Penerapan Ant Colony Optimization Dengan Sentiment-Based Weighting Untuk Rekomendasi Rute Wisata Di Kota Makassar

Rizky Aditya Nugroho; Achmad Mufliq

doi:10.55382/jurnalpustakaai.v5i2.1197

Penulis

Rizky Aditya Nugroho Universitas Nahdlatul Ulama Sidoarjo
Achmad Mufliq Universitas Nahdlatul Ulama Sidoarjo

DOI:

https://doi.org/10.55382/jurnalpustakaai.v5i2.1197

Kata Kunci:

recommendation system, ant colony optimization, star rating, tourist route, Makassar City

Abstrak

Abstract

An effective and relevant tourist route recommendation system is essential to support tourists in making informed decisions when planning efficient and enjoyable trips. This study aims to develop a tourist route recommendation model for Makassar City by implementing a modified Ant Colony Optimization (ACO) algorithm that incorporates user star ratings as weighting factors. The research adopts a computational experimental quantitative approach, consisting of six main stages: identifying tourist destinations, collecting star rating data and estimated travel times between locations, calculating rating-based weights, implementing the ACO algorithm, and evaluating the resulting routes. The data used include star ratings of tourist destinations obtained from digital platforms and estimated travel times retrieved through online mapping services. The results indicate that the ACO model combined with rating-based weighting successfully generates routes that are more preferred by users, as they balance travel efficiency with the quality of destinations. Compared to conventional models that consider only travel time, this hybrid model delivers higher recommendation value in terms of user satisfaction. The proposed model can be applied in the development of intelligent tour guide applications to enhance tourists’ travel experiences. Furthermore, this study opens opportunities for future development by incorporating additional supporting variables to make the system more adaptive and context-aware.

Keywords: recommendation system, ant colony optimization, star rating, tourist route, Makassar City

Abstrak

Sistem rekomendasi rute wisata yang efektif dan relevan sangat dibutuhkan untuk mendukung pengambilan keputusan wisatawan dalam merencanakan perjalanan yang efisien sekaligus menyenangkan. Penelitian ini bertujuan untuk mengembangkan model rekomendasi rute wisata di Kota Makassar dengan mengimplementasikan algoritma Ant Colony Optimization (ACO) yang dimodifikasi dengan bobot berdasarkan rating bintang pengguna. Penelitian menggunakan pendekatan kuantitatif eksperimental berbasis komputasi dengan enam tahapan utama, mulai dari identifikasi destinasi wisata, pengumpulan data rating dan waktu tempuh antar lokasi, perhitungan bobot berbasis rating, implementasi ACO, hingga evaluasi hasil rute yang dihasilkan. Data yang digunakan meliputi rating bintang destinasi wisata dari platform digital serta estimasi waktu tempuh antar lokasi menggunakan layanan pemetaan daring. Hasil penelitian menunjukkan bahwa model ACO yang dikombinasikan dengan bobot rating mampu menghasilkan rute yang lebih disukai oleh pengguna karena menggabungkan efisiensi waktu dan kualitas destinasi. Dibandingkan dengan model konvensional yang hanya mempertimbangkan waktu tempuh, model hybrid ini memberikan nilai rekomendasi yang lebih tinggi dalam konteks kepuasan pengguna. Model yang dihasilkan dapat diimplementasikan dalam pengembangan aplikasi pemandu wisata berbasis sistem cerdas, khususnya untuk meningkatkan pengalaman perjalanan wisatawan. Penelitian ini juga membuka peluang untuk pengembangan lebih lanjut dengan menambahkan variabel-variabel pendukung lainnya agar sistem semakin adaptif dan kontekstual.

Kata kunci: sistem rekomendasi, ant colony optimization, rating bintang, rute wisata, Kota Makassar

Unduhan

Data unduhan belum tersedia.

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