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All Journal Syntax Literate: Jurnal Ilmiah Indonesia Eduvest - Journal of Universal Studies
Septianto, Yudhi
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Aerospace Engineering Humanities Computer Science & IT Education Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Neuroscience Social Sciences Other

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Data Tracer Study Analysis in Higher Education Using The FP-Growth Algorithm Septianto, Yudhi; Musodo, Krisna Adiyarta
Eduvest - Journal of Universal Studies Vol. 4 No. 12 (2024): Journal Eduvest - Journal of Universal Studies
Publisher : Green Publisher Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59188/eduvest.v4i12.50106

Abstract

Knowing the distribution of alumni from a tertiary institution is very useful as evaluation material and benchmarks for teaching and learning activities in the tertiary institution concerned. XYZ College alumni distribution data by carrying out tracer studies. Tracer study data can be used by tertiary institutions for decision making and as input in curriculum development or other academic support facilities. Data mining is used to extract information on large-scale data. The method used is the fp-growth algorithm which is part of the association rule technique which aims to find and determine a data set that often appears in a data mine. Attribute data used in this study are field of study, GPA, year of admission, year of graduation, gender, waiting period, field of work, salary, position. The purpose of this study is to examine the pattern of alignment between data on alumni work using the fp-growth algorithm. The results of this study are in the form of information on patterns of alignment of the relationship between fields of study and GPA, year of entry, year of graduation, waiting period, field of work, salary, gender, position on alumni work in tracer study data in Higher Education using the fp-growth algorithm which will make it easier for tertiary institutions to gain deeper insight into alumni, as well as gain new knowledge about graduates and can be used to improve the quality of higher education.
Evaluasi Sistem E-Learning di Universitas Nasional menggunakan Cobit 2019 Septianto, Yudhi; Hermadi, Irman; Wahjuni, Sri
Syntax Literate Jurnal Ilmiah Indonesia
Publisher : Syntax Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (206.598 KB) | DOI: 10.36418/syntax-literate.v7i12.10415

Abstract

Universitas Nasional (UNAS) menerapkan metode pembelajaran e-learning atau biasa disebut dengan blended learning guna merespon dan siap menyongsong era digital 4.0 dan 5.0. Metode belajar ini memadukan pertemuan tatap muka dengan pembelajaran online dengan memanfaatkan teknologi digital. Pengukuran kinerja dapat diartikan sebagai penilaian mutu dari kemampuan kerja demi mengetahui seberapa jauh capaian yang diharapkan telah terpenuhi, penilaian tersebut tidak terlepas dari proses pengolahan masukan menjadi keluaran dengan memanfaatkan data internal. Saat ini teknik yang digunakan yaitu teknik desain factor yang bertujuan untuk mengidentifikasi kebutuhan pemangku kepentingan (stakeholder drivers and needs) dan menerjemahkan tujuan perusahaan (enterprise goals) menjadi prioritas untuk tujuan penyelarasan teknologi informasi terkait (alignment goals) serta memperoleh domain proses yang di gunakan dalam pembuatan kuesioner. Pengukuran tingkat kemampuan (capability level) untuk mengetahui sejauh mana kinerja e-learning Universitas Nasional saat ini, mengukur tingkat kematangan kinerja pembelajaran e-learning yang mengacu kepada standar framework COBIT 2019, serta memberikan rekomendasi perbaikan untuk meningkatkan kapabilitas (capability level) terhadap sistem pembelajaran e-learning di Universitas Nasional.
Co-Authors Irman Hermadi Musodo, Krisna Adiyarta Sri Wahjuni