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All Journal Jurnal Informatika dan Teknik Elektro Terapan Biner : Jurnal Ilmu Komputer, Teknik dan Multimedia
Adinda Soleha
Universitas Negeri Medan
Humanities Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Transportation

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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.
RANCANG BANGUN SISTEM DETEKSI TOXIC DAN SPAM BERBASIS FINITE AUTOMATA DENGAN ALGORITMA AHO-CORASICK Alya Namira; Zulfahmi Indra; Adinda Soleha; Bryant Tinambunan
Jurnal Informatika dan Teknik Elektro Terapan Vol. 14 No. 3 (2026)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v14i3.9864

Abstract

Perkembangan media sosial meningkatkan risiko penyebaran konten toxic dan spam yang dapat menurunkan kualitas interaksi pengguna. Penelitian ini bertujuan merancang dan mengimplementasikan sistem deteksi konten toxic dan spam berbahasa Indonesia berbasis Finite Automata menggunakan algoritma Aho-Corasick. Dataset yang digunakan terdiri dari dataset_kata_kasar_idn sebanyak 3.111 data dan dataset_spam_idn sebanyak 2.636 data. Dari kedua dataset tersebut diekstrak 89 kata toxic dan 83 kata/frasa spam yang digunakan sebagai kamus keyword sistem. Sebelum proses deteksi, teks melalui tahap preprocessing berupa case folding dan normalisasi karakter berulang. Selanjutnya, keyword dimasukkan ke dalam struktur trie dan dibangun failure function untuk membentuk automata Aho-Corasick. Pengujian dilakukan terhadap 48 kalimat uji yang terdiri atas kategori Toxic, Spam, Normal, dan Toxic+Spam. Hasil penelitian menunjukkan bahwa sistem mampu mencapai akurasi sebesar 91,7% dengan nilai precision rata-rata 0,925, recall 0,939, dan F1-score 0,931. Hasil tersebut menunjukkan bahwa pendekatan Finite Automata dengan algoritma Aho-Corasick efektif digunakan untuk mendeteksi konten toxic dan spam secara cepat pada teks berbahasa Indonesia.
Co-Authors Adidtya Perdana, Adidtya Alya Namira Bryant Tinambunan Khodotun Hadawiyah Margolang Siti Haliza Zamili Zulfahmi Indra, Zulfahmi