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All Journal Jurnal Teknologi Informasi dan Terapan (J-TIT) Jurnal Abdimas Indonesia : Jurnal Abdimas Indonesia
Candra Agustina
Universitas Bina Sarana Informatika, Jakarta, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Other

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Develompent of Machine Learning Model to Predict Hotel Room Reservation Cancellations Eka Rahmawati; Galih Setiawan Nurohim; Candra Agustina; Denny Irawan; Zainal Muttaqin
Jurnal Teknologi Informasi dan Terapan Vol 11 No 2 (2024): December
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v11i2.431

Abstract

The frequent cancellations of hotel room reservations have become a pressing issue for the hospitality industry, especially in high-tourism areas such as Borobudur, Indonesia. This research develops a predictive machine learning (ML) model to identify cancellation probabilities to support proactive decision-making for hotel management. Using datasets from Borobudur-based hotels, key variables such as booking lead time, arrival month, and reservation outcomes were analyzed. Random Forest demonstrated the best performance, achieving an accuracy of 86.36% with a precision of 88.06%, recall of 93.65%, and F1-score of 90.77%. Logistic Regression demonstrated moderate effectiveness, while Bayesian Networks underperformed, highlighting the importance of robust algorithms for such tasks. The findings underscore the potential of ML models, particularly Random Forest, to reduce financial losses and enhance operational efficiency in the hospitality sector by anticipating cancellations and facilitating better resource allocation
Clustering-based Machine Learning Approach For Predicting Tourism Trends From Social Media Behavior Candra Agustina; Eka Rahmawati
Jurnal Teknologi Informasi dan Terapan Vol 12 No 1 (2025): June
Publisher : Jurusan Teknologi Informasi Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/jtit.v12i1.443

Abstract

Digital technology has significantly transformed tourist behavior, particularly in searching for, selecting, and sharing travel experiences. Social media has become a primary source of information, influencing travel decisions through real-time recommendations and user-generated content. However, the large volume of data generated by social media presents challenges in understanding and predicting tourist behavior. This study aims to analyze tourist behavior patterns using a clustering-based machine learning approach, specifically K-Means Clustering. The research examines engagement levels on platforms such as Instagram, TikTok, and TripAdvisor to categorize tourists into three key segments: Digital-Savvy Travelers, Passive Travelers, and Conservative Travelers. The results indicate that machine learning effectively analyzes large-scale tourism data, providing valuable insights for destination marketing, personalized recommendations, and service optimization. The findings highlight the potential of machine learning to identify emerging trends, improve customer segmentation, and enhance targeted promotional strategies. Understanding these patterns enables tourism businesses to create data-driven strategies aligned with modern travel behaviors. In a broader perspective, artificial intelligence can revolutionize tourism marketing, increase customer engagement, and improve the overall travel experience
Pemanfaatan Aplikasi SITUBA Sebagai Inovasi Digital Pelaporan Kasus TBC oleh Kader dan Puskesmas di Kelurahan Nusukan Sardiarinto; Supriyanta; Candra Agustina; Wawan Nugroho; Sola Gracia Deo Andrew; Hani Yulia Rachma; Dehant Mahendra H
Jurnal Abdimas Indonesia Vol. 6 No. 1 (2026)
Publisher : Perkumpulan Dosen Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34697/jai.v6i1.2413

Abstract

Tuberkulosis (TBC) masih menjadi salah satu masalah kesehatan utama di Indonesia, termasuk di Kota Surakarta. Proses pelaporan kasus TBC di tingkat kelurahan selama ini masih dilakukan secara manual, sehingga sering menimbulkan keterlambatan dalam penyampaian data dan tindak lanjut pasien. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memperkenalkan dan menerapkan aplikasi digital SITUBA (Sistem Informasi Penanggulangan TBC) sebagai inovasi pelaporan kasus TBC di Kelurahan Nusukan, Kota Surakarta. Kegiatan dilaksanakan oleh tim dosen dan mahasiswa Universitas Bina Sarana Informatika Kampus Surakarta bekerja sama dengan Dinas Kesehatan Kota Surakarta dan Puskesmas Nusukan. Tahapan pelaksanaan meliputi sosialisasi kepada perangkat kelurahan, pelatihan penggunaan aplikasi bagi kader kesehatan, serta pendampingan dalam proses pelaporan kasus secara digital. Hasil kegiatan menunjukkan peningkatan pemahaman dan kemampuan kader dalam menggunakan aplikasi SITUBA untuk mencatat dan melaporkan data pasien secara lebih sistematis. Selain itu, sistem digital ini dinilai membantu mempermudah koordinasi antara kader, kelurahan, dan puskesmas dalam kegiatan pelacakan pasien TBC.Kesimpulannya, penerapan awal aplikasi SITUBA di Kelurahan Nusukan menunjukkan potensi positif dalam mempercepat alur pelaporan dan meningkatkan efisiensi koordinasi lintas pihak dalam upaya penanggulangan TBC berbasis masyarakat.
Co-Authors Dehant Mahendra H Denny Irawan Eka Rahmawati Galih Setiawan Nurohim Hani Yulia Rachma Sardiarinto Sola Gracia Deo Andrew Supriyanta Wawan Nugroho Zainal Muttaqin