PENERAPAN ALGORITMA C.45 UNTUK MEMPREDIKSI INDIKATOR WEBSITE YANG BAIK
DOI:
https://doi.org/10.33884/jif.v6i02.545Keywords:
Decision tree, Algoritma C.45, Website, indikatorAbstract
The website for a company for now is not just a trend but it is a necessity that absolutely must not be, because with the website all the general information of the company can be shared to its customers directly tampa must be hampered by time and distance. as an example for a particular class of customers can find the information he wants without having to come directly keperusahaan. For that a website must contain important information about the company, the website should be able to represent customer service if asked by customers about company information related to customer needs. In this journal will be discussed one website of the company with 7 (seven) indicators, then of the seven indicators will be seen which indicators most influential on the website itself, this is certainly in the direction of customer satisfaction using the website. so it seems that the existing indicators have different effects between each other. To make this happen the researcher uses clustering method by using algortima C.45 with WEKA software version 44.02. The expected results will be to help the company in the process of developing a better website again.
References
[2] Benni R Suburian, 2014, Aplikasi Data Mining Untuk Menampilkan Tingkat Kelulusan Mahasiswa Dengan Algoritma Apriori. Teknik Informatika STMIK Budi Darma Medan.
[3] Chen Rung-Ching, Cheng Kai-Fan and Hsieh Chia-Fen Hsieh. 2009. Using rough set and support vector Machine for network intrusion detection. Taiwan: Department of Information Management Chaoyang University of Technology Taichung Country.
[4] Eki Roziqa Maris, 2017, Analisis Kepuasan Pelanggan Menggunakan Algoritma C4, Semarang, Program Studi Teknik Informatika Universitas Nurswantoro Semarang
[5] Ferdy Feridian Haryanto, 2017, Penerapan Algoritma C4.5 Untuk Memprediksi Penerimaan Calon Pegawai Pada PT WISE, Program Studi Teknik Informatika Universitas Multi Media Nusantara, Tanggerang Banten.
[6] Gunadi Widi Nurcahyo, 2008. Penerapan Data Mining dengan Algoritma Apriori untuk Mendukung Strategi Promosi Pendidikan. Universitas Putra Indonesia “YPTK” Padang Sumatera Barat
[7] Ginanjar Angga Mabrur dan Riani Lubis. 2012. Penerapan data mining untuk memprediksi kriteria nasabah kredit. Bandung: Program Studi Teknik Informatika Fakultas Teknik dan Ilmu Komputer Universitas Komputer Indonesia.
[8] Harman Rika 2017, Penerapan Data Mining Menggunakan Algoritma C.45 Untuk Menentukan Kelayakan Penerima Uang dan Beras Pada Perumahan Taman Hangtuah Batam Kota.
[9] Harman Rika 2017, Penerapan Algortima C.45 untuk pembelian Laptop, Sistem Informasi Universitas Putera Batam.
[10] Ivandari, 2015, Model Keputusan Untuk Klasifikasi Persetujuan Kredit Menggunakan Algoritma C4.5, Jurnal Litbang Kota Pekalongan.
[11] Jumanto, 2014. Implementasi Data Mining Algoritma C.45 Untuk Memprediksi Perilaku Mahasiswa Dilploma 3 Melanjutkan Strata 1 Di STMIK AMIKOM Yogyakarta. STMIK AMIKOM Yogyakarta.
[12] Kumar Soumen Pati and Asit Kumar Das. 2013. Constructing minimal spanning tree based on rough set theory for gene selection. Department of Computer Science/Information Technology.
[13] Larissa Maharani, 2015, Klasifikasi Nasabah Bank Menggunakan Algoritma C4.5 Sebagai Dasar Pemberian Kredit, Padang Fakultas Ilmu Komputer Universitas Putera Indonesia Padang.
[14] Liliana Swastina, 2013, Penerapan Algortima C4.5 Untuk Penentuan JurusanMahasiswa, Banjarmasin, Program Teknik Informatika STMIK Indonesia Banjarmasin.
[15] Muchamad Piko Henry Widiarto, 2011. Pengambilan Pola Kelulusan Tepat Waktu Pada Mahasiswa STMIK AMIKOM Yogyakarta Menggunakan Data Mining Algoritma C. 45. STMIK AMIKOM Yogyakarta.
[16] Nordin. M.A Rahman, et al. 2011. Applying Rough Set Theory in Multimedia Data Classification. Malaysia: Universiti Sultan Zainal Abidin.
[17] Nurhayati. 2014. Metode rough set untuk melihat perilaku suami yang menjadi akseptor kb vasektomi. Sumatera Utara: Program Studi Teknik Informatika, STMIK Kaputama Binjai.
[18] Sucipto Adi. 2015. Prediksi kredit macet melalui perilaku nasabah Pada koperasi simpan pinjam dengan menggunakan Metode algoritma klasifikasi c4.5. Fakultas Sains dan Teknologi UNISNU Jepara.
[19] Tripathy B. K, et al. 2011. A framework for intelligent medical diagnosis using rough set with formalconcept analysis. India: School of Computing Science and Engineering, VIT University.
[20] Sukma Putri Utari,2015. Implementasi Metode C.45 Untuk Menentukan Guru Terbaik Pada SMK 1 Percut Sei Tuan Medan. Teknik Informatika STMIK Budi Darma Medan
