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All Journal Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Sinkron : Jurnal dan Penelitian Teknik Informatika JURNAL MEDIA INFORMATIKA BUDIDARMA International Journal of Supply Chain Management JUSIM (Jurnal Sistem Informasi Musirawas) Jurnal Statistika dan Matematika (Statmat) Abdiformatika: Jurnal Pengabdian Masyarakat Informatika IJCOSIN : Indonesian Journal of Community Service and Innovation International Journal of Technology, Innovation and Humanities Jurnal HUMMANSI (Humaniora, Manajemen, Akuntansi) Jurnal Masyarakat Madani Indonesia SOROT: Jurnal Pengabdian Kepada Masyarakat International Journal of Applied Mathematics, Sciences, and Technology for National Defense SmartComp IJCOSIN : Indonesian Journal of Community Service and Innovation
Diandra Chika Fransisca
Universitas Telkom
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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RANCANG BANGUN SISTEM INFORMASI OPEN JOURNAL SYSTEMS (OJS) ANDROMEDA PADA PRODI MANAJEMEN BISNIS SYARIAH IAIN PONTIANAK Julianto; Diandra Chika Fransisca
JUSIM (Jurnal Sistem Informasi Musirawas) Vol. 11 No. 2 (2026): JUSIM : Jurnal Sistem Informasi Musi Rawas Juni
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v11i2.3223

Abstract

Open Journal Systems (OJS) is an open-source software application for managing and publishing peer-reviewed online scientific journals developed by the Public Knowledge Project (PKP) and released under the GNU General Public License. This study aims to design and implement OJS Andromeda to support the management of scientific publications in the Sharia Business Management Study Program at IAIN Pontianak. The method used is system implementation with the stages of needs analysis, system design using Unified Modeling Language (UML), PKP-based OJS implementation, journal workflow configuration, and testing using Black Box Testing. The results show that the system design has been adapted to the needs of five user actors through Use Case Diagrams and Activity Diagrams. All main features tested, including Login, New Submission, Review Form, Create Issue, and Publish Article, were declared Valid. The presence of OJS Andromeda provides benefits in the form of a more structured division of journal management work and a wider publication reach because it can be accessed online and has the potential to be indexed in Google Scholar, DOAJ, and Garuda.
Sparsity-based memory scalability analysis of association rule mining algorithms using e-commerce heterogeneous multi-datasets for decision support systems Esti Fadhilah; Diandra Chika Fransisca
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 4 No. 2 (2026): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v4i2.1311

Abstract

Background: Many studies have compared the Apriori, FP-Growth, and ECLAT algorithms. Most of the previous literature focuses on runtime evaluation (execution speed) on homogeneous datasets. Research specifically mapping the visualization of memory curves against the level of data sparsity on common e-commerce heterogeneous. Aims: This study aims to analyze the relationship between sparsity and memory usage of three classic Association Rule Mining algorithms such as Apriori, FP-Growth and ECLAT using a heterogeneous e-commerce dataset. Method: A quantitative approach using Association Rule Mining was applied to different raw datasets from 721 to 30000 transactions. Transactions focused on various item types. The Apriori, FP-Growth, and ECLAT algorithms are implemented in Python, using grid search for minimum support and confidence adjustment to generate frequent item sets and association rules for performance comparison. Result: The results show that the relationship between sparsity and memory usage differs significantly in the three classical association rule mining algorithms. The ECLAT algorithm shows low memory consumption because it uses a vertical TID-list, while the Apriori and FP-Growth algorithms show high memory consumption because they are related to their pattern search methods (Candidate Generation and FP-Tree). Conclusion: This study shows that memory usage is not only influenced by sparsity, but also by the characteristics of the dataset. Then the results of this analysis provide an overview of heterogeneous e-commerce datasets when used in the classical association rule mining algorithm.
Co-Authors Agi Prasetiadi Alifatus Shabrina Amalia Alifta Salma Shafira Auliya Burhanuddin Azaria Nanda Putri Bita Parga Zen Caroline Carren Aurelia R Damara Galuh Pembayun Dwi Hesti Ariani Esti Fadhilah Hasan Nizar Iqsyahiro Kresna A Julianto Linri, Spanica Pamfilia Muhammad Afrizal Amrustian Muhammad Eka Purbaya Muhammad Fajar Sidiq Nizar, Hasan Novian Adi Prasetyo Paath, David Kristian Padosroha Marbun Pradana Ananda Raharja Pusriwijayanti, Salma Ramadlana, Adhe Nuzula Rangga Pradarrel Fathi Safar Dwi Kurniawan Shafira, Alifta Salma Silalahi, Indri Monica Cristiani Trihastuti Yuniati Ummi Athiyah Wildan Maulana Zidan Zahrina Antika Malahati