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Data Driven Smart Tourism Management: A Literature Review on System Integration, Digital Tourist Journey, and UMKM Connectivity in Smart Cities Sherly Agustini; Okta Veza; Nofri Yudi Arifin; Albertus Laurensius Setyabudhi
Engineering and Technology International Journal Vol 8 No 01 (2026): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/eatij.v8i01.1239

Abstract

The rapid development of smart city initiatives has significantly transformed the tourism sector through the adoption of digital technologies and data-driven systems. This study aims to analyze the development of data-driven smart tourism management by focusing on system integration, digital tourist journey, and UMKM connectivity within smart city environments. A Systematic Literature Review (SLR) method was employed to examine 30 relevant articles published between 2020 and 2025. The findings indicate that most studies utilize similar methodological approaches but are applied to different research objects, resulting in fragmented research outcomes. Furthermore, the lack of integration among systems and limited involvement of UMKM in digital platforms remain major challenges in developing effective smart tourism ecosystems. This study highlights the need for integrated, interoperable, and scalable smart tourism systems supported by advanced technologies such as artificial intelligence, big data analytics, and Internet of Things (IoT). The results of this study provide a conceptual foundation and research directions for developing more comprehensive and sustainable smart tourism systems in smart city contexts.
Analisis Efisiensi Distribusi Last Mile Delivery Berbasis Genetic Algorithm pada E-Commerce Albertus Laurensius Setyabudhi
Engineering and Technology International Journal Vol 8 No 01 (2026): Engineering and Technology International Journal (EATIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/eatij.v8i01.1264

Abstract

Penelitian ini mengkaji penerapan Algoritma Genetika (Genetic Algorithm/GA) untuk mengoptimalkan distribusi last mile delivery pada platform e-commerce di Batam, Indonesia. Last mile delivery mencakup 41–53% dari total biaya logistik, menjadikannya komponen kritis dalam rantai pasok. Penelitian menggunakan kerangka Vehicle Routing Problem with Time Windows (VRPTW) dengan data empiris dari 847 titik pengiriman yang dikumpulkan selama enam bulan dari tiga perusahaan e-commerce lokal. GA diimplementasikan dengan operator tournament selection, Order Crossover (OX) (pᶜ=0,85), inversion mutation (pₘ=0,02), dan elitisme 10% pada populasi N=150, generasi T=500. Hasil menunjukkan GA mereduksi total jarak 23,7% (847,3 km → 647,1 km/hari), mengurangi kendaraan aktif 18,4%, meningkatkan on-time delivery dari 78,3% menjadi 93,8%, dan menghemat biaya Rp2.340.000/hari. GA unggul 9,2% atas Clarke-Wright Savings Algorithm dalam total jarak (Wilcoxon p=0,0023, r=0,52). Konvergensi rata-rata dicapai pada generasi ke-312 dengan nilai fitness 0,8734. Temuan ini mengkonfirmasi GA sebagai metaheuristik efektif untuk VRPTW pada konteks kepulauan Indonesia.