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All Journal JSES Indonesian Journal of Engineering and Technological Innovation
Purnama, Candra
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EFEKTIVITAS MODEL PEMBELAJARAN KOOPERATIF TIPE STUDENT TEAM ACHIEVEMENT DIVISION (STAD) UNTUK MENINGKATKAN HASIL BELAJAR FISIKA DI SMA Purnama, Candra; Suarti, Suarti; Ishak, Suryadi
Jurnal Sultra Elementary School Volume 6 Nomor 1 2025 : Februari
Publisher : Universitas Sulawesi Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54297/jses.v6i1.184

Abstract

The Student Team Achievement Division (STAD) cooperative learning model has been widely applied in various disciplines, including physics learning at the high school level. This study aims to analyze the effectiveness of the STAD model in improving physics learning outcomes through literature studies from various relevant studies. The results of the analysis show that the STAD model is able to increase student involvement in learning, strengthen conceptual understanding, and improve learning outcomes significantly compared to conventional methods. The advantage of STAD lies in the structure of group cooperation that encourages active interaction between students, thus creating a more dynamic and enjoyable learning environment. In addition, this model also contributes to improving students' social skills. However, the implementation of STAD requires careful planning and support from teachers so that learning can run effectively. Thus, the STAD model is recommended as one of the effective approaches in physics learning in high school. Informasi Artikel Abstra
Optimasi Kueri pada Very Large Database untuk Analisis Transaksi E-Commerce Real-Time Menggunakan Hybrid Indexing dan Partitioning Purnama, Candra
Indonesian Journal of Engineering and Technological Innovation Vol. 1 No. 4 (2025): December: Indonesian Journal of Engineering and Technological Innovation
Publisher : Yayasan Cendekia Gagayunan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63142/ijeti.v1i4.462

Abstract

The growth rate of e-commerce transactions generates enormous data volumes (Very Large Database/VLDB), creating significant performance challenges for real-time analytical queries. Traditional optimization techniques are often inadequate when applied separately. This study proposes and tests a hybrid optimization strategy that integrates Range Partitioning and Partial Indexing in a PostgreSQL database system. An experimental research method was conducted by building a database simulation containing 100 million rows of synthetic transaction data, then comparing performance between a baseline configuration and an optimized configuration. Test results show significant improvement. The complex aggregation query (Q1) experienced an 86.6% acceleration in execution time (from 14,200 ms to 1,900 ms), while the specific search query (Q2) improved by 89.1% (from 8,500 ms to 930 ms). Query plan analysis proves the effectiveness of the partition pruning mechanism and the use of more efficient partial indexes. It is concluded that this hybrid strategy is effective in optimizing VLDB performance for e-commerce analytical workloads and is recommended for adoption in production environments.
Co-Authors Ishak, Suryadi Suarti, Suarti