Analisis Kinerja Metode Rough Set dan Algoritma Apriori Dalam Identifikasi Pola Penyakit Demam Tifoid
46
DAFTAR PUSTAKA
Adeyemo, O, O. Adeyeye, T, O & Ogunbiyi, O. 2015. Comparative Study of ID3/C4.5
Decision tree and Multilayer Perceptron Algorithms for the Prediction of
Typhoid Fever . Afr J. of Comp & ICTs. Vol 8, No. 1. ISSN 2006-1781:
103-112.
Ahok, A, S. & Sandeep, S, Jore. 2014. The Apriori Algorithm: Data Mining
Approaches Is To Find Frequent Items Set From A Transaction Dataset.
Ijirset ISSN 2319-8753: 210-214.
Berry, M. J. A. & Linoff, G. S. 2004. Data Mining Technique for maketing, sales
cutomer relationship management second editon, Wiley Publishing, Inc.
Budiono. Fahmi, A. Pujiono. 2014. Penerapan Metode Association Rule
Menggunakan Algoritma Apriori untuk Mengidentifikasi Pola Penyakit
Radang Sendi. Techno.COM. Vol 13 No 2. ISSN 2356-2579 : 115-124
Connolly, T. & Begg, C. 2004. Database System A Practical Approach to Design,
Implementation, and Management. Addison Wesley : England.
Frawley, J, W., Shapiro, P, G & Matheus, J, C. 1992. Knowledge Discovery in
Databases: An Overview. AI Magazine. 57-70.
Hakim, M, L & Rusli, M. 2013. Data Mining Menggunakan Metode Rough Set untuk
Menentukan Bakat Mahasiswa. Prosessor. ISSN 2089 – 628X : 5-11.
Jiawei, H & Kamber, M. 2006. Data Mining Concepts And Techniques. 2nd Edition.
Elsevier. Inc: San Fransisco.
Jiawei, H., Kamber, M & Pei, J. 2012. Data Mining Concepts And Techniques. 3nd
Edition. Elsevier. Inc: San Fransisco.
Kurniawati, S. 2015. Penerapan Metode Rough Set Pada Tingkat Kepuasan
Konsumen Terhadap Kualitas Pelayanan Hotel. Informasi dan Teknologi
Ilmiah (INTI). ISSN 2339-210X:138-142.
Li, T., Ruan, D., Wets, G., Song, J & Xu, Y. 2007. A Rough Sets Based Characteristic
Relation Approach For Dynimic Attribute Generalization . Knowledge
Based System 20 (5). 485-494.
Listiana, N. Anggraeni, W. & Muchlason, A. 2011. Implementasi algoritma rough set
untuk deteksi dan penanganan dini penyakit sapi. Jurnal Teknik ITS 1 :
A310-A315.
Universitas Sumatera Utara
47
Mi, J., Wu, W. & Zhang, W. 2004. Approaches to knowledge reduction based on
variable precision rough set model. Information Sciences 159 (2004) 255272.
Nahar, J., Tickle, S. & Ali, S. 2009. Significant Cancer Prevention Factor
Extraction: An Association Rule Discovery Approach. Springer Science:
353-367.
Oguntimilehin, A. Adetunmbi, A, O & Abiola, O, B. 2013. A Machine Learning
Approach to Clinical Diagnosis of Typhoid Fever . International Journal of
Computer and Information Technology 2 (04) : 671 – 676.
Pawlak, Z. 2002. Rough set and intelligent data analysis. Information Sciences 147 :
1-12.
Rohman. 2010. Distribusi Penyebaran Demam Typhoid Menurut Umur dan Gejala.
Prosiding Seminar Nasional Unimus. ISBN 978.979.704.883.9 : 88 – 90.
Thangavel, K., Qiang Shen. & Pethalakshmi, A. 2006. Application of Clustering for
Feature Selection Based on Rough Set Theory Approach. The
International Journal of Artificial Intelligence and Machine Learning
(AIML): 19-27.
Turban, E. Aronson, J, E & Liang, T. P. 2005. Decision Support Systems and
Intelligent Systems 7th. Prantice –Hall.Inc : New Jersey.
Widiastuti, D & Sofi, N. 2014. Analisis Perbandingan Algoritma Apriori dan FPGrowth pada Transaksi Koperasi. UG Jurnal. Vol 8 No 01 : 21-24.
Yin, X. & Han, J. 2003. CPAR: Classification based on Predictive Association
Rules, SIAM Int. Conf. on Data Mining (SDM’03), San Fransisco.
Universitas Sumatera Utara
DAFTAR PUSTAKA
Adeyemo, O, O. Adeyeye, T, O & Ogunbiyi, O. 2015. Comparative Study of ID3/C4.5
Decision tree and Multilayer Perceptron Algorithms for the Prediction of
Typhoid Fever . Afr J. of Comp & ICTs. Vol 8, No. 1. ISSN 2006-1781:
103-112.
Ahok, A, S. & Sandeep, S, Jore. 2014. The Apriori Algorithm: Data Mining
Approaches Is To Find Frequent Items Set From A Transaction Dataset.
Ijirset ISSN 2319-8753: 210-214.
Berry, M. J. A. & Linoff, G. S. 2004. Data Mining Technique for maketing, sales
cutomer relationship management second editon, Wiley Publishing, Inc.
Budiono. Fahmi, A. Pujiono. 2014. Penerapan Metode Association Rule
Menggunakan Algoritma Apriori untuk Mengidentifikasi Pola Penyakit
Radang Sendi. Techno.COM. Vol 13 No 2. ISSN 2356-2579 : 115-124
Connolly, T. & Begg, C. 2004. Database System A Practical Approach to Design,
Implementation, and Management. Addison Wesley : England.
Frawley, J, W., Shapiro, P, G & Matheus, J, C. 1992. Knowledge Discovery in
Databases: An Overview. AI Magazine. 57-70.
Hakim, M, L & Rusli, M. 2013. Data Mining Menggunakan Metode Rough Set untuk
Menentukan Bakat Mahasiswa. Prosessor. ISSN 2089 – 628X : 5-11.
Jiawei, H & Kamber, M. 2006. Data Mining Concepts And Techniques. 2nd Edition.
Elsevier. Inc: San Fransisco.
Jiawei, H., Kamber, M & Pei, J. 2012. Data Mining Concepts And Techniques. 3nd
Edition. Elsevier. Inc: San Fransisco.
Kurniawati, S. 2015. Penerapan Metode Rough Set Pada Tingkat Kepuasan
Konsumen Terhadap Kualitas Pelayanan Hotel. Informasi dan Teknologi
Ilmiah (INTI). ISSN 2339-210X:138-142.
Li, T., Ruan, D., Wets, G., Song, J & Xu, Y. 2007. A Rough Sets Based Characteristic
Relation Approach For Dynimic Attribute Generalization . Knowledge
Based System 20 (5). 485-494.
Listiana, N. Anggraeni, W. & Muchlason, A. 2011. Implementasi algoritma rough set
untuk deteksi dan penanganan dini penyakit sapi. Jurnal Teknik ITS 1 :
A310-A315.
Universitas Sumatera Utara
47
Mi, J., Wu, W. & Zhang, W. 2004. Approaches to knowledge reduction based on
variable precision rough set model. Information Sciences 159 (2004) 255272.
Nahar, J., Tickle, S. & Ali, S. 2009. Significant Cancer Prevention Factor
Extraction: An Association Rule Discovery Approach. Springer Science:
353-367.
Oguntimilehin, A. Adetunmbi, A, O & Abiola, O, B. 2013. A Machine Learning
Approach to Clinical Diagnosis of Typhoid Fever . International Journal of
Computer and Information Technology 2 (04) : 671 – 676.
Pawlak, Z. 2002. Rough set and intelligent data analysis. Information Sciences 147 :
1-12.
Rohman. 2010. Distribusi Penyebaran Demam Typhoid Menurut Umur dan Gejala.
Prosiding Seminar Nasional Unimus. ISBN 978.979.704.883.9 : 88 – 90.
Thangavel, K., Qiang Shen. & Pethalakshmi, A. 2006. Application of Clustering for
Feature Selection Based on Rough Set Theory Approach. The
International Journal of Artificial Intelligence and Machine Learning
(AIML): 19-27.
Turban, E. Aronson, J, E & Liang, T. P. 2005. Decision Support Systems and
Intelligent Systems 7th. Prantice –Hall.Inc : New Jersey.
Widiastuti, D & Sofi, N. 2014. Analisis Perbandingan Algoritma Apriori dan FPGrowth pada Transaksi Koperasi. UG Jurnal. Vol 8 No 01 : 21-24.
Yin, X. & Han, J. 2003. CPAR: Classification based on Predictive Association
Rules, SIAM Int. Conf. on Data Mining (SDM’03), San Fransisco.
Universitas Sumatera Utara