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All Journal Jurnal Teknologi dan Manajemen Informatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Agrokreatif Jurnal Ilmiah Pengabdian kepada Masyarakat ILKOM Jurnal Ilmiah Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Nasional Cosphi Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer (BALOK)
Kartika Chandra Pelangi
Universitas Ichsan Gorontalo
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering

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Sistem Prediksi Jumlah Wisatawan Di Lambangan Pauno Desa Kendek Menggunakan Metode Support Vector Machine Hermawan, Tamsil; Yasin Aril Mustofa; Kartika Chandra Pelangi
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 3 No 1 (2024): Mei 2024
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v3i1.772

Abstract

Abstrac- Banggai Laut is regency rich in agricultural products and marine beauty.  One of the very famous tourist attractions in Banggai Laut is Lambangan Pauno Beach. Lambangan Pauno Beach is one of the beachside tourist attractions at Kendek in Banggai Utara Subdistrict, which is 10 km from Banggai City. Lambangan Pauno is a very representative tourist attraction because it can be reached by car or motorbike. It extends for about 200 meters with clean white sand, coral rocks, cliffs, and Ketapang trees, fencing on the left and right ends of the beach, making the view beautiful.  Lambangan Pauno has become a tourist spot in Banggai Laut often visited by tourists. Tourist visits have increased drastically due to many factors, including competitive travel costs and the number of adequate travel routes. It is supported by facilities that make visitors comfortable and guarantee security. Based on the research results, it is found that the research categorization produced by SVM is very good. It is proven by the test results which produce an accuracy rate of 90%. Keywords: prediction system, number of tourists, SVM
Analisis Sentimen Objek Wisata Di Kabupaten Banggai Laut Menggunakan Metode Naive Bayes Fatmawati; Husdi; Kartika Chandra Pelangi; Rofiq Harun
Jurnal Ilmiah Ilmu Komputer Banthayo Lo Komputer Vol 3 No 1 (2024): Mei 2024
Publisher : Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37195/balok.v3i1.882

Abstract

Abstract - are carried out and a place to have fun for a long time to achieve satisfaction, enjoy good service, and bring home beautiful memories of the tourist attractions. In Banggai Laut Regency, many tourist attractions are attractive for tourism activities. The number of visitors increases every year. The discussion about tourist attractions in Banggai Laut Regency is interesting to the local community. There are a lot of public comments about the tourist attractions in Banggai Laut. The number of opinions about tourist attractions in Banggai Laut makes it difficult to determine the sentiment of the comments manually. Therefore, sentiment analysis is required to classify the comments and whether or not they tend to be positive. In this case, this study employs the Naïve Bayes algorithm to classify the problems. Based on the sentiment analysis, it is proven that the Naïve Bayes method or algorithm can classify comments with good results. The accuracy generated in this sentiment analysis is 87%, with a division of training data of 90% and test data of 10%. The acquisition of these accuracy results indicates that the proposed algorithm has a Fairly Good diagnostic level. Keywords: sentiment analysis, tourist attraction, Naïve Bayes
Co-Authors Abd. Rahmat Karim Haba Apriyanto Alhamad Fatmawati Fatmawati Hermawan, Tamsil Husdi Iftinan Inayah Mohamad Irvan A. Salihi Maryam Hasan Muh Faisal Nurhayati Olii Rofiq Harun Sudirman S. Panna Tri Handayani Yasin Aril Mustofa Yulianti Lasena