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Journal : Jurnal Pilar Nusa Mandiri

OPTIMASI ALGORITMA VECTOR SPACE MODEL DENGAN ALGORITMA K-NEAREST NEIGHBOUR PADA PENCARIAN JUDUL ARTIKEL JURNAL Fauziah, Siti; Sulistyowati, Daning Nur; Asra, Taufik
Jurnal Pilar Nusa Mandiri Vol 15 No 1 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Maret 2
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (895.206 KB) | DOI: 10.33480/pilar.v15i1.27

Abstract

Articles is one part of the scientific work which was manifested in the form of writing and containing a lot of information that are requisite and suited therein to the exclusion of .Many small article day with allah is as a variety of sorts of the title and the methodology that was used , but does not make up for the possibility of a resemblance of the title of the article that is there is .This study aims to for determining the rate of a resemblance between an article of the american journal of public from the point of view of the title of the articles the american journal of public by the use of an algorithm of vector space the model and compare it with an algorithm k-nearest neghbour .The data used pt pgn promised to supply 10 the title of an article of the american journal of public keyword on information retrieval .Testing the data with of these keywords documents produced by the only by the magnitude of the resemblance of its on the highest a method of vsm it will be on a doc 5 , doc 7 , doc 8 and doc 4 .While for the program knn generate a level of the resemblance of its on range doc7 , doc10| doc8 , doc10| doc4 , d10| doc5 , doc10| doc3 , doc10. So that came to the conclusion that the occurrence of the addition of the criteria used to they obtain documents they do similaritas keyword after
KLASIFIKASI SELEKSI ATRIBUT PADA SERANGAN SPAM MENGGUNAKAN METODE ALGORITMA DECISION TREE Sudibyo, Aji; Asra, Taufik; Rifai, Bakhtiar
Jurnal Pilar Nusa Mandiri Vol 14 No 2 (2018): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Septemb
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1077.348 KB) | DOI: 10.33480/pilar.v14i2.31

Abstract

The Internet is very okay for right now, the Internet cannot be separated from its use of email, one of the threats that occur when using email is spam, spam is a message or email is unwanted by the recipient and sent in the masses.. Research on spam attacks are derived from the dataset as much spam 4601 records comprising 1813 records are considered spam and not spam data 278 with initial attributes as much as 57 attribute with attribute class 1, wants done on using select attribute with the decision tree becomes 15 attribute with attribute class 1 conducted 3 experiments testing with percentage attribute 30%, 50% and 70% select attribute obtained the results of the select attribute features of 70% better results were obtained from 30% or 50% with accuracy values of 92,469%.
SENTIMENT ANALYSIS ON GOJEK AND GRAB USER REVIEWS USING SVM ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION Hermanto, Hermanto; Kuntoro, Antonius Yadi; Asra, Taufik; Nurajijah, Nurajijah; Effendi, Lasman; Ocanitra, Ridatu
Jurnal Pilar Nusa Mandiri Vol 16 No 1 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1068.985 KB) | DOI: 10.33480/pilar.v16i1.1304

Abstract

Users of the Gojek and Grab application can provide reviews or comments about the application on Google Play. Reviews in the form of giving opinions about their satisfaction or dissatisfaction with the services provided. So with the many opinions provided, making people selective in choosing an online motorcycle taxi service provider. The application with the best review will be chosen by the community. In previous studies regarding the classification of online ojek service review using the Naïve Bayes algorithm, C.45 and Random Forest produced an unsatisfactory accuracy of 69.18% at the highest value. This study aims to determine the extent of the analysis of Gojek and Grab application user reviews based on user comments by classifying negative and positive reviews with a higher level of accuracy than previous studies so that applications with the best reviews can be known for public consideration in using the application's services. The method used for data review classification is using the Support Vector Machine (SVM) based on Particle Swarm Optimization (PSO). The test results on the Grab application review get the highest accuracy results in the amount of 73.09% with AUC value = 0.804, while for the test results on the application review Gojek get an accuracy value of 65.59% and AUC value = 0.680