Analysis Of Association Rules Predictions Using CT-Pro Algorithms And Hash-Based Algorithms In Violence In Children

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Analysis of Association Rules Predictions Using CT-Pro Algorithms and Hash-Based Algorithms in Violence in Children

Introduction

Violence against children is a serious problem that affects many communities around the world. In North Sumatra, the incidence of violence against children is relatively high, and it can be carried out by various parties, including parents, family members, close people in the home environment, and foreigners. The police play an important role in handling the phenomenon of crime against children and trying to reveal various criminal acts that may occur. One method that can be used is through analytical techniques that explore certain habits that are often related to acts of violence.

The Problem of Association Rule Analysis

One approach used to carry out this analysis is the association rule technique. This technique focuses on the search for items that often appear or known as frequent itemsets. However, a priori algorithm commonly used has significant weaknesses in terms of performance, especially when dealing with large databases. This weakness lies in the need to read the database repeatedly, which causes the processing time to be very long in producing support and confidence values.

The Need for Alternative Approaches

To overcome this problem, an alternative approach is needed in the analysis of association rules. Two alternative approaches that can be used are the CT-Pro and Hash-Based algorithms. The CT-PRO algorithm utilizes the CFP-Tree data structure, which allows the process of searching for frequent itemsets to take place faster, thanks to the reduction in the number of trajectories (trajectories) or tree that is built. On the other hand, hash-based uses hashing techniques to speed up the process, where database scanning is only carried out in the first iteration to enter the itemset candidate into the hash table.

CT-Pro Algorithm

The CT-Pro algorithm is a new approach to association rule analysis that uses the CFP-Tree data structure. This data structure allows the process of searching for frequent itemsets to take place faster, thanks to the reduction in the number of trajectories (trajectories) or tree that is built. The CT-Pro algorithm has been shown to be more efficient than the a priori algorithm, especially when dealing with large databases.

Hash-Based Algorithm

The Hash-Based algorithm is another alternative approach to association rule analysis. This algorithm uses hashing techniques to speed up the process, where database scanning is only carried out in the first iteration to enter the itemset candidate into the hash table. The Hash-Based algorithm has been shown to be more efficient than the a priori algorithm, especially when dealing with large databases.

Test Results

Test results with 3% support parameters and 15% confidence show that the CT-PRO algorithm is able to produce 22 rules in the execution time of 0.25 seconds, while the Hash-Based algorithm also produces 22 rules but with an execution time of 0.73 seconds. This shows the superiority of CT-PRO in terms of processing efficiency of processing time.

New Crime Pattern

Furthermore, this analysis managed to find a new crime pattern with the highest confidence and support. The pattern indicates that in the case of acts of sexual harassment, there is a high possibility that physical actions of torture will also occur. With confidence reaching 59% and support of 34, as well as a 1.29 elevator ratio, this finding can be an important indicator for the police and the authorities in formulating the prevention and handling strategies of violence against children.

Conclusion

Through the use of the CT-Pro and Hash-Based algorithms, it is hoped that this analysis can make a real contribution in efforts to reduce and uncover cases of violence against children in North Sumatra. In addition, this research is the first step to introduce new techniques in data analysis that has the potential to increase the effectiveness of responses to crime in the community.

Recommendations

Based on the findings of this research, the following recommendations can be made:

  • The police and the authorities should use the CT-Pro and Hash-Based algorithms to analyze data related to violence against children.
  • The police and the authorities should use the new crime pattern found in this research to formulate prevention and handling strategies of violence against children.
  • Further research should be conducted to explore the potential of the CT-Pro and Hash-Based algorithms in other areas of crime analysis.

Limitations

This research has several limitations, including:

  • The data used in this research is limited to North Sumatra, and it may not be representative of other regions.
  • The CT-Pro and Hash-Based algorithms may not be suitable for all types of data, and further research is needed to explore their potential in other areas of crime analysis.

Future Research Directions

Future research directions include:

  • Exploring the potential of the CT-Pro and Hash-Based algorithms in other areas of crime analysis.
  • Developing new techniques in data analysis that can increase the effectiveness of responses to crime in the community.
  • Conducting further research to explore the potential of the CT-Pro and Hash-Based algorithms in other regions.

References

  • [1] [Author's Name], [Year]. [Title of the Paper]. [Journal Name], [Volume], [Issue], [Pages].
  • [2] [Author's Name], [Year]. [Title of the Paper]. [Journal Name], [Volume], [Issue], [Pages].
  • [3] [Author's Name], [Year]. [Title of the Paper]. [Journal Name], [Volume], [Issue], [Pages].

Appendix

The appendix includes additional information that is not included in the main body of the paper, such as:

  • Additional test results
  • Additional data analysis
  • Additional references

Note: The references and appendix are not included in this response as they are not provided in the original text.
Q&A: Analysis of Association Rules Predictions Using CT-Pro Algorithms and Hash-Based Algorithms in Violence in Children

Q: What is the main goal of this research?

A: The main goal of this research is to analyze the effectiveness of the CT-Pro and Hash-Based algorithms in predicting association rules related to violence against children in North Sumatra.

Q: What are the CT-Pro and Hash-Based algorithms?

A: The CT-Pro algorithm is a new approach to association rule analysis that uses the CFP-Tree data structure to speed up the process of searching for frequent itemsets. The Hash-Based algorithm uses hashing techniques to speed up the process, where database scanning is only carried out in the first iteration to enter the itemset candidate into the hash table.

Q: What are the advantages of using the CT-Pro and Hash-Based algorithms?

A: The CT-Pro and Hash-Based algorithms have several advantages, including:

  • Faster processing time
  • Ability to handle large databases
  • Ability to find new crime patterns

Q: What are the limitations of this research?

A: The limitations of this research include:

  • The data used in this research is limited to North Sumatra, and it may not be representative of other regions.
  • The CT-Pro and Hash-Based algorithms may not be suitable for all types of data, and further research is needed to explore their potential in other areas of crime analysis.

Q: What are the implications of this research for law enforcement and policymakers?

A: The implications of this research for law enforcement and policymakers include:

  • The use of the CT-Pro and Hash-Based algorithms to analyze data related to violence against children
  • The use of new crime patterns found in this research to formulate prevention and handling strategies of violence against children

Q: What are the future research directions for this topic?

A: The future research directions for this topic include:

  • Exploring the potential of the CT-Pro and Hash-Based algorithms in other areas of crime analysis
  • Developing new techniques in data analysis that can increase the effectiveness of responses to crime in the community
  • Conducting further research to explore the potential of the CT-Pro and Hash-Based algorithms in other regions

Q: How can readers get more information about this research?

A: Readers can get more information about this research by:

  • Contacting the author of this paper
  • Searching for related papers and articles on academic databases
  • Visiting the website of the research institution that conducted this study

Q: What are the potential applications of this research in real-world settings?

A: The potential applications of this research in real-world settings include:

  • Law enforcement agencies using the CT-Pro and Hash-Based algorithms to analyze data related to violence against children
  • Policymakers using new crime patterns found in this research to formulate prevention and handling strategies of violence against children
  • Researchers using the CT-Pro and Hash-Based algorithms to explore new areas of crime analysis

Q: What are the potential benefits of using the CT-Pro and Hash-Based algorithms in crime analysis?

A: The potential benefits of using the CT-Pro and Hash-Based algorithms in crime analysis include:

  • Faster and more accurate analysis of data
  • Ability to find new crime patterns and trends
  • Ability to inform prevention and handling strategies of crime

Q: What are the potential challenges of using the CT-Pro and Hash-Based algorithms in crime analysis?

A: The potential challenges of using the CT-Pro and Hash-Based algorithms in crime analysis include:

  • Difficulty in implementing and using the algorithms
  • Limited availability of data and resources
  • Potential for bias and error in the analysis

Q: How can readers stay up-to-date with the latest developments in this research area?

A: Readers can stay up-to-date with the latest developments in this research area by:

  • Following the author of this paper on social media
  • Subscribing to academic journals and databases related to crime analysis
  • Attending conferences and workshops related to crime analysis