IMPLEMENTASI TEXT MINING UNTUK ANALISIS PREFERENSI MASYARAKAT TERHADAP TEMPAT WISATA DI INDONESIA

Abstract

untuk meningkatkan daya tariknya. Untuk itu diperlukan informasi preferensi terkait suatu tempat wisata tertentu yang bisa didapat salah satunya dari media sosial Twitter menggunakan text mining . Pada penelitian ini telah dibuat aplikasi untuk melakukan analisis preferensi masyarakat terhadap tempat wisata di Indonesia dengan menerapkan text mining menggunakan analisis sentimen dan analisis faktor dengan studi kasus candi Borobudur dan candi Prambanan. Algoritma Naive Bayes Classifier (NBC) digunakan pada analisis sentimen, dan metode Principal Component Analysis (PCA) digunakan pada analisis faktor. Dari penelitian yang sudah dilakukan didapatkan hasil akurasi klasifikai sebesar 100% untuk topik candi Borobudur, 80.59% untuk topik candi Prambanan, dan 90.48% untuk akurasi rata-rata menggunakan ABSTRACT Tourism is one of Indonesia's leading sectors that needs to be maintained and developed to increase its attractiveness. For this reason, public preference information regarding a particular tourist spot that can be obtained is one of them from Twitter social media using text mining. In this study an application has been made to analyze people's preferences for tourist attractions in Indonesia by applying text mining using sentiment analysis and factor analysis with a case study of Borobudur temple and Prambanan temple. The Naive Bayes Classifier (NBC) algorithm is used in sentiment analysis, and the Principal Component Analysis (PCA) method is used in factor analysis. From the research that has been done, the results of classification are 100% for the topics of Borobudur temple, 80.59% for the topic of Prambanan temple, and 90.48% for the average accuracy using the NBC algorithm. The PCA method produced 10 positive factors and 7 negative factors for the topic of Borobudur temple, while for the topic of Prambanan temple there were 8 positive factors and 3 negative factors. All factors formed have been validated and interpreted by experts. It can be concluded if the application made can be used to find out information on people's preferences for tourist attractions in Indonesia.