PEMANFAATAN DATA MINING DENGAN METODE CLUSTERING UNTUK EVALUASI BIAYA DOKUMEN EKSPOR DI PT WINSTAR BATAM
DOI:
https://doi.org/10.30865/mib.v1i2.322Abstract
Data Mining is a technology that already exists and grows long enough. Many companies are less use of old data stored in the database, to be used as much as possible. This research is trying to apply Data Mining technology by using the clustering method to get new knowledge, which is expected to be useful for the continuity and development of the company. The algorithm used is K-Means Clustering which is the process of grouping a number of data or objects into a cluster (group) so that each cluster will contain data that is as similar as possible and different from other cluster objects. Tests were performed with the Rapid Miner 5.3 application. The result is clustered clustering customer data suggested for the evaluation of the cost of processing the export documents.References
Alfina, T., Santosa, B. dan Barakbah, A.R. (2012).“Analisa Perbandingan Metode Hierarchical Clustering, K-Means Dan Gabungan Keduanya Dalam Cluster Data (studi kasus : problem kerja praktek jurusan teknik industri ITS)â€. Jurnal Teknik ITS.1. 521-525.
Pudjiantoro, T. H., Renaldi, F. dan Teogunadi, A. (2011).“Penerapan Data Mining Untuk Menganalisis Kemungkinan Pengunduran Diri Calon Mahasiswa Baruâ€. Konferensi Nasional Sistem dan Informatika. 51-60.
Lindawati.(2008).“Data Mining Dengan Teknik Clustering Dalam Pengklasifikasian Data Mahasiswa Studi Kasus Prediksi Lama Studi Mahasiswa Universitas Bina Nusantaraâ€. Seminar Nasional Informatika. 174-180.
Ediyanto, Mara, M.N. dan Satyahadewi, N. (2013). “Pengklasifikasian karakteristik Dengan Metode K-Means Cluster Analysisâ€. Buletin Ilmiah Mat.Stat, dan Penerapannya (Bimaster).2 (2). 133-136.
Rismawan, T.dan Kusumadewi, S. (2008).“Aplikasi K-Means Untuk Pengelompokan Mahasiswa Berdasarkan Nilai Body Mass Index (BMI) & Ukuran Kerangkaâ€. Seminar Nasional Aplikasi Teknologi Informatika. E43-E48.
Handoyo, R., Rumani, R. dan Nasution, S.M. (2014). â€Perbandingan Metode Clustering Menggunakan Metode Single Linkage Dan K-Means Pada Pengelompokan Dokumenâ€. JSM STMIK Mikroskil. 15 (2). 73-82.
Suprihatin. (2011). “Klastering K-Means Untuk Penentuan Nilai Ujianâ€. Jusi. 1 (1). 53-62. Ikhwan, A., Nofriansyah, D. dan Sriani. (2015). “Penerapan Data Mining Dengan Algoritma Fp- Growth Untuk Mendukung Strategi Promosi Pendidikan (Studi Kasus Kampus STMIK Triguna Dharma)â€. Jurnal Ilmiah SAINTIKOM. 14 (3). 211- 226.
Aravind, H.,C. Rajgopal. dan K.P. Soman. (2010).“A Simple Approach to Clustering in Excelâ€. International Journal of Computer Applications. 11 (7). 19-25.
Prasetyo, E. (2014).†Data Mining Mengolah Data Menjadi Informasi Menggunakan Matlabâ€. Yogyakarta : CV Andi Offset. Ong, J.O.(2013).“Implementasi Algoritma K-Means Clustering Untuk Menentukan Strategi Marketing Di President Universityâ€. Jurnal Ilmiah Teknik Industri. 12 (1). 10-20.
Tayal, M.A. dan Raghuwanshi, M.M. (2010). “Review on Various Clustering Methods for the Image Dataâ€. Journal of Emerging Trends in Computing and Information Sciences. 2. 34-38.
Ridwan, M., Suyono, H. dan Sarosa, M. (2013). “Penerapan Data Mining Untuk Evaluasi Kinerja Akademik Mahasiswa Menggunakan Algoritma Naive Bayes Classifierâ€. Jurnal EECCIS. 7 (1). 59-64.
Sharma, N., Bajpai, A. and Litoriya, R. (2012). “Comparison the various clustering algorithms of Weka Toolsâ€. International Journal of Emerging Technology and Advanced Engineering. 2 73-80.
Sidhu, N.K. and Kaur, R. (2013).†Clustering In Data Miningâ€. International Journal of Computer Trends and Technology (IJCTT). 4. 710-7014.
Krotha, R.S. and Merugula, S. (2013). â€A Brief Survey On Document Clustering Techniques Using MATLABâ€. International Journal of Computer & Organization Trends. 3. 1-6.
Sutrisno, Afriyudi, Widiyanto. (2013). â€Penerapan Data Mining Pada Penjualan Menggunakan Metode Clustering Study Kasus PT. Indomarco Palembangâ€. Jurnal Ilmiah Teknik Informatika Ilmu Komputer.10 (10). 1-11.
Oyelade, O. J., Oladipupo, O.O. and Obagbuwa, I.C. (2010).†Application of k-Means Clustering algorithm for prediction of Students’ Academic Performanceâ€. (IJCSIS) International Journal of Computer Science and Information Security. 7 (1). 292-295.
Sirait, T.H. dan Ong, J.O. (2011). â€Analisis Keberhasilan Mahasiswa dengan Metode Cluster ing K-Means.â€. SNASTIA. 1-6.
Ali, H. dan Wangdra, T.(2010). “Technopreneurship dalam perspektif bisnis onlineâ€. 1. Batam : Baduose Media. Mardiani. (2014).†Perbandingan Algoritma K-Means dan EM untuk Clusterisasi Nilai Mahasiswa Berdasarkan Asal Sekolahâ€. Citec Journal. 1 (4). 316-325.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International 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 Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment 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 acknowledgment 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 (Refer to The Effect of Open Access).
