PERANCANGAN BISNIS AGARPINTAR (LEARNING MANAGEMENT SYSTEM BERBASIS AI)

Muhammad Nashih Al Wafi, NIM.: 21106050030 (2025) PERANCANGAN BISNIS AGARPINTAR (LEARNING MANAGEMENT SYSTEM BERBASIS AI). Skripsi thesis, UIN SUNAN KALIJAGA YOGYAKARTA.

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Abstract

AgarpIntar is designed as an Artificial Intelligence (AI)-based online learning platform to address limitations in Indonesia’s digital education system, such as one-way interaction, lack of personalization, and reliance on complex infrastructure. The platform offers innovative features, including AI Document Chat, automatic plagiarism detection, personalized learning material recommendations based on progress, and gamification to enhance student engagement. Using the Blue Ocean Strategy, AgarpIntar creates unique value by eliminating server infrastructure costs for institutions while offering flexible service models (hosted or self-hosted). Business analysis indicates long-term viability through technical risk mitigation, digital marketing strategies, and partnerships with educational institutions. This shows that AgarpIntar can help reduce education infrastructure costs, facilitate access to quality education to remote areas, increase the focus on curriculum development by teachers, increase student learning independence, and inclusiveness of education through a platform that is easily accessible at an affordable cost. AgarpIntar aims to be an inclusive educational solution, supporting access to quality education in remote areas and improving teacher administrative efficiency through automation. This study concludes that AgarpIntar is commercially feasible

Item Type: Thesis (Skripsi)
Additional Information / Supervisor: Ir. Maria Ulfah Siregar, S.Kom., MIT
Uncontrolled Keywords: AgarpIntar, Learning Management System, Artificial Intelligence, Desain Bisnis Platform Pembelajaran
Subjects: 000 Ilmu Komputer, Ilmu Informasi, dan Karya Umum > 000 Karya Umum > 005.36 Sistem Informasi
Divisions: Fakultas Sains dan Teknologi > Informatika (S1)
Depositing User: Muh Khabib, SIP.
Date Deposited: 14 Jul 2025 09:56
Last Modified: 14 Jul 2025 09:56
URI: http://digilib.uin-suka.ac.id/id/eprint/71806

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