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All Journal JOURNAL OF SCIENCE AND SOCIAL RESEARCH Instal : Jurnal Komputer
Indrayani, Maida
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Social Sciences

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Implementation of Bubble Sort to Sort Positive Integers in Ascending Using the Flowgorithm Application Jabar, Ami Abdul; Indrayani, Maida; Parhusip, Nelviony; Nasution, Darmeli
Bahasa Indonesia Vol 16 No 03 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i03.231

Abstract

This research utilizes computer technology and software as effective learning media. The Bubble Sort algorithm was chosen because it is simple but effective in sorting data. Using Flowgorithm as a visualization tool makes it easier to understand the algorithm and ensures correct implementation. The research methodology includes literature study, analysis of data sorting characteristics, and application of algorithms in Flowgorithm. The results show that Bubble Sort succeeded in sorting the data correctly according to ascending order, confirming the usefulness of the Flowgorithm application in learning algorithms and programming.
PEMETAAN PILIHAN LULUSAN SMK PANCA BUDI MEDAN MENGGUNAKAN ALGORITMA K-MEANS DAN VISUALISASI DATA Indrayani, Maida; Iqbal, Muhammad; Nasution, Darmeli
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3543

Abstract

Abstract: This research maps the career choices of SMK Panca Budi Medan graduates using the K-Means algorithm and data visualization. The study included 219 graduates from 2024 across eight study programs. The majority (44.7%) chose to work, followed by 32.0% who pursued higher education, 16.4% were undecided, and 6.8% became entrepreneurs. Graduates with higher average report card scores tended to continue their studies, while those with lower scores often opted to work or were undecided. The K-Means algorithm successfully clustered graduates, with Cluster 1.0 showing the highest academic potential (average score: 94.60). The findings provide strategic recommendations for the school, including intensifying career guidance for undecided graduates, strengthening higher education pathways for high-achievers, accelerating entrepreneurship incubators, and implementing personalized alumni coaching based on clustering analysis. Keywords: Tracer Study, K-Means, Data Visualization, SMK, Alumni Outcomes Abstrak: Penelitian ini memetakan pilihan karier lulusan SMK Panca Budi Medan menggunakan algoritma K-Means dan visualisasi data. Studi melibatkan 219 lulusan tahun 2024 dari delapan program studi. Sebagian besar lulusan (44,7%) memilih langsung bekerja, diikuti oleh 32,0% yang melanjutkan kuliah, 16,4% "belum tahu", dan 6,8% berwirausaha. Alumni dengan rata-rata nilai rapor tertinggi cenderung melanjutkan kuliah, sedangkan yang lebih rendah umumnya memilih bekerja atau belum memiliki rencana. Algoritma K-Means berhasil mengelompokkan lulusan, dengan cluster 1.0 merepresentasikan potensi akademik tertinggi (rata-rata nilai: 94,60). Temuan ini menghasilkan rekomendasi strategis bagi sekolah, meliputi pengintensifan program bimbingan karier, penguatan jalur kuliah bagi siswa berprestasi tinggi, akselerasi pengembangan inkubator wirausaha, serta implementasi pembinaan alumni berbasis personalisasi dari hasil clustering. Kata kunci: Tracer Study, K-Means, Visualisasi Data, SMK, Outcome Alumni
Co-Authors Jabar, Ami Abdul Muhammad Iqbal Nasution, Darmeli Parhusip, Nelviony