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All Journal JURIKOM (Jurnal Riset Komputer)
Rizkysari Meimaharani
Universitas Muria Kudus, Kudus
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Smart Virtual Guide: Chatbot Cerdas Sistem Informasi Goa Terawang dengan Analisis User Adoption Rosvika Dwi Umanisti; Aditya Akbar Riadi; Rizkysari Meimaharani
JURIKOM (Jurnal Riset Komputer) Vol. 13 No. 3 (2026): Juni 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i3.9807

Abstract

Most local tourist destinations in Indonesia still rely on static information systems that are unable to provide real-time responses to visitors, including the Terawang Ecopark Cave in Blora Regency, Central Java. This research developed an intelligent chatbot called Smart Virtual Guide based on the Large Language Model (LLM) which is integrated into the information system of Goa Terawang Ecopark, as well as analyzing the level of user acceptance using the Technology Acceptance Model (TAM). Different from previous tourism chatbot research which is generally based on conventional NLP and only supports one language, the novelty of this research lies in the integration of LLM with the support of Indonesian and Javanese at the same time in local tourist destinations. The development of the system uses the Waterfall method with functional testing through Black Box Testing and data collection from 30 respondents using a Likert scale questionnaire. The results of the Black Box Testing test showed that all features were valid, while the TAM results obtained an average percentage of 80.95% (Good category) on the PEOU, PU, BI, and ATU variables. These findings prove that LLM-based approaches with regional language support are effective in improving the quality of digital tourism information services that are more interactive, inclusive, and adaptive.
Implementasi Metode Forward Chaining untuk Rekomendasi Jurusan Perguruan Tinggi Berdasarkan Minat dan Bakat MA XYZ Shofa Allaisya; Aditya Akbar Riadi; Rizkysari Meimaharani
JURIKOM (Jurnal Riset Komputer) Vol. 13 No. 1 (2026): Februari 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v13i1.9463

Abstract

Choosing a college major is a crucial decision for final year students as it impacts their academic success and future career paths. However, the process of selecting a major is often carried out without objectively considering students' interests and talents, which can lead to mismatches in the learning process. This study aims to develop an expert system-based college major recommendation system using the Forward Chaining method to analyze students' interests and talents. Interest and talent data are obtained through questionnaires filled out by students independently through the system, then used as the initial basis for the conclusion-making process. The knowledge base is structured in the form of IF–THEN rules that link interest and talent characteristics with specific majors and their respective weights. The inference process is carried out by matching existing facts with available rules to produce a suitability score for each major. The results of the study show that the system is able to provide logical and structured major recommendations according to students' interest and talent profiles. The results of system testing on student data indicate that the system is able to produce logical and consistent major recommendations. Functional testing using the Black Box Testing method shows a success rate of 100%, indicating that all system functions run according to the specified requirements.
Co-Authors Aditya Akbar Riadi Rosvika Dwi Umanisti Shofa Allaisya