IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOR UNTUK IDENTIFIKASI KUALITAS AIR (STUDI KASUS : PDAM KOTA SURAKARTA)

Authors

  • Rio Adi Arnomo
  • Wawan Laksito Yuly Saptomo STMIK Sinar Nusantara, Indonesia
  • Paulus Harsadi

DOI:

https://doi.org/10.30646/tikomsin.v6i1.345

Abstract

Water quality in urban areas in Surakarta has decreased nowadays. The increase of industrial development, its poor sewage treatment, and some other factors cause this urban problem. The result of the water quality monitoring system with K-Nearest Neighbor algorithm on this research certainly will help the laborers’ duty of PDAM (Local Government Owned Water Utilities) in analyzing water quality. For the consideration of majority output in this method, the system works by taking the nearest distance to the assigned number of K. The training data for this research was taken in March 2016 form the report of water monitoring result in PDAM’S laboratory of Surakarta. The identification result is divided into eligible (MS) and ineligible (TMS). The testing data result is applied in algorithm performance testing with confusion matrix having accuracy level 82,5%.

Keywords: water quality, K-Nearest Neighbor, Confusion matrix

Author Biography

Wawan Laksito Yuly Saptomo, STMIK Sinar Nusantara

Teknik Informatika

References

A. St-Hilaire, T. B. M. J. Ouarda, Z. Bargaoui, A. Daigle, and L. Bilodeau, “Daily river water temperature forecast model with a k-nearest neighbour approach,†Hydrol. Process., vol. 26, no. 9, pp. 1302–1310, 2012.

K. Liu, Z. Li, C. Yao, J. Chen, K. Zhang, and M. Saifullah, “Coupling the k-nearest neighbor procedure with the Kalman filter for real-time updating of the hydraulic model in flood forecasting,†Int. J. Sediment Res., vol. 31, no. 2, pp. 149–158, 2016.

H.-I. Eum, S. P. Simonovic, and Y.-O. Kim, “Climate Change Impact Assessment Using K-Nearest Neighbor Weather Generator: Case Study of the Nakdong River Basin in Korea,†J. Hydrol. Eng., vol. 15, no. 10, pp. 772–785, 2010.

R. I. Ndaumanu and M. R. Arief, “Analisis Prediksi Tingkat Pengunduran Diri Mahasiswa dengan Metode K-Nearest Neighbor,†JISATI, vol. 1, no. 1, pp. 1–15, 2014.

E. M. Elnahrawy, “Log-Based Chat Room Monitoring Using Text Categorization : A Comparative Study,†IASTED Int. Conf. Inf. Knowl. Shar. (IKS 2002), 2002.

G. Toker and Ö. Kırmemiş, “Text Categorization Using k-Nearest Neighbor Classification,†Middle East Tech. Univ., 2013.

Y. Liao and V. R. Vemuri, “Using Text Categorization Techniques for Intrusion Detection,†Proc. 11 th USENIX Secur. Symp., 2002.

F. Bajramovic, F. Mattern, N. Butko, and J. Denzler, “A comparison of nearest neighbor search algorithms for generic object recognition,†Adv. Concepts Intell. Vis. Syst., pp. 1186–1197, 2006.

A. . Rosa and A. Shalahuddin, Modul Pembelajaran Perangkat Lunak (Terstruktur dan Berorientasi Objek). Bandung: Modula, 2011.

T. Cover and P. Hart, “Nearest neighbor pattern classification,†IEEE Trans. Inf. Theory, vol. 13, no. 1, pp. 21–27, Jan. 1967.

M. Bramer, Principles of Data Mining, no. January 2007. London: Springer London, 2007.

K. Michelin, P. Jian, and H. Jiawei, “Data Mining: Concepts and Techniques,†vol. 278, pp. 6093–6100, 2003.

Downloads

Published

2018-04-17

Issue

Vol. 6 No. 1 (2018): Jurnal TiKomSiN

Section

Articles

Citation Check

License

Authors who publish with this journal agree to the following terms:

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
  • Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

 

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.