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All Journal Jurnal Mirai Management Sosiohumanitas: Jurnal Ilmu-Ilmu Sosial dan Humaniora Jurnal Wacana Ekonomi PRIMA : Portal Riset dan Inovasi Pengabdian Masyarakat eProceedings of Management IJOEM: Indonesian Journal of Elearning and Multimedia Journal of Indonesia Business Research (JIBR)
Dian Puteri Ramadhani
Universitas Telkom, Jawa Barat
Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Social Sciences Veterinary Other

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Analisis E – Satisfaction Aplikasi Alfagift Menggunakan Text Classification Dan Topic Modeling Customer Satisfaction Analysis Of The Alfagift Aplication Using Text Classification And Topic Modeling Amasya Seraya Tanod; dian puteri ramadhani
Journal of Indonesia Business Research (JIBR) Vol. 4 No. 1 (2026): June 2026
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jibr.v4i1.10947

Abstract

Perkembangan digitalisasi dan meningkatnya pengguna internet di Indonesia telah mendorong pola belanja masyarakat dari konvensional beralih daring. Dapat dilihat dari nilai transaksi e-commerce yang mengalami peningkatan. Alfagift, menjadi salah satu aplikasi belanja grosir yang saat ini diapkai oleh masyarakat Indonesia. Hal ini menjadi tantangan perusahaan dalam mempertahankan kepuasan pelanggan pada persaingan e-commerce yang kompetitif. Penelitian ini memiliki tujuan menganalisis kepuasan pelanggan pada aplikasi Alfagift menggunakan metode text classification dan topic modeling. Data penelitian diperoleh dari GooglePlaystore, sebanyak 50.323 ulasan dikumpulkan melalui teknik scraping. Analisis sentimen menggunakan IndoBERT, lalu hasil analisis sentimen dicari topik utama yang mempengaruhi kepuasan pelanggan menggunakan metode BERTopic. Hasil penelitian menunjukkan terdapat 70.6% pengguna memiliki persepsi positif dan 29.4% lainnya sentimen negatif. Terdapat dimensi dengan sentimen positif pada offers & discount yang menggambarkan kepuasan pada fitur promosi hingga ongkos kirim pada aplikasi. Pada dimensi paling negatif app experience menggambarkan ketidakpuasan pelanggan akan pengalaman menggunakan aplikasi seperti kendala sistem dan kesulitan pada metode pembayaran. Hasil pemodelan topik mendapatkan topik utama setiap dimensi dengan sentimen positif dan negatif paling tinggi. Pada dimensi offers & discount ditemukan pengguna mengulas mengenai penawaran harga hingga diskon yang menarik. Sedangkan, pada topik utama dimensi app experience terdapat pengguna mengeluhkan terkait sistem aplikasi yang masih kurang handal.
Utilizing Retrieval Augmented Generation (RAG)-Based Chatbots as an Innovative Learning Tool in Higher Education: A Case Study on the Use of Digital Learning Resources Yusza Murti; Dian Puteri Ramadhani; Herry Irawan
IJOEM: Indonesian Journal of E-learning and Multimedia Vol. 4 No. 3 (2025): Indonesian Journal of E-learning and Multimedia
Publisher : CV. Media Inti Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58723/ijoem.v4i3.510

Abstract

Background: Higher education institutions face information fragmentation and cognitive overload as students struggle to access learning materials scattered across multiple digital platforms. Large Language Models encounter hallucination issues and static knowledge bases, limiting their educational application.Aims: This research aims to design and evaluate a Retrieval Augmented Generation (RAG)-based chatbot system integrated with Learning Management Systems to address information fragmentation in educational environmentsMethods: We employed Design Science Research Methodology (DSRM) to develop the RAG-based chatbot. Technology Acceptance Model (TAM) assessment with 267 undergraduate students and semi-structured interviews with five faculty members evaluate user acceptance and pedagogical perspectives.Results: The RAG chatbot achieved strong initial user acceptance (mean score 4.097). Students valued perceived usefulness over ease of use, with high usage intentions and recommendation willingness. Faculty recognized pedagogical value while emphasizing quality assurance needs.Conclusion: This exploratory study demonstrates technical feasibility and baseline user acceptance for RAG-based chatbots in education, showing promise for addressing information accessibility challenges. Demonstration-based evaluation requires validation through longitudinal field studies.
Co-Authors Amasya Seraya Tanod Andry Alamsyah Cliffadika Aqshal Winata Purba Dian Indiyati Hasanah, Fathiyyah Herry Irawan Hidayat, Bangbang Irwan Mulyawan Maaruf, Muhammad Syafei Muhammad Syafei Maaruf Mukti Bawono Wicaksono Nurvita Trianasari Sindy, Nadila Arie Tanod, Amasya Seraya Yusza Murti