scholarly journals ANALISIS DATA MINING HOTEL BOOKING MENGGUNAKAN MODEL ID3

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Agus Budiyantara ◽  
Andreanus Kevin Wijaya ◽  
Anthony Gunawan ◽  
Michael Rolland
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Success Rate ◽  
Rapid Development ◽  
The Internet ◽  
Processing Data ◽  
The Future ◽  
Hotel Booking ◽  
Business Sectors

<em>The rapid development of information technology in this era makes it easier for someone to get information. Many business sectors are now promoting their products or services on the internet. An example is a hotel, in the technological era now we can easily find out about hotel information, ranging from location, price, and others. With the convenience to get information about this hotel, customers are indirectly increasing in a hotel. This of course causes the data contained in a hotel to increase as well. These data can be processed until we get an output and there is also data that is missing or cannot be processed. The data that can be processed can be analyzed until finally it becomes an information and prediction. In this journal, we will explain the Data Mining analysis in a hotel to analyze the success rate of a hotel. By doing this analysis, you will get insights about the level of success of the hotel and can also predict the future. Thus later the results of this analysis can be used by the hotel to assist in better decision making. Processing data in this study using the Rapid Miner application by entering data of customers who make hotel reservations</em>

scholarly journals Application of Data Mining Technology Based on Data Center

2022 ◽  
Vol 2146 (1) ◽  
pp. 012017
Author(s):  
Longjun Zhang ◽  
Kun Liu ◽  
Ilyar Ilham ◽  
Jiaxin Fan
Keyword(s):  
Data Mining ◽  
Computer Science ◽  
Data Center ◽  
Rapid Development ◽  
Research Field ◽  
The Internet ◽  
Test Results ◽  
Mining Technology ◽  
Processing Data ◽  
Definition Of

Abstract Data mining technology refers to the use of mathematics, statistics, computer science and other methods to process a large amount of information to obtain useful conclusions and provide valuable decisions for people. With the rapid development and popularization of the Internet era and the more and more extensive application of computers in various fields, data mining technology has become a hot research field in today’s society. Based on the data center, this paper studies the data mining technology. Firstly, this paper expounds the definition of data mining, and studies the process of data mining and the steps of processing data. Then, this paper also designs and studies the framework of data mining, and tests the performance of the algorithm. Finally, the test results show that data mining technology can well meet the target requirements.

Application of Data Mining Technology in Higher Education

2014 ◽  
Vol 574 ◽  
pp. 743-747
Author(s):  
Xiao Hong Liu
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Rapid Development ◽  
Complete Information ◽  
Focus Of Attention ◽  
Technical Support ◽  
Mining Technology ◽  
Information Platform

With the rapid development of information technology, many universities have a relatively complete information platform, and a mass of data resources. Faced a lot of data, how the data is rational used and developed, to accomplish the transformation of knowledge that provide managers with basis for decision making, has become the focus of attention in universities. Data mining technology provide technical support for achieving this goal.

scholarly journals Membangun Branding Produk UMKM Melalui Media Sosial Tiktok

2021 ◽  
Vol 4 (2) ◽  
pp. 280-289
Author(s):  
Lian Fawahan ◽  
Ita Marianingsih Purnasari
Keyword(s):  
Information Technology ◽  
Social Media ◽  
Human Activity ◽  
Digital Economy ◽  
The Internet ◽  
Market Segment ◽  
The Future ◽  
Qualitative Descriptive ◽  
Future Business ◽  
Internet Network

The occurrence of the Covid-19 pandemic  makes many MSMEs have to lose money and go out of business, whereas in Indonesia the most important joint that sustains the wheels of the country's economy is MSMEs. In addition to the pandemic, the challenge of MSMEs is rise of the digital economy movement is very  rapid  for making    MSMEs  demanded to understand information technology. The covid-19 pandemic is increasingly encouraging human activity through the internet network. One of the simplest steps to build a brand through TikTok social media. In  2020 number of downloads amounted to 63.3 million both in the Apple store and the play store the best-selling application is TikTok. Indonesia  is the downloader of the application amounting to 11% of the total downloads of tiktok application, with tiktok MSME actors can build their product brand, considering it does not require a lot of cost and energy. The potential of the wider market and the future business will also be a consideration because tiktok social media is widely used by millennials who have high consumptive power.  This study uses qualitative descriptive, uses literature studies quoted from book journals as well as relevant websites. The purpose of this study is to encourage MSMEs to have a good brand so that they can compete with other products, and through social media, especially TikTok, the MSME market segment can be wider internationally. Considering that social media has eliminated geography, meaning that when it can go viral social media, everyone can see MSME products. Keywords: MSMEs, Branding, TikTok

THE RESEARCH TREND OF INFORMATION TECHNOLOGY AND DECISION MAKING IN 2009

2010 ◽  
Vol 09 (01) ◽  
pp. 1-8 ◽  
Author(s):  
YONG SHI
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Decision Support ◽  
Risk Analysis ◽  
Multiple Criteria Decision Making ◽  
Advisory Board ◽  
Research Trend ◽  
Research Topics

The research topics of the 39 papers published in the International Journal of Information Technology and Decision Making (IT&DM) in 2009 can be classified into three major directions: decision support, multiple criteria decision making, and data mining and risk analysis. The Editor-in-Chief, on behalf of the editorial board and advisory board, highlights the key ideas of these contributions. The seven papers in first issue of 2010 IT&DM are also introduced.

Prediksi Tingkat Kelulusan Tepat Waktu Mahasiswa Menggunakan Algoritma Naïve Bayes pada Universitas XYZ

2020 ◽  
Vol 12 (2) ◽  
pp. 104-107
Author(s):  
Nurhayati . ◽  
Nuraeny Septianti ◽  
Nani Retnowati ◽  
Arief Wibowo
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Data Processing ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Bayes Method ◽  
Processing Data ◽  
Student Graduation ◽  
Phase Data ◽  
Bayes Algorithm

Data processing is imperative for the development of information technology. Almost any field of work has information about data. The data is made use of the analysis of the job. Nowadays, information data is imperatively processed to help workers in making decisions. This study discusses student prediction graduation rates by using the naïve Bayes method. That aims at providing information to college if they can use it properly to utilize the data of students who graduated by processing data mining. Based on the data mining process, steps founded that used producing information, namely predicting student graduation on time. The method of this study is Naïve Bayes with classification techniques. At this study, researchers used a six-phase data mining process of industry crossing standards in data mining known as CRISP-DM. The results of research concluded that the application of the Naive Bayes algorithm uses 4 (four) parameters namely ips, ipk, the number of credits, and graduation by getting an accuracy value of 80.95%.

Organizational Data Mining (ODM)

2011 ◽  
pp. 1-8
Author(s):  
Hamid R. Nemati ◽  
Christopher D. Barko
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Competitive Advantage ◽  
Current Status ◽  
Decision Making Process ◽  
Actionable Knowledge ◽  
The Core ◽  
Mining Tools

An increasing number of organizations are struggling to overcome “information paralysis” — there is so much data available that it is difficult to understand what is and is not relevant. In addition, managerial intuition and instinct are more prevalent than hard facts in driving organizational decisions. Organizational Data Mining (ODM) is defined as leveraging data mining tools and technologies to enhance the decision-making process by transforming data into valuable and actionable knowledge to gain a competitive advantage (Nemati & Barko, 2001). The fundamentals of ODM can be categorized into three fields: Artificial Intelligence (AI), Information Technology (IT), and Organizational Theory (OT), with OT being the core differentiator between ODM and data mining. We take a brief look at the current status of ODM research and how a sample of organizations is benefiting. Next we examine the evolution of ODM and conclude our chapter by contemplating its challenging yet opportunistic future.

scholarly journals Maintaining the Role of Humans in the Forecast Process: Analyzing the Psyche of Expert Forecasters

2007 ◽  
Vol 88 (12) ◽  
pp. 1893-1898 ◽  
Author(s):  
Neil A. Stuart ◽  
David M. Schultz ◽  
Gary Klein
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Weather Forecasting ◽  
Time Constraints ◽  
Learning Gap ◽  
Weather Forecasters ◽  
The Future ◽  
Mental Modeling ◽  
And Training

The Second Forum on the Future Role of the Human in the Forecast Process occurred on 2–3 August 2005 at the American Meteorological Society's Weather Analysis and Forecasting Conference in Washington, D.C. The forum consisted of three sessions. This paper discusses the second session, featuring three presentations on the cognitive and psychological aspects of expert weather forecasters. The first presentation discussed the learning gap between students (goal seekers) and teachers (knowledge seekers)—a similar gap exists between forecasters and researchers. In order to most effectively train students or forecasters, teachers must be able to teach across this gap using some methods described within. The second presentation discussed the heuristics involved in weather forecasting and decision making under time constraints and uncertainty. The final presentation classified the spectrum of forecasters from intuitive scientists to the disengaged. How information technology can best be adapted so as not to inhibit intuitive scientists from their mental modeling of weather scenarios is described. Forecasters must continuously refine their skills through education and training, and be aware of the heuristic contributions to the forecast process, to maintain expertise and have the best chance of ensuring a dynamic role in the future forecast process.

CURRENT RESEARCH TREND: INFORMATION TECHNOLOGY AND DECISION MAKING IN 2008

2009 ◽  
Vol 08 (01) ◽  
pp. 1-5 ◽  
Author(s):  
YONG SHI
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information Technology ◽  
Decision Analysis ◽  
Credit Scoring ◽  
Advisory Board ◽  
Research Trend ◽  
Web Based ◽  
Mining Methods ◽  
New Research

On behalf of the editorial advisory board of the International Journal of Information Technology and Decision Making (IT&DM), the Editor-in-Chief reviews the current research trend of this journal based on all the papers published in 2008. They are web-based decision analysis, credit scoring techniques and new data mining methods which combine both decision-making techniques and information technology tools. In addition, the Editor-in-Chief summarizes the key ideas of contributions in this new issue that may contain new research trend of IT&DM in 2009.

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