RAMADHAN, FAIZ MUHAMMAD (2026) RANCANG BANGUN APLIKASI REKRUTMEN MAHASISWA MAGANG BERBASIS WEB DENGAN CHATBOT ASISTENSI INFORMASI BERBASIS TF-IDF DAN NAIVE BAYES PADA UNIVERSITAS MERCU BUANA. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
The rapid development of information technology encourages higher education institutions to implement digitalization in various academic processes, including the management of student internship programs. At Universitas Mercu Buana, the recruitment process for student internships is still conducted manually, resulting in several issues such as limited dissemination of internship information, unstructured data management, and a high volume of repetitive inquiries handled by bureaus and the university’s human resources department. These conditions cause the recruitment process to be less effective and efficient. This study aims to design and develop a web-based student internship recruitment application integrated with a student assistance chatbot. The chatbot is developed using the Naïve Bayes algorithm and the TF-IDF method to classify student questions and provide relevant automated Responses related to internship recruitment information, such as requirements, registration procedures, documents, and bureau information. The research approach employed is Research and Development (R&D) using the Waterfall system development model, which consists of requirement analysis, system design, implementation, testing, and evaluation stages. The expected outcome of this research is a web-based internship recruitment system that facilitates registration, selection, and internship data management in an integrated manner among students, bureaus, and the university’s human resources department. In addition, the implementation of a chatbot based on Naïve Bayes and TF-IDF is expected to improve the efficiency of information services by providing fast and accurate automated Responses. Therefore, the developed application is expected to enhance the effectiveness of the internship recruitment process and support digital transformation at Universitas Mercu Buana. Keywords: internship recruitment, web-based information system, chatbot, Naïve Bayes, TF-IDF. Perkembangan teknologi informasi mendorong perguruan tinggi untuk melakukan digitalisasi dalam berbagai proses akademik, termasuk dalam pengelolaan program magang mahasiswa. Di Universitas Mercu Buana, proses rekrutmen mahasiswa magang masih dilakukan secara manual sehingga menimbulkan berbagai permasalahan, seperti keterbatasan penyebaran informasi lowongan, pengelolaan data yang kurang terstruktur, serta tingginya beban pertanyaan berulang yang harus ditangani oleh biro dan pihak SDM universitas. Kondisi tersebut menyebabkan proses rekrutmen menjadi kurang efektif dan efisien. Penelitian ini bertujuan untuk merancang dan membangun aplikasi rekrutmen mahasiswa magang berbasis web yang terintegrasi dengan fitur chatbot asistensi mahasiswa. Chatbot dikembangkan menggunakan algoritma Naïve Bayes dan metode TF-IDF untuk mengklasifikasikan pertanyaan mahasiswa dan memberikan respons otomatis yang relevan terkait informasi rekrutmen magang, seperti persyaratan, alur pendaftaran, dokumen, dan informasi biro. Pendekatan penelitian yang digunakan adalah Research and Development (R&D) dengan model pengembangan sistem Waterfall, yang meliputi tahap analisis kebutuhan, perancangan sistem, implementasi, pengujian, dan evaluasi. Hasil yang diharapkan dari penelitian ini adalah tersedianya sistem rekrutmen magang berbasis web yang mampu memfasilitasi proses pendaftaran, seleksi, dan pengelolaan data magang secara terintegrasi antara mahasiswa, biro, dan SDM universitas. Selain itu, penerapan chatbot berbasis Naïve Bayes dan TF-IDF diharapkan dapat meningkatkan efisiensi layanan informasi dengan memberikan jawaban otomatis secara cepat dan akurat. Dengan demikian, aplikasi yang dikembangkan diharapkan dapat meningkatkan efektivitas proses rekrutmen magang serta mendukung transformasi digital di lingkungan Universitas Mercu Buana. Kata kunci: rekrutmen magang, sistem informasi berbasis web, chatbot, Naïve Bayes, TF-IDF.
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