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Google Classroom Learning Media Acceptance and Use Analysis Using Technology Acceptance Model (TAM) Indyah Hartami Santi
International Journal of Economics, Social Science, Entrepreneurship and Technology (IJESET) Vol. 1 No. 1 (2022): FEBRUARY 2022
Publisher : Pusat Riset Manajemen dan Publikasi Ilmiah Serta Pengembangan Sumber Daya Manusia Sinergi Cendikia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (487.049 KB) | DOI: 10.55983/ijeset.v1i1.65

Abstract

Google Classroom learning media in distance learning classes becomes a medium worth considering. The purpose of this study was to find out the level of admission of students in using google classroom learning media. The approach method is carried out by quantitative method by spreading the questionnaire to students and the results of this data collection are calculated using SPSS. The analysis model used is the Technology Acceptance Model. From calculations and analysis obtained the result that the relationship between ease of use of intentions and interface design relationship to usability is rejected. While the result of the relationship of usability to intention, the relationship between intention with the use of technology, the relationship between interface design with ease, the relationship of experience to ease and the relationship of ease to usefulness received
Android-Based Tourism Geographic Information System For Blitar Raya Utilizing Google Maps API and Kotlin Dimas Adi Pratama; Indyah Hartami Santi; Filda Febrinita
Jurnal Ilmiah Sistem Informasi Vol 5 No 2 (2026): May: Jurnal Ilmiah Sistem Informasi
Publisher : LPPM Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/cwe5de68

Abstract

The limited availability of integrated digital tourism information in Blitar Raya has made it challenging for visitors to plan their travel routes efficiently. This research aims to develop an Android-based Geographic Information System (GIS) that integrates the Google Maps API with the Bellman-Ford algorithm to optimize the shortest travel routes among tourism destinations. The system was developed using the Rapid Application Development (RAD) methodology, emphasizing user involvement through iterative prototyping and feedback. Primary data were collected from field observations, semi-structured interviews with tourists and local administrators, and beta testing involving 52 respondents, while secondary data were obtained from the Blitar Tourism Board and BPS statistical databases. The implementation integrates the Google Distance Matrix API to construct a weighted graph, which is processed by the Bellman-Ford algorithm, demonstrating higher route stability and accuracy than the Dijkstra and Haversine approaches in small-to-medium graph structures. The system achieved an 84.46% user acceptance rate, categorized as “Excellent” according to the ISO/IEC 25010 usability standard. Empirical findings show that the average response time of 1.5–2.5 seconds indicates high computational efficiency for real-time map rendering. This study contributes theoretically by presenting an algorithmic integration framework for mobile GIS applications and practically by offering a functional digital tourism platform to enhance local tourism management. The findings also suggest that combining RAD with algorithmic optimization can effectively bridge the gap between user experience and computational performance in tourism-based GIS systems.