AbstrakOpen Library Telkom University mengalami pertumbuhan yang pesat baik dari sisi jumlah maupunkekayaan kontennya. Sebagai konsekuensinya, dibutuhkan metode pencarian yang mampu memberikanhasil yang lebih akurat. Pencarian berbasis metadata sudah memberikan tambahan opsi, namun jugamasih memiliki kelemahan tidak dapat menemukan dokumen yang memiliki kemiripan. Kelemahan inibisa diatasi oleh pencarian semantik dengan memahami maksud dari pencari dan makna kontekstualistilah, seperti yang ditampilkan dalam data pencarian dengan mengkombinasiakan Latent SemanticAnalysis (LSA) dan weighted tree similarity. Berdasarkan hasil pengujian, sistem yang dibagun mampumemberikan informasi relevan dengan rata-rata nilai precision dan recall yang baik. Nilai rata-rataprecision 57.1181868% dan nilai rata-rata recall 85.0848178%. Hasil nilai rata-rata recall sudah baikkarena hampir mendekati 100% artinya tingkat keberhasilan sistem dalam menemukan dokumen yangrelevan. Sehingga dapat disimpulkan, metode LSA dan weigted tree mampu memberikan dokumen yangrelevan kepada penggunanya serta ketepatan antara kueri masukkan dengan hasil pencarian dokumen.Kata Kunci: latent semantic analysis, weighted tree similarityAbstractThe Telkom University Open Library promotes rapid growth in terms of both the amount and wealth of itscontent. As a consequence, a search method is needed that is able to provide more accurate results. Searchbased on metadata has provided additional options, but also has the disadvantage of not being able to finddocuments that have a similarity. This weakness can be overcome by semantic search with the intent andpurpose of contextual terms, as referred to in search data by combining Latent Semantic Analysis (LSA)and weighted tree similarity. Based on the test results, the built system is able to provide relevantinformation with an average value of precision and good memory. The average precision value is57.1181868% and the average recall value is 85.0848178%. The results of the average value of 100%withdrawal means the level of success in finding relevant documents. Detachable, the LSA method and theweigted tree provide relevant documents for its users as well as the accuracy between the queries providedwith the document search results.Keywords: latent semantic analysis, weighted tree similarity