KLASIFIKASI OPPORTUNITY MENGGUNAKAN ALGORITMA C4.5, C4.5 DAN NAÏVE BAYES BERBASIS PARTICLE SWARM OPTIMIZATION

  • Endang Sri Palupi (1*) Sistem Informasi Universitas Bina Sarana Informatika
  • Said Mirza Pahlevi (2) Ilmu Komputer STMIK Nusa Mandiri

  • (*) Corresponding Author
Keywords: Algoritma C4.5, Naïve Bayes, Particle Swarm Optimization.

Abstract

Predicting an opportunity whether to be successful (buy) or not (no), with the aim to increase selling for target achievement of marketing. Marketing is required to find a good opportunity so that it can be a prospect of sales in great value and the long term. In this research, the dataset is taken from a CRM application (Customer Relationship Management) at PT. XYZ, sales of telesales team in January - March 2016. From these results, the PSO-based C4.5 algorithm has the highest accuracy and AUC value. In this research comparative algorithms C4.5, C4.5 based PSO, and Naïve Bayes using Confusion Matrix testing methods and ROC curves. The highest accuracy value using PSO-based C4.5 algorithm is 80,90% with AUC value 0.833 is good classification, next is Naïve Bayes based PSO algorithm with accuracy value equal to 83,15% and value of AUC 0,894 is good classification, the last C4.5 algorithm the lowest accuracy value of 66.67% with AUC 0.592 is failure classification. From these results, the PSO-based C4.5 algorithm has the highest accuracy.

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References

Budiman, I., Prahasto, T., & Christyono, Y. (2014). Data Clustering Menggunakan Metodologi CRISP-DM Untuk Pengenalan Pola Proporsi Pelaksanaan Tridharma. JURNAL SISTEM INFORMASI BISNIS. https://doi.org/10.21456/vol1iss3pp129-134

Fauziah, A. (2008). PELUANG INVESTASI EMAS ..., Anggriani Fauziah, HUKUM EKONOMI SYARIAH FAI, UMP 2016., 14–41.

Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques. Data Mining: Concepts and Techniques. https://doi.org/10.1016/C2009-0-61819-5

Hand, D. J. (2008). Data Mining: Methods and Models by D. T. Larose. Biometrics. https://doi.org/10.1111/j.1541-0420.2008.00962_9.x

Mujab, S. (2013). PENCARIAN MODEL TERBAIK ANTARA ALGORITMA C4.5 DAN C4.5 BERBASIS PARTICLE SWARM OPTIMIZATION UNTUK PREDIKSI PROMOSI DEPOSITO. Rancang Bangun E-CRM Pada Pasar Murah Solo, 1, 3–4.

Palupi, E. S., & Pahlevi, S. M. (2019). Laporan Akhir Penelitian Mandiri: Klasifikasi Opportunity Menggunakan Algoritma C4.5, C4.5 Dan Naïve Bayes Berbasis Particle Swarm Optimization. Jakarta.

Prabowo, A. D. R., & Muljono, M. (2018). Prediksi Nasabah Yang Berpotensi Membuka Simpanan Deposito Menggunakan Naive Bayes Berbasis Particle Swarm Optimization. Techno.Com. https://doi.org/10.33633/tc.v17i2.1648

Pratikto, F. R., & Wibisono, Y. Y. (2012). Analisis Customer Lifetime Value Terhadap Wholesale Customer Perusahaan Telekomunikasi Dengan Memperhitungkan Risiko Potensi Laba. Research Report - Engineering Science, 1. Retrieved from http://journal.unpar.ac.id/index.php/rekayasa/article/view/139

Ratelle, C. F., Larose, S., Guay, F., & Senécal, C. (2005). Perceptions of parental involvement and support as predictors of college students’ persistence in a science curriculum. Journal of Family Psychology. https://doi.org/10.1037/0893-3200.19.2.286

Santoso, T. B. (2015). Analisa Dan Penerapan Metode C4.5 Untuk Prediksi Loyalitas Pelanggan. CEUR Workshop Proceedings. https://doi.org/10.1017/CBO9781107415324.004

Saputra, E. H., & Muktamar, B. A. (2014). Implementasi Data Mining Dengan Naive Bayes Classifier Untuk Mendukung Strategi Pemasaran Di Bagian. Seminar Nasional Teknologi Informasi Dan Multimedia 2014.

Setiawan, H., Minarsih, M. M., Fathoni, A., Jurusan, M., Fakultas, M., Dan, E., … Ekonomika, F. (2016). PENGARUH KUALITAS PRODUK, KUALITAS PELAYANAN DAN KEPERCAYAAN TERHADAP KEPUASAN NASABAH DAN LOYALITAS NASABAH DENGAN KEPUASAN SEBAGAI VARIABEL INTERVENING ( Studi Kasus Pada Nasabah Koperasi Rejo Agung Sukses Cabang Ngaliyan ). Journal Of Management, 2(2). Retrieved from http://jurnal.unpand.ac.id/index.php/MS/article/view/492

Siegel, R., Naishadham, D., & Jemal, A. (2012). Cancer statistics, 2012. CA: A Cancer Journal for Clinicians. https://doi.org/10.3322/caac.20138

Siti, E. (2016). Penerapan Particle Swarm Optimization Untuk Seleksi Fitur Pada Analisis Sentimen Review Perusahaan Penjualan Online Menggunakan Naïve Bayes. Evolusi. https://doi.org/10.2311/evo.v4i1.276

So, I. G., & Sheila, S. (2011). Analisis Perancangan Customer Relationship Management Berbasis Web pada PT ASP Jakarta. Binus Business Review, 2(1), 100. https://doi.org/10.21512/bbr.v2i1.1115

Wang, X., & Bramer, M. (2007). Exploring Web search results clustering. In Research and Development in Intelligent Systems XXIII - Proceedings of AI 2006, the 26th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence. https://doi.org/10.1007/978-1-84628-663-6-30

Published
2020-02-01
How to Cite
Palupi, E., & Pahlevi, S. (2020). KLASIFIKASI OPPORTUNITY MENGGUNAKAN ALGORITMA C4.5, C4.5 DAN NAÏVE BAYES BERBASIS PARTICLE SWARM OPTIMIZATION. INTI Nusa Mandiri, 14(2), 233-238. https://doi.org/10.33480/inti.v14i2.1178
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