Ubaidillah, Muhammad Afif
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Tourism Recommendation System in Bali Using Topsis and Greedy Algorithm Methods Ubaidillah, Muhammad Afif; Gede Dwidasmara, Ida Bagus
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 8 No 3 (2020): JELIKU Volume 8 No 3, February 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v08.i03.p09

Abstract

Tourism is the mainstay of the economy of the region of Bali and is an important sector in supporting the level of community welfare. The world of tourism is essentially an important symbol for Bali. Of the many tourists who come to Bali, of course not all tourists know all information about Bali, such as in terms of tourist locations, and tourist attractions closest to other tourist attractions. Therefore, the authors aim to create a recommendation system that can provide planning for the selection of tourist attractions according to the closest distance and the user's budget. This system is designed using the TOPSIS (Technique for Order Preference by Similarity To Ideal Solution) method and the Greedy Algorithm. The TOPSIS method is a SPK (Decision Making System) that will be used for the selection of tourist attractions that will help tourists to arrange vacation planning before going on a tour. While the Greedy Algorithm is used to find the closest or shortest distance between a tourist site and other tourist attractions, this algorithm will be able to determine which path will be taken first or called the local optimal path, so that all the paths are taken at the end of the trip and create a travel route shortest or called the global optimum so that it can also be the expected solution. From this it can be determined the value of the shortest travel route that starts from the location of the user's residence to the tourist attractions and to other nearby tourist attractions. The data used is data obtained from DISPARDA, namely tourist data. Research related to the selection of tourism object decisions based on the type of tourism, prices and facilities, and the results are able to provide recommendations for tourist attractions that meet these criteria. Tourism Selection Using Techniques For Order Preference By Similarity To Ideal Solution (Topsis) With Object Localization Visualization [4], Development of Decision Support System for Hotel Determination in Buleleng District Using Analytic Hierarchy Process (AHP) Method and Technique for Others Reference By Similarity To Ideal Solution (TOPSIS) [3], a Decision Support System for Determining Tourist Locations using the Top-sis Method [6]
Peringkas Teks Otomatis Berita Online Menggunakan Metode Cross Latent SemanticAnalysis & Cosine Similarity Ubaidillah, Muhammad Afif; Dwidasmara, Ida Bagus Gede; Muliantara, Agus
JELIKU (Jurnal Elektronik Ilmu Komputer Udayana) Vol 9 No 1 (2020): JELIKU Volume 9 No 1, Agustus 2020
Publisher : Informatics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JLK.2020.v09.i01.p11

Abstract

Ringkasan merupakan suatu cara yang efektif untuk meyajikan suatu karangan yang panjang dalam bentuk yang singkat. Walaupun bentuknya ringkas, namun ringkasan itu tetap memepertahankan pikiran pengarang dan pendekatannya yang asli. Namun dalam membuat ringkasan kita harus membaca berita atau artikel terlebih dahulu, sedangkan ringkasan dibuat dengan tujuan untuk meminimalkan waktu pembaca dan memberikan teks yang isinya langsung mengarah pada tujuan utama atau ide pokoknya. Pada penelitian ini memaparkan peringkasan teks otomatis berita online dari sebuah website menggunakan CLSA (Cross Latent Semantic Analysis) dan Cosine Similarity. Penelitian ini dilakukan untuk menguji seberapa baik hasil dan akurasi ringkasan yang dilakukan oleh CLSA dan cosine similarity. Penelitian ini menggunakan data sekunder dari berita dari media online yaitu web balipost.com dengan wilayah khusus Denpasar. Proses pengambilan data dilakukan dengan cara crawling. Data berita yang digunakan ialah sebanyak 161 berita, berita hasil ringkasan sistem nantinya akan dibandingkan dengan hasil ringkasan manual untuk mendapatkan akurasinya. Dari hasil pengujian yang dilakukan oleh sistem didapatkan nilai rata – rata akurasi F-Measure sebesar 58%, rata – rata Precision 62% dan rata – rata Recall 57%. Hasil dari penelitian peringkasan teks otomatis dari berita online dengan menggunakan metode CLSA dan cosine similarity memberikan hasil dan akurasi ringkasan yang cukup. Keywords : ringkasan, peringkas teks otomatis, crawling, CLSA, cosine similarity