scholarly journals Prediksi Tingkat Ketersediaan Stock Sembako Menggunakan Algoritma FP-Growth dalam Meningkatkan Penjualan

2020 ◽  
pp. 67-73
Author(s):  
Rahmad Aditiya ◽  
Sarjon Defit ◽  
Gunadi Widi Nurcahyo
Keyword(s):  
Association Rule ◽  
Large Data ◽  
Grocery Stores ◽  
Data Sets ◽  
Data Mining Technique ◽  
Transaction Data ◽  
Relationship Of ◽  
Purchasing Patterns ◽  
The Relationship ◽  
North Sumatra

Large data sets can be processed to become useful information, one of the data that can be processed is sales transaction data at UD. Smart Aliwansyah, which will become important information to increase sales. This study aims to find the pattern of product purchases to predict the level of availability of staple foods so as to increase sales. The data that is processed in this study uses the sales transaction data of goods obtained from the sales invoice of UD. Smart Aliwansyah, North Sumatra Tax Village. Based on these data, with the provision that a minimum of 2 types of goods in 1 transaction is examined using a data mining technique in association with the FP-Growth algorithm with a confidence value of 75% and a minimum support of 20%. The tools used by Rapidminer 9.4 are to obtain product purchasing patterns which are used as information to predict the level of stock availability. The result of the sales data processing process is the association rule. Association Rule is obtained in the form of a relationship between goods sold together with other goods in a transaction. From this pattern, it can be recommended to the shop owner as information for preparing basic food stocks to increase sales results. This research is very suitable to be applied to determine the patterns of consumer spending such as the relationship of each item purchased by consumers, so this research is appropriate for use by grocery stores.

From data to knowledge mining

2009 ◽  
Vol 23 (4) ◽  
pp. 427-441 ◽  
Author(s):  
Ana Cristina Bicharra Garcia ◽  
Inhauma Ferraz ◽  
Adriana S. Vivacqua
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Evaluation Criteria ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Data Mining Technique ◽  
Mining Technique ◽  
Data Points

AbstractMost past approaches to data mining have been based on association rules. However, the simple application of association rules usually only changes the user's problem from dealing with millions of data points to dealing with thousands of rules. Although this may somewhat reduce the scale of the problem, it is not a completely satisfactory solution. This paper presents a new data mining technique, called knowledge cohesion (KC), which takes into account a domain ontology and the user's interest in exploring certain data sets to extract knowledge, in the form of semantic nets, from large data sets. The KC method has been successfully applied to mine causal relations from oil platform accident reports. In a comparison with association rule techniques for the same domain, KC has shown a significant improvement in the extraction of relevant knowledge, using processing complexity and knowledge manageability as the evaluation criteria.

NILAI KERJA DITINJAU DARI ETNIS BATAK TOBA PADA ANGGOTA SATUAN BRIGADE MOBILE KEPOLISIAN DAERAH SUMATERA UTARA

2019 ◽  
Vol 4 (1) ◽  
pp. 8-14
Author(s):  
Debi Angelina Br. Barus
Keyword(s):  
Work Values ◽  
Quantitative Description ◽  
The North ◽  
Work Value ◽  
Toba Batak ◽  
Relationship Of ◽  
The Relationship ◽  
North Sumatra

This study aims to determine the relationship of work values with the Batak Toba ethnic. This research was conducted at the Mobile Brigade Unit of the North Sumatra Regional Police. The subjects in this study were 45 people. This study uses a quantitative description approach. The results of the study are to find that hamoraon, hagabeon and hasangapon (3H) are in line with the principle of the work value of Brimob members. 3H is the peak achievement of individual Toba Batak ethnic work value in the mobile brigade unit of the North Sumatra regional police. Keyword: Work value, Batak Toba Etnic   Penelitian ini bertujuan untuk mengetahui hubungan nilai kerja dengan etnis Batak Toba. Penelitian ini dilakukan di Satuan Brigade Mobile Kepolisian Daerah Sumatera Utara. Subjek dalam penelitian ini adalah 45 orang. Penelitian ini menggunakan pendekatan kuantitatif deskripsi. Hasil penelitian adalah menemukan bahwa hamoraon, hagabeon dan hasangapon (3H) sejalan dengan prinsip nilai kerja pada satuan anggota Brimob. 3H merupakan puncak pencapaian dari nilai kerja individu yang beretnis Batak Toba di satuan brigade mobile kepolisian daerah Sumatera Utara. Kata Kunci: Nilai kerja, Etnis Batak Toba

The Theoretical and Empirical Research on Pricing of China's Carbon Emission Permits

2012 ◽  
Vol 524-527 ◽  
pp. 2474-2481
Author(s):  
Zhi Gang Huang ◽  
Jiao Ling Xie ◽  
Wen Ping Wu
Keyword(s):  
Option Pricing ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Supply And Demand ◽  
Practical Significance ◽  
Emission Permits ◽  
Transaction Data ◽  
Carbon Finance ◽  
Relationship Of ◽  
The Relationship

Carbon emissions permits has its own particularity,and with the development of carbon finance,carbon emissions permits possess the commodity attributes and financial attributes.So its price isn’t determined only by the relationship of commodity supply and demand,but also affected by a variety of factors.But because the transaction data is not available,so the pricing of the carbon emissions permits can not really consider from the angle of the influencing factors of price.Therefore, this paper is on the basis of previous studies using mathematical tools and introducing the option pricing mechanism to study th pricing of China's carbon emissions permits basing on carbon emissions,which is designed for providing reference on the pricing of China's carbon emissions,being of both theoretical and practical significance.

scholarly journals The Relationship of Maternal Health Conditions on the Utilization of Maternity Waiting Homes for Maternity Motherhood

2020 ◽  
Vol 2 (1) ◽  
pp. 220-230
Author(s):  
Zufrizal ◽  
Ida Yustina ◽  
Asfriyati
Keyword(s):  
Maternal Health ◽  
Health Conditions ◽  
Regional Government ◽  
Cross Sectional ◽  
Government Program ◽  
Maternity Waiting Homes ◽  
Cross Sectional Design ◽  
Relationship Of ◽  
The Relationship ◽  
North Sumatra

Maternity Waiting Homes is a regional government program that aims to reduce maternal mortality. But in reality, there are still many people who do not utilize this facility. The purpose of this study is to determine the relationship of maternal health conditions on the utilization of maternity waiting homes for maternity motherhood. This research is an explanatory survey research with cross sectional design. The study was conducted in Langkat Regency, North Sumatra. The results showed that there was a relationship between maternal health conditions and the utilization of the maternity waiting house for maternity motherhood in Langkat Regency (p = 0.027).

scholarly journals Algorithm and Simulation of Association Rules of Drug Relationship Based on Network Model

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Hui Teng ◽  
Yukun Ma ◽  
Di Teng
Keyword(s):  
Decision Making ◽  
Network Model ◽  
Association Rules ◽  
Association Rule ◽  
Simulation Analysis ◽  
Pharmaceutical Research ◽  
Accurate Analysis ◽  
Systematic Analysis ◽  
Relationship Of ◽  
The Relationship

Studying drug relationships can provide deeper information for the construction and maintenance of biomedical databases and provide more important references for disease treatment and drug development. The research model has expanded from the previous focus on a certain drug to the systematic analysis of the pharmaceutical network formed between drugs. Network model is suitable for the study of the nonlinear relationship of the pharmaceutical relationship by modeling the data learning. Association rule mining is used to find the potential correlations between the various sets of massive data. Therefore, based on the network model, this research proposed an algorithm for drug interaction under improved association rules, which achieved accurate analysis and decision-making of drug relationship. Meanwhile, this research applied the established association rule algorithm to discuss the relationship between Chinese medicine and mental illness medicine and conducted the algorithm research and simulation analysis of the association relationship. The results showed the association rule algorithm based on the network model constructed was better than other association algorithms. It had reliability and superiority in decision-making in improving the drug-drug relationship. It also promoted the rational use of medicines and played a guiding role in pharmaceutical research. This provides scientific research personnel with research basis and research ideas for disease-related diagnosis.

scholarly journals Bought and Sold: Exploring the Effects of Big Data on User Agency and Commodification

2021 ◽  
Author(s):  
Kristia M. Pavlakos
Keyword(s):  
Social Sciences ◽  
Big Data ◽  
Data Privacy ◽  
Large Data ◽  
Data Sets ◽  
Privacy Regulation ◽  
Scholarly Literature ◽  
User Interests ◽  
The Social ◽  
The Relationship

Big Data1is a phenomenon that has been increasingly studied in the academy in recent years, especially in technological and scientific contexts. However, it is still a relatively new field of academic study; because it has been previously considered in mainly technological contexts, more attention needs to be drawn to the contributions made in Big Data scholarship in the social sciences by scholars like Omar Tene and Jules Polonetsky, Bart Custers, Kate Crawford, Nick Couldry, and Jose van Dijk. The purpose of this Major Research Paper is to gain insight into the issues surrounding privacy and user rights, roles, and commodification in relation to Big Data in a social sciences context. The term “Big Data” describes the collection, aggregation, and analysis of large data sets. While corporations are usually responsible for the analysis and dissemination of the data, most of this data is user generated, and there must be considerations regarding the user’s rights and roles. In this paper, I raise three main issues that shape the discussion: how users can be more active agents in data ownership, how consent measures can be made to actively reflect user interests instead of focusing on benefitting corporations, and how user agency can be preserved. Through an analysis of social sciences scholarly literature on Big Data, privacy, and user commodification, I wish to determine how these concepts are being discussed, where there have been advancements in privacy regulation and the prevention of user commodification, and where there is a need to improve these measures. In doing this, I hope to discover a way to better facilitate the relationship between data collectors and analysts, and user-generators. 1 While there is no definitive resolution as to whether or not to capitalize the term “Big Data”, in capitalizing it I chose to conform with such authors as boyd and Crawford (2012), Couldry and Turow (2014), and Dalton and Thatcher (2015), who do so in the scholarly literature.

Visual Data Mining for Discovering Association Rules

2008 ◽  
pp. 2105-2120
Author(s):  
Kesaraporn Techapichetvanich ◽  
Amitava Datta
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Large Data ◽  
Data Sets ◽  
Visual Data Mining ◽  
Useful Knowledge ◽  
Large Databases ◽  
A New Technique ◽  
Mining Association Rule

Both visualization and data mining have become important tools in discovering hidden relationships in large data sets, and in extracting useful knowledge and information from large databases. Even though many algorithms for mining association rules have been researched extensively in the past decade, they do not incorporate users in the association-rule mining process. Most of these algorithms generate a large number of association rules, some of which are not practically interesting. This chapter presents a new technique that integrates visualization into the mining association rule process. Users can apply their knowledge and be involved in finding interesting association rules through interactive visualization, after obtaining visual feedback as the algorithm generates association rules. In addition, the users gain insight and deeper understanding of their data sets, as well as control over mining meaningful association rules.

scholarly journals Personalized web search on e-commerce using ontology based association mining

2017 ◽  
Vol 7 (1.1) ◽  
pp. 286
Author(s):  
B. Sekhar Babu ◽  
P. Lakshmi Prasanna ◽  
P. Vidyullatha
Keyword(s):  
Data Mining ◽  
Web Search ◽  
Large Data ◽  
Association Mining ◽  
Data Sets ◽  
Data Mining Algorithm ◽  
Web Data ◽  
Data Mining Technique ◽  
Web Data Mining ◽  
The Web

 In current days, World Wide Web has grown into a familiar medium to investigate the new information, Business trends, trading strategies so on. Several organizations and companies are also contracting the web in order to present their products or services across the world. E-commerce is a kind of business or saleable transaction that comprises the transfer of statistics across the web or internet. In this situation huge amount of data is obtained and dumped into the web services. This data overhead tends to arise difficulties in determining the accurate and valuable information, hence the web data mining is used as a tool to determine and mine the knowledge from the web. Web data mining technology can be applied by the E-commerce organizations to offer personalized E-commerce solutions and better meet the desires of customers. By using data mining algorithm such as ontology based association rule mining using apriori algorithms extracts the various useful information from the large data sets .We are implementing the above data mining technique in JAVA and data sets are dynamically generated while transaction is processing and extracting various patterns.

Visual Data Mining for Discovering Association Rules

2011 ◽  
pp. 209-226
Author(s):  
Kesaraporn Techapichetvanich ◽  
Amitava Datta
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Association Rule ◽  
Large Data ◽  
Data Sets ◽  
Visual Data Mining ◽  
Useful Knowledge ◽  
Large Databases ◽  
A New Technique ◽  
Mining Association Rule

Both visualization and data mining have become important tools in discovering hidden relationships in large data sets, and in extracting useful knowledge and information from large databases. Even though many algorithms for mining association rules have been researched extensively in the past decade, they do not incorporate users in the association-rule mining process. Most of these algorithms generate a large number of association rules, some of which are not practically interesting. This chapter presents a new technique that integrates visualization into the mining association rule process. Users can apply their knowledge and be involved in finding interesting association rules through interactive visualization, after obtaining visual feedback as the algorithm generates association rules. In addition, the users gain insight and deeper understanding of their data sets, as well as control over mining meaningful association rules.

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