with set of frequent word item sets for mining large Indonesian text data. Denpasar, s.n.

Maylawati, D. S. & Saptawati, G. A. P., 2016. Set of Frequent Word Item sets as Feature Representation for Text with Indonesian Slang. Medan, IOP Conf. Series: Journal of Physics.

Meyer, B., 1997. Object-Oriented Software Construction. Second ed. s.l.:Prentice Hall.

Pressman, R. S., 2010. Software Engineering, A Practitioner's Approach. 7 ed. New York: McGraw-Hill.

Ramdhani, M. A., 2013. Metodologi Penelitian dalam Riset Teknologi Informasi. Bandung: UIN Sunan Gunung Djati Bandung.

Sommerville, I., 2011. Software Engineering. 9 ed. Massachusetts, United State, America: Addison-Wesley.

Srividhya, V. & Anitha, R., 2010. Evaluating Preprocessing Techniques in Text Categorization. International Journal of Computer Science ad Application Isues 2010.

Torre, C. J., Matrin-Bautista, M. J. S. & Blanco, I. D., 2008. Text Knowledge Mining: And Approach to Text Mining. ESTYLF08, 17-19 September.

Zohar, Y. E., 2002. Introduction to Text Mining. [Online]

Available at: http://www.docstoc.com/docs/25443990/Introduction-to-Text-Mining

[Accessed 2014].

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Published

2018-03-28

How to Cite

Maylawati, D. S., Sugilar, H., & Yudhiantara, R. A. (2018). KUALITAS PERANGKAT LUNAK: MODULARITAS PUSTAKA TEXT PRE-PROCESSING. Jurnal Perspektif, 1(2). https://doi.org/10.15575/jp.v1i2.11

Issue

Vol. 1 No. 2 (2017): Jurnal Perspektif

Section

Jurnal Perspektif

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