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Big data analytic untuk pembuatan rekomendasi koleksi film personal menggunakan Mlib. Apache Spark

Berkala Ilmu Perpustakaan dan Informasi

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Title Big data analytic untuk pembuatan rekomendasi koleksi film personal menggunakan Mlib. Apache Spark
 
Creator Wahyudi, Indah Survyana
 
Subject Recommendation Engine; Big Data Analytic; ALS-WR; Cosine Similarity; Data Mining
 
Description Introduction. The digital age is characterized by the explosion of digital information that creates problems in information retrieval. Search engines have a weakness in the keywords/queries that users can remember. Recommendations arise as solutions to provide personal information. Data Collection Method. In this paper, the researcher presented a recommendation engine model using dataset from movielends.org.Analysis Data. Alternating Least Square-Weight Regulation (ALS-WR) was used as a big data analytic algorithm in rating prediction and Cosine Similiarity as the second filter to bring items closer to the genre. Results and Discussions.The results of  Root Mean Squared Error (RMSE) from 100K datasets were 0.96 (validation) and 0.94 (test). The results RMSE from 1M dataset were 0.86 (validation) and 0.96 (test). The results  RMSE from 10M dataset were 0.81 (validation) and 0.81 (test). The result cosine similarity was 1 for 100% resemblance and it  decreased based on the similarity level. The user acceptance test was 28% user accepts the result of first recommendation, this value increased to 62% acceptance level of the user against the second recommendation. Conclusions. The final results show that 75% of respondents prefer the second recommendation  from two-stage filtering than just collaborative filtering.  
 
Publisher UPT Perpustakaan Universitas Gadjah Mada
 
Contributor —
 
Date 2018-06-07
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier https://jurnal.ugm.ac.id/bip/article/view/32208
10.22146/bip.32208
 
Source Berkala Ilmu Perpustakaan dan Informasi; Vol 14, No 1 (2018): Juni; 11-25
2477-0361
1693-7740
 
Language eng
 
Relation https://jurnal.ugm.ac.id/bip/article/view/32208/21180
https://jurnal.ugm.ac.id/bip/article/downloadSuppFile/32208/3636
https://jurnal.ugm.ac.id/bip/article/downloadSuppFile/32208/3637
https://jurnal.ugm.ac.id/bip/article/downloadSuppFile/32208/3638
 
Rights Copyright (c) 2018 Berkala Ilmu Perpustakaan dan Informasi
http://creativecommons.org/licenses/by-sa/4.0
 


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