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All Journal JURNAL PENDIDIKAN TAMBUSAI International Journal of Multidisciplinary Research of Higher Education (IJMURHICA)
Azmi, Arafil
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Economics, Econometrics & Finance Education Engineering Languange, Linguistic, Communication & Media Social Sciences

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Analisis Sentimen Ulasan Pengguna Aplikasi Bibit Menggunakan Algoritma Naive Bayes dan K-Nearest Neighbors (KNN) Azmi, Arafil; Hendriyani, Yeka; Dewi, Ika Parma; Budayawan, Khairi
Jurnal Pendidikan Tambusai Vol. 9 No. 2 (2025): Agustus
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v9i2.27464

Abstract

Perkembangan aplikasi investasi digital seperti Bibit menuntut pemahaman mendalam terhadap persepsi pengguna. Penelitian ini menganalisis sentimen ulasan pengguna aplikasi Bibit di Google Play Store menggunakan algoritma Naïve Bayes dan K-Nearest Neighbors (KNN). Sebanyak 2.586 ulasan dikumpulkan, kemudian diproses melalui pelabelan data, praproses teks, pemberian bobot menggunakan TF-IDF, dan klasifikasi dengan rasio data latih-uji 60:40, 70:30, 80:20, dan 90:10. Hasil penelitian menunjukkan bahwa sentimen positif mendominasi dengan persentase 74,2%, sedangkan sentimen negatif sebesar 25,8%. Naïve Bayes unggul dengan akurasi tertinggi 89,70% pada rasio 90:10, dengan presisi dan recall yang seimbang serta stabilitas yang lebih baik dibandingkan KNN yang mencapai akurasi tertinggi 88,84%, tetapi fluktuatif. Temuan ini merekomendasikan Naïve Bayes sebagai algoritma yang konsisten untuk analisis sentimen ulasan aplikasi investasi. Hasil penelitian ini dapat menjadi referensi berbasis data bagi calon investor dalam pengambilan keputusan.
The Implementation of the Gale-Shapley Algorithm in School Admission Preferences: An Analysis of Matching Efficiency and Allocation Equity Sandra, Randi Proska; Syamsi, Alkindi; Azmi, Arafil; Febriani, Natasya; Apriliyanti, Resti; Nerurkar, Pranav
International Journal of Multidisciplinary Research of Higher Education Vol 8 No 4 (2025): (October) Education, Religion Studies, Social Sciences, STEM, Economic, Tourism,
Publisher : Islamic Studies and Development Center in Collaboration With Students' Research Center Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/ijmurhica.v8i4.409

Abstract

In today’s educational landscape, integrating algorithmic approaches into school admission systems is crucial to ensure fairness, transparency, and efficiency. This study investigates the application of the Gale-Shapley algorithm to address the challenges of student-school matching, which often result in mismatches and inequities. This study aims to explain how the Gale-Shapley algorithm can ensure stable student placement, where no pair of students prefers each other over the post-assignment. Employing a mixed-methods approach, we combined a literature review with a simulation-based implementation using Python. A test case involving four students and four schools was used to validate the algorithm’s performance. The preferences of both students and schools were modeled, and the Gale-Shapley algorithm was applied to generate stable matchings. Authors analysis focused on evaluating the stability, fairness, and efficiency of the outcomes. The results demonstrate that the algorithm consistently produces optimal and conflict-free placements aligned with participant preferences. These findings highlight the algorithm’s potential to enhance the equity and effectiveness of school admission processes, particularly when applied to real-world educational settings. The implications of the discussion show that it supports trust in the admission system, because the stability and transparency of the process increase legitimacy and acceptance by all parties, including students, schools, and educational authorities.
Co-Authors Apriliyanti, Resti Budayawan, Khairi Febriani, Natasya Ika Parma Dewi Nerurkar, Pranav Sandra, Randi Proska Syamsi, Alkindi Yeka Hendriyani