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All Journal Unisda Journal of Mathematics and Computer Science (UJMC) J-Icon : Jurnal Komputer dan Informatika
Rizka Safitri Lutfiyani
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Computer Science & IT Education Mathematics

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PERBANDINGAN ALGORITMA DJIKSTRA DAN WARSHALL DALAM PENENTUAN LINTASAN TERPENDEK KE KOTA KLATEN Niken Retnowati; Rizka Safitri Lutfiyani
Unisda Journal of Mathematics and Computer Science (UJMC) Vol 4 No 2 (2018): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department of Mathematics and Natural Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (676.572 KB) | DOI: 10.52166/ujmc.v4i2.1132

Abstract

Search for the shortest path is a problem that is faced when we want to travel or go somewhere. Klaten City is one of the cities in Central Java. Cities around Klaten include Boyolali. When we go to Klaten city there are several alternative roads or trails that can be chosen from Boyolali. Mathematically this condition can be applied in graphical form to find the shortest path to the city of Klaten. Determination of the shortest path can be found using the Djikstra Algorithm and the Warshall Algorithm. Researchers tried to compare the two methods to get the most optimal result. From the study concluded that the Djikstra algorithm is more effective than the Warshall algorithm for the shortest path from Boyolali to Klaten.
IMPLEMENTASI PENDETEKSIAN SPAM EMAIL MENGGUNAKAN METODE TEXT MINING DENGAN ALGORITMA NAÏVE BAYES DAN DECISION TREE J48 Rizka Safitri Lutfiyani; Niken Retnowati
J-ICON : Jurnal Komputer dan Informatika Vol 9 No 2 (2021): Oktober 2021
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v9i2.5304

Abstract

Email is quite popular as a digital communication media. This is because the message sending process via email is easy. Unfortunately, most messages in emails are spam emails. Spam is a message that the recipient of the message does not want because spam usually contains advertising messages or fraudulent messages. Ham is the message that the recipient wants. One way to sort these messages is to classify email messages into spam or Ham. Naïve Bayes and decision tree J48 are the algorithms that can be used to classify email messages. Therefore, this study aims to compare the effectiveness of the Naïve Bayes algorithm and decision tree J48 in sorting spam emails. The method used is text mining. Data containing the text of the email message in English will be processed before being classified with Naïve Bayes and decision tree J48. The pre-process stage includes tokenization, disposal of stop word lists, stemming, and attribute selection. Furthermore, Data text for email message will be processed using the Naïve Bayes algorithm and decision tree J48. The Naïve Bayes algorithm is a classification algorithm based on Bayesian Decision Theory, while the J48 decision tree algorithm is the development of the ID3 decision tree algorithm. The result of this research is that the decision tree J48 algorithm gets higher accuracy than the Naïve Bayes algorithm. The decision tree J48 algorithm has an accuracy of 93,117% while Naïve Bayes has an accuracy of 88,5284%. The conclusion of this study is that the decision tree J48 algorithm is superior to Naive Bayes for sorting spam emails when viewed from the level of accuracy of each algorithm.
Co-Authors Niken Retnowati Niken Retnowati