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Biner : Jurnal Ilmu Komputer, Teknik dan Multimedia
Published by CV. SHOFANAH MEDIA BERKAH
ISSN : -     EISSN : 29883814     DOI : -
Core Subject : Humanities, Science, Engineering,
Humanities Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Transportation
1. Komputasi Lunak, 2. Sistem Cerdas Terdistribusi, Manajemen Basis Data, dan Pengambilan Informasi, 3. Komputasi evolusioner dan komputasi DNA/seluler/molekuler, 4. Deteksi kesalahan, 5. Sistem Energi Hijau dan Terbarukan, 6. Antarmuka Manusia, 7. Interaksi Manusia-Komputer, 8. Hibrida dan Algoritma Terdistribusi Pemrosesan Informasi Manusia, 9. Komputasi Berkinerja Tinggi, 10. Penyimpanan informasi, 11. Keamanan, integritas, privasi, dan kepercayaan, 12. Pemrosesan Sinyal Gambar dan Ucapan, 13. Sistem Berbasis Pengetahuan, 14. Jaringan Pengetahuan, 15. Multimedia dan Aplikasi, 16. Sistem Kontrol Jaringan, 17. Klasifikasi Pola Pemrosesan Bahasa Alami, 18. Pengenalan dan sintesis ucapan, 19. Kecerdasan Robot, 20. Analisis Kekokohan, 21. Kecerdasan Sosial, 22. Statistic 23. Komputasi grid dan kinerja tinggi, 24. Realitas Virtual dalam Aplikasi Rekayasa, 25. Intelijen Web dan Seluler, 26. Data Besar, 27. Manajemen Informatika, 28. Sistem Informasi, 29. Desain Permainan, 30. Sistem Multimedia, 31. Pemrosesan Gambar, 32. IOT 33. Pemrograman Seluler, 34. Desain Basis Data, 35. Pemrograman Jaringan, 36. Sistem Terdistribusi, 37. Sistem Pendukung Keputusan, 38. Sistem Pakar, 39. Kriptografi, 40. Model dan Simulasi, 41. Jaringan 42. Teknik Sipil 43. Teknik Kimia 44. Teknik Terapan yang relevan 45. Multimedia
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 301 Documents
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Analisis Perbandingan Kinerja Binary Search Tree dan AVL Tree dalam Sistem Pencarian Data Mahasiswa Siti Haliza Zamili; Alya Namira; Khodotun Hadawiyah Margolang; Adinda Soleha; Adidtya Perdana
BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia Vol. 3 No. 6 (2026): BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia
Publisher : CV. Shofanah Media Berkah

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Abstract

Information retrieval systems are a crucial part of data management, particularly in academic systems that store a large amount of student data. Search effectiveness is greatly influenced by the format and organization of the data. This study aims to evaluate and compare the performance of two types of tree data structures, namely Binary Search Trees and AVL Trees, in student data retrieval activities. Testing was conducted using numerical datasets reflecting student information with varying amounts of data: 20, 40, 60, 80, and 100. Parameters used in the assessment included tree height and data search duration. The algorithm was implemented using the Python programming language. The test results show that Binary Search Trees tend to have tree heights that increase significantly with increasing data volume due to the absence of a balancing mechanism. Meanwhile, AVL Trees can maintain the balance of their tree structure through a rotation process that makes the tree height more consistent. In addition, search time in AVL Trees also appears faster than Binary Search Trees, especially when the amount of data encountered is larger. Therefore, AVL Trees are considered more efficient and ideal for implementation in student data retrieval systems that require fast and stable searches.

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