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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) International Journal of Quantitative Research and Modeling SisInfo : Jurnal Sistem Informasi dan Informatika Nuansa Informatika Jurnal Bhakti Karya dan Inovatif Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)
Marwondo
Department Of Informatic, Faculty Of Technology And Informatic, Universitas Informatika Dan Bisnis Indonesia, Bandung, Indonesia.
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Physics Social Sciences Other

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Journal : International Journal of Quantitative Research and Modeling

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Data Cleansing Strategies on Data Sets Become Data Science Sardjono Sardjono; R. Yadi Rakhman Alamsyah; Marwondo Marwondo; Elia Setiana
International Journal of Quantitative Research and Modeling Vol 1, No 3 (2020)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (688.219 KB) | DOI: 10.46336/ijqrm.v1i3.71

Abstract

The digital era very grows up with the increasing using of smartphone and many organization or companies was implemented of a system to support their business. That is who will increase the volume of usage and dissemination of data, neither through open nor closed internet networks. Because there is the need to process large data and how to get it from different store resource, so requirement strategy to process the data according to the rule of good, effective and efficient in activity data cleansing until the data set can be use as mature and very useful information for their business purpose. By using the R languaged who can process large data and has data complexity for the data loaded from different storage resource can be done as well as. To using R languaged maximally, so we have to a basic skill that needed to process the data set which will be used to be data scient for organizations or companies by good data cleansing techniques. In this research on Data Cleansing Strategies on data set owned by organizations,will describe the correct step by step to obtaining data that very useful to be uses as data science for organization so by the data that generated after the data cleansing process is very meaningful and useful for making decisions, other than that this research give basic overview and guide to the beginner all data scientists by doing data cleansing in the way stages and also provides a way to analyze from the result of execution some functions used.
Co-Authors Alif Gufron Pratama Catherin Rumambo Mogot Pandin Elia Setiana Imannudin Akbar Iqbal Ardiansyah Iqbal Maulana Michael A. Yonathan Nugraha Nugraha R. Yadi Rakhman R. Yadi Rakhman R. Yadi Rakhman Alamsyah Santi Dwi Putri Sardjono Sardjono Sardjono Sardjono Sarjono Sarjono Seny Nurhasanah Titan Parama Yoga Ujang Riswanto Venia Retreva Danestiara Wahyu Kurnianto Wilner Saut Lamhot Wiyanudin