Pengklasteran Jenis Barang Dan Daerah Tujuan Yang Sering Dikirim Ke PT.Pos Indonesia Cabang Binjai Metode Clustering

 (*)Randatul Hasanah Mail (STMIK Kaputama, Binjai, Indonesia)
 Hotler Manurung (STMIK Kaputama, Binjai, Indonesia)
 Mili Alfhi Syari (STMIK Kaputama, Binjai, Indonesia)

(*) Corresponding Author

Abstract

Technological developments are widely used by various companies to support acceleration in their business processes, one of which is an online shop that uses technology to send goods ordered by buyers. The POS office is one of many companies that provide goods delivery services. Delivery of goods made must go through a registration process to record the goods to be sent. Reports on the results of registration data every month are only stored as archives. Data mining is one of the data processing techniques which is a process to find useful information and the pattern can be used as a supporting tool in decision making in developing a business. The K-Means algorithm is a simple algorithm for classifying or grouping projects with certain attributes in clusters. Clustering is a data analysis method, which is often included in data mining methods to group data.

Keywords


Business, Clustering, Data Mining, Reports, K-Means



Article Metrics

Abstract view : 162 times

References

Johan Oscar Ong, Jurnal Ilmiah Teknik Industri, vol. 12, p. 1, juni 2013.

Sri Mulyati, Prosiding Seminar Ilmiah Nasional Teknologi Komputer, vol. 1, no. Padang, p. 2, oktober 2015.

Asroni, Jurnal Ilmiah Semesta Teknika, vol. 18, Magelang, p. 3, maret 2015.

Elly muningsih, jurnal bianglala informatika, vol. 3, Yogyakarta, p. 4, maret 2015.

Guntur Setiawan, implementasi dalam birokrasi pembangunan, bandung, p. 5, 2002.

Jiawei dan Kamber, Micheline han, data mining, p. 6, 2006.

Budi Santosa, data mining teknik pemanfaatan data untuk keperluan bisnis, Yogyakarta, p. 7, 2007.

Luthfiq Emha Kusrini, algoritma data mining, Yogyakarta, p. 8, 2009.

Dominikus Juju Feri Sulianta, Data mining meramalkan bisnis perusahaan, jakarta, p. 9, 2010.

Juan santana finn lee, data mining:meramalkan bisnis perusahaan, no. jakarta, p. 11, 2010.

Abu Bakar dan Wibowo Arif, akuntansi keuangan dasar2, jakarta, p. 12, 2008.

Oliviera, pendekatan partisi dan clustering, p. 13, 2007.

Bian S.,et.al Everitt, Cluster Analisys, p. 14, 2011.

Brian S.,et.al Everitt, Cluster Analisys 5th Edition, p. 15, 2011.

Everitt et al, agglomerative clustering, p. 16, 2011.

Adi Nugroho, analisa dan perancangan, no. bandung, p. 17.

Haviluddin, Unified modelling language, p. 18, 2011.

Bila bermanfaat silahkan share artikel ini

Berikan Komentar Anda terhadap artikel Pengklasteran Jenis Barang Dan Daerah Tujuan Yang Sering Dikirim Ke PT.Pos Indonesia Cabang Binjai Metode Clustering

Refbacks

  • There are currently no refbacks.


Copyright (c) 2022 Randatul Hasanah, Hotler Manurung, Mili Alfhi Syari

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


Jurnal PELITA INFORMATIKA: INFORMASI DAN INFORMATIKA
Published by STMIK Budi Darma
Email: pelitainformatika.stmikbd@gmail.com
Journal is licensed under a Creative Commons Attribution 4.0 International License