Analisa Performa Metode Cosine Dan Jacard  Pada Pengujian Kesamaan Dokumen

Sugiyamto, Sugiyamto; Surarso, Bayu; Sugiharto, Aris

doi:10.14710/jmasif.5.10.8434

Cited by 3 publications

(1 citation statement)

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“…Jaccard Distance is a method used to calculate the level of similarity (similarity) between two objects. The following is the equation of the Jaccard Distance (Sugiyamto, Surarso, & Sugiharto, 2021).…”

Section: ∑ (1)mentioning

confidence: 99%

Clustering Analysis of Tweets About COVID-19 Using the K-Means Algorithm

Andi¹,

Juliandy²,

David³

2023

Sinkron

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One of the trending topics in 2020 to 2022 is tweets about Coronavirus Disease 2019 (COVID-19). A large number of tweets regarding COVID-19 that have appeared have been mixed and not grouped properly, making it difficult for Twitter users to read and sort them based on the information they want. One solution that can be applied to overcome the problems described is through clustering of tweets information about COVID-19. In this study, researchers used quantitative research with the K-Means method, which is one of the clustering methods used in grouping data. The data used in this study is a dataset taken from Kaggle, namely Omicron-Covid-19 Variant Tweets, and also taken through a scraping process with Bright Data with a total of 4,103 datasets. The results showed that determining the best cluster using the Elbow method on the dataset produced empirical evidence that the best cluster was k = 5. The results of grouping tweets regarding COVID-19 using the K-Means Clustering method with k = 5 resulted in the largest number of cluster members being cluster 4 with 1,185 tweets, the second largest was cluster 1 with 1,047 tweets, the third largest was cluster 2 with 757 tweets, the fourth largest was cluster 3 as many as 744 tweets, and the smallest number of cluster members is cluster 5 as many as 370 tweets.

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Section: ∑ (1)mentioning

confidence: 99%

Clustering Analysis of Tweets About COVID-19 Using the K-Means Algorithm

Andi¹,

Juliandy²,

David³

2023

Sinkron

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Comparative study for better result on query suggestion of article searching with MySQL pattern matching and Jaccard similarity

Rinartha

Suryasa

2017

2017 5th International Conference on Cyber and IT Service Management (CITSM)

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Personalized Information Retrieval from Friendship Strength of Social Media Comments

Majeed¹,

Yousaf²,

Shafiq³

et al. 2022

Intelligent Automation &Amp; Soft Computing

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Social networks have become an important venue to express the feelings of their users on a large scale. People are intuitive to use social networks to express their feelings, discuss ideas, and invite folks to take suggestions. Every social media user has a circle of friends. The suggestions of these friends are considered important contributions. Users pay more attention to suggestions provided by their friends or close friends. However, as the content on the Internet increases day by day, user satisfaction decreases at the same rate due to unsatisfactory search results. In this regard, different recommender systems have been developed that recommend friends to add topics and many other things according to the seeker's interests. The existing system provides a solution for personalized retrieval, but its accuracy is still a problem. In this work, we have proposed a personalized query recommendation system that utilizes Friendship Strength (FS) to recommend queries. For FS calculation, we have used the Facebook dataset comprising of more than 22k records taken from four different accounts. We have developed a ranking algorithm that provides ranking based on FS. Compared with existing systems, the proposed system can provide encouraging results. Key research groups and organizations can use this system for personalized information retrieval.

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Analisa Performa Metode Cosine Dan Jacard Pada Pengujian Kesamaan Dokumen

Cited by 3 publications

References 0 publications

Clustering Analysis of Tweets About COVID-19 Using the K-Means Algorithm

Clustering Analysis of Tweets About COVID-19 Using the K-Means Algorithm

Comparative study for better result on query suggestion of article searching with MySQL pattern matching and Jaccard similarity

Personalized Information Retrieval from Friendship Strength of Social Media Comments

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