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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Algoritma
M. Husni Syahbani
Universitas Sriwijaya
Computer Science & IT Decision Sciences, Operations Research & Management Library & Information Science Other

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Analisis Sentimen Ulasan Pengguna Pada Aplikasi Kitabisa: Donasi & Zakat Menggunakan Metode Support Vector Machine (SVM) dan Naive Bayes Nabilah Putri Maharani; M. Rudi Sanjaya; Ali Ibrahim; M. Husni Syahbani
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3376

Abstract

The rapid advancement of digital technology has spurred the emergence of online philanthropy platforms like Kitabisa, which collect a large volume of user reviews. Reviews on the Google Play Store reflect both satisfaction levels and service issues, but their unstructured nature makes manual analysis difficult. This study evaluates user sentiment on the Kitabisa platform by comparing the Support Vector Machine (SVM) and Naive Bayes models. A dataset of 11,887 reviews was processed through preprocessing and word weighting using the TF-IDF approach. The evaluation results show that the Support Vector Machine outperformed Naive Bayes with an accuracy of 84.05% and an F1-score of 0.93, while Naive Bayes achieved an accuracy of 81.73% and an F1-score of 0.92. Theoretically, this study reinforces the literature regarding the superiority of Support Vector Machines for unstructured text data. Additionally, the results of this research produce an automated evaluation framework that can be used by application developers as a basis for improving service quality in accordance with user perceptions accurately.
Analisis Pengaruh Trust dan Privacy terhadap Intensi Penggunaan AI-Driven Recruitment di Kalangan Mahasiswa Ilmu Komputer Ardina Ariani; Muhammad Rudi Sanjaya; Iin Seprina; Willy; M. Husni Syahbani
JSI: Jurnal Sistem Informasi (E-Journal) Vol 18 No 1 (2026): JSI: Jurnal Sistem Informasi (E-Journal)
Publisher : Jurusan Sistem Informasi Fakultas Ilmu Komputer Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/jsi.v18i1.575

Abstract

Penelitian ini menganalisis pengaruh Trust dan Privacy terhadap intensi penggunaan AI-driven recruitment di kalangan mahasiswa Ilmu Komputer. Menggunakan pendekatan kuantitatif dengan metode Partial Least Squares - Structural Equation Modeling (PLS-SEM), data diolah melalui perangkat lunak SmartPLS 4. Hasil analisis menunjukkan bahwa Trust berpengaruh positif dan signifikan terhadap intensi penggunaan (β = 0.576, p < 0.05). Demikian pula, Privacy terbukti memiliki pengaruh positif dan signifikan (β = 0.253, p < 0.05). Secara simultan, kedua variabel tersebut mampu menjelaskan variasi intensi penggunaan sebesar 49.2% (R2 = 0.492). Temuan ini menegaskan bahwa kepercayaan pada keandalan sistem dan jaminan keamanan data pribadi merupakan faktor determinan utama bagi mahasiswa dalam mengadopsi teknologi rekrutmen berbasis AI. Pengembang platform disarankan untuk meningkatkan transparansi algoritma guna memperkuat penerimaan pengguna.   Kata Kunci: AI-driven Recruitment, Trust, Privacy, Intensi Penggunaan, PLS-SEM.
Co-Authors Ali Ibrahim Ardina Ariani Iin Seprina M. Rudi Sanjaya Muhammad Rudi Sanjaya Nabilah Putri Maharani Willy