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All Journal Jurnal IPTEK Jurnal Bisnis Digital dan Enterpreneur (BISENTER)
Arnoldus Janssen Dahur
Politeknik Negeri Tanah Laut
Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Industrial & Manufacturing Engineering Mechanical Engineering Social Sciences Other

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Lexicon-Based, Naïve Bayes, C4.5 for Analyzing Visitor Data Reviews as Recommendations for Priority Development of Labuan Bajo Tourism Arnoldus Janssen Dahur; Defitroh Chen Sami'un
Jurnal IPTEK Vol 29, No 2 (2025): December
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2025.v29i2.8178

Abstract

Labuan Bajo is one of Indonesia’s national priority destinations, known for its natural beauty and unique ecosystem. However, several issues raised by tourists—such as complaints regarding prices, infrastructure, and environmental cleanliness—may affect its image and tourism sustainability. This study aims to analyze tourist perceptions of Labuan Bajo based on 7,000 reviews from TripAdvisor and Google Maps obtained through web crawling. Sentiment labeling was conducted using a Lexicon-Based approach, while classification was performed using the Naïve Bayes and C4.5 algorithms, both with and without the Synthetic Minority Oversampling Technique (SMOTE). The results showed 4,374 positive, 2,769 negative, and 1,804 neutral reviews. Based on the CRISP-DM method, Naïve Bayes achieved the highest accuracy of 88%, compared to 78% for C4.5. Dominant positive terms such as beautiful, stunning, and sustainable highlight Labuan Bajo’s natural strengths, while negative terms like price, toilet, and trash indicate areas requiring improvement. The findings provide strategic recommendations to enhance tourism management and service quality toward sustainable tourism development.
Integrasi Computational Thinking dan Teori Graf untuk Pemecahan Masalah Mahasiswa Teknologi Rekayasa Komputer Jaringan Arwin Wahyu Saputra; Dewi Indra Anggraeni; Liny Mardhiyatirrahmah; Arnoldus Janssen Dahur; Dery Yuswanto Jaya; I Made Candra Girinata
Jurnal Bisnis Digital dan Enterpreneur (BISENTER) Vol. 4 No. 2 (2026): Jurnal Bisnis Digital dan Enterpreneur
Publisher : STMIK Amika Soppeng

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70247/bisenter.v4i2.357

Abstract

Problem-solving skills are essential competencies for Network Computer Engineering Technology students, particularly in Discrete Mathematics. This study examines the application of Computational Thinking (CT) and Graph Theory to support students’ problem-solving skills in Discrete Mathematics. Utilizing a systematic literature review, this research synthesizes findings from empirical and conceptual studies regarding CT integration in mathematics. The review indicates that CT's four pillars, decomposition, pattern recognition, abstraction, and algorithm design coherently align with Graph Theory elements such as vertex-edge representation, adjacency matrices, and routing algorithms. The reviewed empirical studies indicate that several CT-based learning interventions are associated with improvements in mathematical problem-solving, although their effectiveness varies according to instructional design and learning context. The study also identifies common conceptual difficulties in graph theory, which can be mitigated through a structured CT approach. Integrating CT and Graph Theory not only strengthens conceptual understanding but also prepares students for technical networking challenges. Descriptive data on students' learning achievements is presented as a contextual baseline, reinforcing the urgency of implementing this framework.
Co-Authors Arwin Wahyu Saputra Defitroh Chen Sami'un Dery Yuswanto Jaya Dewi Indra Anggraeni I Made Candra Girinata Liny Mardhiyatirrahmah