Topic Modeling Pada Abstrak Skripsi Menggunakan Metode Latent Semantic Analysis
DOI:
https://doi.org/10.22441/10.22441/format.2022.v11.i1.009Kata Kunci:
Klasifikasi Topik, Latent Semantic AnalysisAbstrak
Abstrak – Skripsi merupakan penelitian akhir bagi mahasiswa strata-1. Dengan semakin bertambahnya dokumen skripsi, maka akan terbentuk informasi dari kumpulan dokumen tersebut. Penelitian ini dilakukan untuk menentukan pemodelan topik dan analisis tren topik dari kumpulan abstrak skripsi Program Studi Sastra Ingris UINSA tahun 2014 sampai 2019. Dari 720 dataset abstrak skripsi dilakukan pemodelan topik dengan metode Latent Semantic Analysis yang meliputi preprocessing, pembobotan term, dan perhitungan Singular Value Decomposition. Pemodelan Topik menghasilkan 20 topik linguistik dan 17 topik literatur. Kemudian pada analisis tren topik, diperoleh 7 tren topik untuk setiap jenis penelitian. Penelitian didominasi oleh penelitian linguistik tindak tutur yang termasuk dalam bidang sosiolinguistik. Berdasarkan hasil analisis jenis penelitian dibandingkan dengan data real jenis penelitian Program Studi Sastra Inggris UINSA, menghasilkan hasil analisis penelitian linguistik memiliki presisi 80% dan recall 90%, sedangkan jumlah penelitian literatur memiliki presisi 74% dan recall 57%, tingkat akurasi analisis jenis penelitian memiliki rata-rata 79%Unduhan
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