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All Journal Jurnal Informatika JATI (Jurnal Mahasiswa Teknik Informatika)
Herman Yuliansyah
Teknik Informatika, Universitas Ahmad Dahlan
Computer Science & IT

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Association pattern of students thesis examination using fp-growth algorithms Ika Arfiani; Herman Yuliansyah; Tia Purwantias
Jurnal Informatika Vol 14, No 3 (2020): September 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jifo.v14i3.a17691

Abstract

The thesis examination is the final project for students to graduate from their majors. This thesis researches scientific work between a student and a supervisor in finding solutions to a problem. In the thesis examination, students must present their research results to be criticized by the examiner. This article aims to analyze the association pattern of student thesis examinations at a private university. Although the thesis's implementation has been carried out following procedures, to determine the composition of the board of examiners needs to be analyzed by examining the pattern of relationships between research topics, supervisors, and examiners. This study uses 448 data and uses FP-Growth Algorithms to find the rules. The research methodology starts from preparing the Dataset, cleansing data, selecting data, loading data into applications, transforming data, itemset frequencies, forming patterns, and analyzing rules. This study found 145 patterns of association rules with a minimum support value = 4 and a minimum trust value = 50%. The association rule pattern of 77.78% is under scientific group data. The benefits of the association pattern produced in this study can determine the composition of the examiners on the student thesis examination according to the research topic and scientific field of the examiners.
MODEL PREDIKSI KOLABORASI ILMIAH DENGAN MEMBANDINGKAN WEIGHTED PREFERENTIAL ATTACHMENT DAN WEIGHTED KATZ INDEX PADA JARINGAN CO-AUTHORSHIP M. Milky Gazura; Herman Yuliansyah
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 3 (2026): JATI Vol. 10 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i3.18217

Abstract

Prediksi kolaborasi ilmiah merupakan permasalahan penting dalam analisis jaringan akademik untuk mengidentifikasi potensi hubungan antar peneliti di masa depan. Namun, sebagian besar pendekatan belum mempertimbangkan frekuensi kolaborasi sebagai bobot hubungan dalam jaringan co-authorship. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan model prediksi keterhubungan pada jaringan co-authorship berbobot dengan membandingkan metode Weighted Katz Index (WKatz), Weighted Preferential Attachment (WPA), serta metode dasar Preferential Attachment (PA) dan Katz Index. Dataset yang digunakan merupakan publikasi ilmiah dosen Program Studi Psikologi Universitas Ahmad Dahlan periode 2010–2024 yang dikumpulkan dari Google Scholar dan direpresentasikan sebagai graf tak berarah berbobot. Evaluasi dilakukan menggunakan skema link prediction berbasis waktu dengan sepuluh iterasi temporal dan diukur menggunakan metrik Area Under the Curve (AUC). Hasil penelitian menunjukkan bahwa Katz Index dengan parameter β = 0,01 memperoleh nilai rata-rata AUC tertinggi sebesar 0,96560, diikuti oleh WKatz sebesar 0,95376, sedangkan WPA dan PA menghasilkan nilai yang lebih rendah, masing-masing sebesar 0,67870 dan 0,64363. Temuan ini menunjukkan bahwa pendekatan berbasis Katz memiliki kinerja prediksi yang lebih unggul dibandingkan metode lainnya dalam konteks jaringan co-authorship berbobot
Co-Authors Ika Arfiani M. Milky Gazura Tia Purwantias