ANDI WIJANARKO, NIM. 12651082 (2016)PENERAPAN DATA MINING UNTUK MENENTUKAN STRATEGI PROMOSI UNIVERSITAS PGRI YOGYAKARTA MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING. Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.
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Abstract
New admissions process of PGRI Yogyakarta University students generate data that are highly abundant in the form of student profile data. Based on it some hidden information could be known by doing data processing using that‟s profile‟s data and also obtaining useful information for university. Information that we get could be contribute for university as a consideration to decide new admissions promotion in the next year.This research aims to classify student data‟s into a cluster by utilizing Data Mining process using clustering techniques. The algorithm used for the cluster techniques is K-Means algorithm. K-Means is one method of non-hierarchical clustering of data that can group student data into several clusters based on the similarity of the data, so the data of students who have similar characteristics are grouped into one cluster and that have different characteristics grouped in another cluster. Atributes that used in this study is student‟s country, student‟s major in a high school, and GPA for two semesters with a value above 2,75.Cluster that formed after K-Means Algorithm process is three cluster with the first cluster amounted to 379 student data, second cluster amounted to 68 student data, and the third cluster amounted to 43 student data. Cluster with the highest average GPA is the first cluster. The results of this research are used for a making decision to determine promotion strategy based on clusters formed.
Item Type: | Thesis (Skripsi) |
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Additional Information / Pembimbing: | M. Didik R Wahyudi, S.T., MT. |
Uncontrolled Keywords: | student‟s major in a high school, country, GPA, K-Means Clustering, Data Mining, Universitas PGRI Yogyakarta. |
Subjects: | Tehnik Informatika |
Divisions: | Fakultas Sains dan Teknologi > Teknik Informatika (S1) |
Depositing User / Editor: | Miftahul Ulum [IT Staff] ---- youtube : ulum virgo -------- Facebook : digilibuin |
Date Deposited: | 06 Oct 2016 02:42 |
Last Modified: | 06 Oct 2016 02:42 |
URI: | http://digilib.uin-suka.ac.id/id/eprint/22268 |
Inilah Kumpulan Contoh Judul Proposal dan Skripsi Teknik Informatika yang saya perkirakan Mudah DIkerjakan oleh temen-temen mahasiswa teknik informatika yang sedang atau akan menyusun skripsi. Skripsi Teknik Informatika termasuk skripsi yang sangat sulit dan memerlukan referensi.
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Lokasi | : | DKI Jakarta (Bisa COD) |
Kondisi | : | Baru |
Posted on | : | 07-07-2015 01:48 |
Terjual | : | 0 barang telah terjual |
Dilihat | : | 2606 kali |
Last Sundul | : | 16 October 2015, 03:11:41 PM |
Penjelasan Produk
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UNTUK PAPER DENGAN SUB PENELITIAN DATA MINING LAINNYA DAPAT ORDER KEPADA KAMI. HANYA MELAYANI DARI ACM DAN IEEE EXPLORE.
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Data mining (Data Analysis)
Big Data / Analytics / Data Mining
Educational Data Mining
Data Warehousing and Data Mining
Distributed Data Mining
Spatial Data Mining (Data Mining)
Stream Mining (Data Mining)
Data Mining in Bioinformatics
Data Stream Mining
Data Mining Techniques
Data mining and Text mining
Temporal Data Mining
Data Mining – Concepts and Techniques
Database And Data Mining
Graph Data Mining
Spatio Temporal Data Mining (Data Mining)
Data Stream (Data Mining)
Privacy Preserving Data Mining
Data Mining and Business Intelligence
Data mining in Finance
Formal Concept Analysis (Data Mining)
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Banking data mining
Web Data Mining
Time Series Data Mining
Data Mining and Knowledge Discovery
Behaviour Data Mining
Data mining in Decision Support Systems
Business Analytics; Data Mining; Statistical Learning
Spatial data mining
Educational and Financial Data Mining
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Assessments (Educational Data Mining)
Web Mining, Social Network Analysis, Data Mining
Medical Data Mining
Data Mining Teknik Association Rule Dengan Teknik Algoritma Apriori
Domain Driven Data Mining
Semi-structured data mining
Data Mining for Business Intelligence
Xml Data mining
Future Trends in Data Mining
Data mining, Information Extraction, Deep Web
Data base systems and data mining
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Data Mining, Data Storage and duplication and Web Development.
Data Mining, Datawarehouse
Personalization, Data Minig, Web Usage Mining
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Hypergraphs, Graphs, Data Mining
Data Mining Programing
Financial data mining
Visual Data Mining
Data Mining in Water Resources Managment
Data Mining and Web Mining
On-Line data mining
Trajectory Data Mining
Data Mining and Data Warehousing
Machine Learning and Data Mining
Data mining in medical research
Agent Mining (Data Mining)
Intrusion Detection in Data Mining
Data Mining in Agriculture
Data Mining in Health Care
Data Mining in Image Processing
Application of data mining Techniques in Natural Resource
Data Mining and Neural Networks
Data Mining in Cloud Computing
Data Mining and Exploratory Data Analysis
Data Mining algorithms.
Combined Mining (Data Mining)
Semantic Web,Databases,Data mining
Data Mining (Archaeology)
Data mining and Warehousing
Data Mining Project Engineering - Data Mining Project Requirements Engineering - Knowledge Discovery - Knowledge Enginnering
Machine Learning & Data Mining In Pattern Recognition
Spatial & Temporal Data Warehousing and Mining
Social Security Data Mining
Data Mining in Metabolomics
Data Mining, Statistics, Structural Equation Modeling
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Learning History Data Mining
Multimedia and Data Mining
Data Mining In Healthcare
Data Mining in Higher Education
Data Mining Multimedia
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Data Mining, Semantic web
Spacial Data Mining
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