Development of Website Content

Oct 13, 2025 by magicalceylontours.com 126 views

Introduction

The rise of online gambling in Indonesia has become a significant concern for the government and the public. According to the 2021 criminal statistical data from BPS, there has been a substantial increase in gambling cases. Moreover, hundreds of public complaints are filed every month to Kominfo regarding websites with negative content, including gambling. The government has attempted to address this issue by implementing a negative content detection system called Trustpositive, but its effectiveness is still questionable. This study proposes a new method to build a more effective gambling website detection system, utilizing the Feature Extraction technique in the form of unigrams, bigrams, and trigrams as a reference in the classification process.

Background

Online gambling has become a widespread problem in Indonesia, with the government struggling to keep up with the rapid growth of online gambling websites. The emergence of new technologies and techniques has made it increasingly difficult for the government to detect and block access to these websites. The negative impact of online gambling on society is significant, including financial losses, addiction, and social problems. Therefore, it is essential to develop an effective system to detect and prevent online gambling websites.

Methodology

This study proposes a new method to build a more effective gambling website detection system. The system utilizes the Feature Extraction technique in the form of unigrams, bigrams, and trigrams as a reference in the classification process. The system receives a website URL as input, then takes content from the web page and predicts its category using two algorithms: Naive Bayes and Support Vector Machine. The results showed that the combination of feature extraction bigram and trigram with the naive bayes algorithm is effective in classifying websites. This system reached the precision and recall value of 99%, with an overall test score of 90%. This shows that this system is able to detect online gambling sites with a high level of accuracy.

Results

The results of this study demonstrate the effectiveness of the proposed system in detecting online gambling websites. The system achieved a high level of accuracy, with a precision and recall value of 99% and an overall test score of 90%. This suggests that the system is able to detect online gambling sites with a high level of accuracy. The results also indicate that the combination of feature extraction bigram and trigram with the naive bayes algorithm is effective in classifying websites.

Discussion

The development of the gambling website detection system is very important to protect the public from the negative impact of online gambling. By utilizing information Retrieval System and Natural Language Processing technology, this system can help the government in an effort to block access to websites that contain negative content. This study made a significant contribution in efforts to fight online gambling. The use of Machine Learning algorithms and techniques Feature Extraction proves that technology can help in overcoming complex social problems such as gambling.

Conclusion

In conclusion, this study proposes a new method to build a more effective gambling website detection system. The system utilizes the Feature Extraction technique in the form of unigrams, bigrams, and trigrams as a reference in the classification process. The results showed that the combination of feature extraction bigram and trigram with the naive bayes algorithm is effective in classifying websites. This system reached the precision and recall value of 99%, with an overall test score of 90%. This shows that this system is able to detect online gambling sites with a high level of accuracy. The development of the gambling website detection system is very important to protect the public from the negative impact of online gambling.

Recommendations

Some things that need to be considered in the development of this system are:

Development of Website Content

Online gambling websites continue to grow and use new techniques to avoid detection. Therefore, this system needs to be continuously updated and improved in order to remain effective.

Algorithm Development

The algorithm used needs to be evaluated and examined to increase the accuracy and effectiveness of the system.

Collaboration with Related Parties

Cooperation with Kominfo, Internet Service Providers, and other related parties are very important to ensure the success of this system.

Future Research Directions

With the continuing development of technology, it is hoped that this gambling website detection system can be an effective solution in protecting the public from the negative impact of online gambling. Future research directions include:

Improving the Accuracy of the System

Continuously updating and improving the system to increase its accuracy and effectiveness.

Expanding the Scope of the System

Expanding the scope of the system to detect other types of negative content, such as hate speech and cyberbullying.

Developing a More Effective Algorithm

Developing a more effective algorithm to increase the accuracy and effectiveness of the system.

Limitations of the Study

This study has some limitations, including:

Limited Dataset

The dataset used in this study is limited, which may affect the accuracy and effectiveness of the system.

Limited Scope

The scope of this study is limited to detecting online gambling websites, which may not be effective in detecting other types of negative content.

Limited Collaboration

The collaboration with related parties is limited, which may affect the success of the system.

Conclusion

Q: What is the main objective of this study?

A: The main objective of this study is to propose a new method to build a more effective gambling website detection system, utilizing the Feature Extraction technique in the form of unigrams, bigrams, and trigrams as a reference in the classification process.

Q: What is the significance of this study?

A: This study is significant because it proposes a new method to detect online gambling websites, which is a major concern for the government and the public. The study aims to develop an effective system to detect and prevent online gambling websites, which can help protect the public from the negative impact of online gambling.

Q: What are the key findings of this study?

A: The key findings of this study are:

The combination of feature extraction bigram and trigram with the naive bayes algorithm is effective in classifying websites.
The system reached the precision and recall value of 99%, with an overall test score of 90%.
The system is able to detect online gambling sites with a high level of accuracy.

Q: What are the limitations of this study?

A: The limitations of this study are:

The dataset used in this study is limited, which may affect the accuracy and effectiveness of the system.
The scope of this study is limited to detecting online gambling websites, which may not be effective in detecting other types of negative content.
The collaboration with related parties is limited, which may affect the success of the system.

Q: What are the recommendations for future research?

A: The recommendations for future research are:

Improving the accuracy of the system by continuously updating and improving the system.
Expanding the scope of the system to detect other types of negative content, such as hate speech and cyberbullying.
Developing a more effective algorithm to increase the accuracy and effectiveness of the system.

Q: What are the potential applications of this study?

A: The potential applications of this study are:

Developing an effective system to detect and prevent online gambling websites.
Protecting the public from the negative impact of online gambling.
Providing a framework for developing similar systems to detect other types of negative content.

Q: What are the implications of this study for policymakers and practitioners?

A: The implications of this study for policymakers and practitioners are:

The need to develop effective systems to detect and prevent online gambling websites.
The importance of collaboration with related parties to ensure the success of the system.
The need to continuously update and improve the system to increase its accuracy and effectiveness.

Q: What are the future directions for this research?

A: The future directions for this research are:

Improving the accuracy of the system by developing more effective algorithms.
Expanding the scope of the system to detect other types of negative content.
Developing a more effective system to detect and prevent online gambling websites.

Q: What are the potential challenges and limitations of this research?

A: The potential challenges and limitations of this research are:

The need to continuously update and improve the system to increase its accuracy and effectiveness.
The potential for online gambling websites to adapt and evade detection.
The need for collaboration with related parties to ensure the success of the system.

Q: What are the potential benefits of this research?

A: The potential benefits of this research are:

Developing an effective system to detect and prevent online gambling websites.
Protecting the public from the negative impact of online gambling.
Providing a framework for developing similar systems to detect other types of negative content.