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All Journal Majalah Ilmiah Teknologi Elektro International Journal of Engineering and Emerging Technology
Kheri Arionadi Shobirin
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

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Evaluasi Pengembangan Disaster Recovery Center untuk Data Center Universitas Udayana Kheri Arionadi Shobirin; Nyoman Putra Sastra; Made Sudarma
Jurnal Teknologi Elektro Vol 20 No 1 (2021): (Januari - Juni ) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MITE.2021.v20i01.P20

Abstract

Data Center has a vital and strategic role in supporting university operations. Based on Government Regulation No.17 of 2019 article 20 section 1: Every Data Center owner must have a Disaster Recovery Center. Evaluation of Disaster Recovery Center Development for Udayana University Data Center conducted by considering aspects of natural threats, human threats, environmental threats, existing Data Center specification, virtualization, and cloud technology used to maintain the availability of Data Center services for Udayana University with the most efficient development costs. Using cost comparation for DRC development and operation for 3 years, found that implementation cost of Cloud DRC 3 times higher compare to Conventional DRC. High cloud computing cost contribute 67% of Cloud DRC cost structure.
Analysis of Shopping Cart At Drugs Store By Using An Apriori Algorithm Adi Panca Saputra Iskandar; Kheri Arionadi Shobirin; Komang Oka Saputra
International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

Competition in the business world in the pharmacy industry, demands the Pharmacist to determine a strategy that can increase drug sales. One way is to overcome the problems that occur in drugs store such as problems and sales of drug recommendations to suppliers who still use the prediction system of pharmacists. Data growth is less so utilized, data and information become useless like waste, sales strategy only as a little assumption without information and knowledge in server, consequently sales down and not range and items become expired and stock procurement is not according to market demand. Extracting data or an effort to retrieve valuable knowladge and information in a large database is called data mining or Knowledge Discovery in Database or usually shortened as KDD . One of the most popular algorithm in data mining technic is Apriori Algorithm, while the discovery of “relational combination pattertn among itemset used Assosiation Rules”. Data mining has been implemented into the various fields like : business or trade, education and telecommunication. In bussiness for instance, the implementation result of data mining use ‘algorithm Apriori which can give a hand to help the Businessmen make decision on supplies. For example, the necessity of supplies system in a drugstore as one of the mecical stuff supplier, and to determine which product as the priority should be supplied to anticipate out of stock of supplies availability in the store, as the results will also affect to the consumer service and daily income. Drugs are essential unit should be supplied and being and essential factor which will impact to the consumer trust to a hospital or another medical service. That is why the availability of medical drugs in drugstores is completely needed to support the succes of distribution to the consumers, so the activity of medical service to consumers run thoroughly. In this case, data mining is seen as able to buildt intelligent business environment as solution for competing increated compitition among the drugstores in future.
Data Warehouse Schemas using Multidimensional Data Model for Retail Kheri Arionadi Shobirin; Adi Panca Saputra Iskandar; Ida Bagus Alit Swamardika
International Journal of Engineering and Emerging Technology Vol 2 No 1 (2017): January - June
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

A data warehouse are central repositories of integrated data from one or more disparate sources from operational data in On-Line Transaction Processing (OLTP) system to use in decision making strategy and business intelligent using On-Line Analytical Processing (OLAP) techniques. Data warehouses support OLAP applications by storing and maintaining data in multidimensional format. Multidimensional data models as an integral part of OLAP designed to solve complex query analysis in real time.
Big Data Management Putu Suta Adya Dharma Rahadi; Kheri Arionadi Shobirin; Sri Ariyani
International Journal of Engineering and Emerging Technology Vol 1 No 1 (2016): July - December
Publisher : Doctorate Program of Engineering Science, Faculty of Engineering, Udayana University

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Abstract

In recent years, big data is a term representing large and complicated datasets that traditional data processing, including acquisition, pre-processing, storage, analytics, and visualization, etc, are not capable of tackling. Big data is a term that describes a large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. The usage of big data nowadays has deeply penetrated into various industries, such as e-commerce, retail, manufacturing, media, transportation, health-care, education, etc. In e-commerce, big data can be used in product ranking solution which offers solution to provide accurate information to the user based on their behavior when they are accessing any e-commerce website.
Co-Authors Ida Bagus A. Swamardika Iskandar, Adi Panca Saputra Komang Oka Saputra Made Sudarma Ni Wayan Sri Ariyani Nyoman Putra Sastra Putu Suta Adya Dharma Rahadi