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All Journal Progresif: Jurnal Ilmiah Komputer Mutiara: Jurnal Penelitian dan Karya Ilmiah
Muhammad Fariz
Universitas Muhammadiyah Prof. Dr. Hamka
Religion Humanities Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Other

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Integrasi Ilmu Agama Dalam Sistem Pendidikan di Era Pasca Keruntuhan Kekhalifahan Islam La Denna Hasri Monasari; Indah Winarni; Muhammad Fariz; Herdi Tri Nanda; Nurjanah Nurjanah
Mutiara : Jurnal Penelitian dan Karya Ilmiah Vol. 2 No. 4 (2024): Agustus : Mutiara : Jurnal Penelitian dan Karya Ilmiah
Publisher : STAI YPIQ BAUBAU, SULAWESI TENGGARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59059/mutiara.v2i4.1413

Abstract

Education and knowledge are essential for effectively integrating different fields of study. The combination of religious-based lessons with general lessons in the modern era is particularly important, especially in Islamic education. To achieve this, strong educational institutions are needed that can accommodate these fields of knowledge. The integration of science and religion into Islamic education can be achieved through various means. This includes incorporating science and religion into the curriculum, the teaching and learning process, and social education aspects. Therefore, high-quality educational institutions can blend religion and science to meet the needs of their students, rather than applying a dichotomy of knowledge.
Analisis Sentimen Ulasan Aplikasi Gojek Menggunakan Support Vector Machine Muhammad Fariz; Ade Davy Wiranata
Progresif: Jurnal Ilmiah Komputer Vol. 22 No. 3 (2026): Juli
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v22i3.3969

Abstract

Evaluating Gojek’s service quality can be achieved by extracting valuable insights from the Google Play Store review corpus. However, the surging volume of data necessitates computational automation to substitute inefficient manual analysis. This study develops a sentiment analysis model using the Support Vector Machine (SVM) algorithm applied to 2,000 scraped reviews. The corpus undergoes comprehensive text preprocessing, rating-based polarity labeling, and lexical feature extraction via Term Frequency-Inverse Document Frequency (TF-IDF). Model validation demonstrates an impressive predictive performance, achieving an accuracy of 86.21%. The distribution of public opinion reveals a dominance of positive sentiment at 57.47%, outperforming the negative cluster at 42.53%. Empirically, the methodological fusion of TF-IDF and SVM is highly reliable as an analytical instrument to dissect consumer perceptions for future service improvements. Keywords: Sentiment Classification; Support Vector Machine; TF-IDF Weighting; Service Evaluation; Gojek. Abstrak Evaluasi kualitas layanan Gojek dapat diekstraksi dari korpus ulasan Google Play Store. Namun, lonjakan volume data menuntut otomatisasi komputasional guna mensubstitusi analisis manual yang inefisien. Penelitian ini mengonstruksi model analisis sentimen menggunakan algoritma Support Vector Machine (SVM) terhadap 2.000 entri ulasan hasil web scraping. Korpus diproses melalui tahapan prapemrosesan teks komprehensif, pelabelan polaritas berbasis rating, serta ekstraksi fitur leksikal mendayagunakan metode Term Frequency-Inverse Document Frequency (TF-IDF). Validasi arsitektur klasifikasi membuktikan performa prediktif yang impresif, dengan raihan akurasi menyentuh 86,21%. Peta distribusi opini publik mendemonstrasikan dominasi sentimen afirmatif (positif) sebesar 57,47%, mengungguli klaster negatif di angka 42,53%. Secara empiris, fusi metodologis antara pembobotan TF-IDF dan SVM terbukti sangat andal sebagai instrumen analitik komputasional guna membedah persepsi konsumen demi mendukung evaluasi perbaikan layanan Gojek di masa depan.
Co-Authors Ade Davy Wiranata Herdi Tri Nanda Indah Winarni La Denna Hasri Monasari Nurjanah Nurjanah