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Nasution, Muhammad Ibrahim
Politeknik Negeri Padang
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Journal : JOURNAL OF SCIENCE AND SOCIAL RESEARCH

 1 
PENERAPAN DATA MINING UNTUK PEMETAAN KINERJA AKADEMIK MAHASISWA DENGAN METODE K-MEANS G, Katrina Flomina; Rosman, Edwar; Nasution, Muhammad Ibrahim; Febrina, Yerri Kurnia; Hasibuan, Rajimar Suhal
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 2 (2025): May 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i2.3179

Abstract

Abstract: Implementation of the K-Means clustering algorithm in this study aims to group students based on academic performance in the D3 Teknik Komputer PSDKU Solok Selatan. Clustering is performed based on course grades over 3 semesters, GPA from semester 1 to 3, and student attendance. Data was taken from 27 students who have completed their studies over 3 semesters with a dataset of 29 attributes that will be used in this research. 1 attribute as an identity, 27 attributes underwent a normalization process using MIN-Max Scaler. The clustering process using the Elbow Method and Silhouette Score obtained an optimal cluster k=3, where cluster 0 consists of 10 students, cluster 1 has 8 students, and cluster 2 has 9 students. Cluster 1 shows students with very good academic performance, cluster 2 with diverse academic performance, and cluster 0 with low or poor performance. Principal Component Analysis (PCA) analysis shows good clustering results without overlap. Keyword: Data mining, K-Means clustering, Elbow Method, Silhouette Score, Academic               Performance Abstrak: Implementasi algoritma K-Means clustering  di penelitian ini bertujuan mengelompokkan mahasiswa berdasarkan kinerja akademik pada Program Studi D3 Teknik Komputer PSDKU Solok Selatan. Clustering dilakukan berdasarkan nilai matakuliah selama 3 semester, IP semester 1 sampai 3 dan absensi kehadiran mahasiswa. Data diambil dari 27 mahasiswa yang telah menyelesaikan perkuliahan selama 3 semester dengan 29 atribut datashet yang akan digunakan pada penelitian ini. 1 atribut sebagai identitas, 27 atribut dilakukan proses normalisasi menggunakan MIN-Max Scaler. Proses clustering dengan Metode Elbow dan Silhouette Score mendapatkan klaster optimal k=3, dimana klaster 0 terdiri dari 10 mahasiswa, klaster 1 terdapat 8 mahasiswa dan klaster 2 terdapat 9 mahasiswa. Klaster 1 menunjukkan mahasiswa dengan kinerja akademik yang sangat baik, klaster 2 dengan kinerja akademik yang beragam dan klaster 0 dengan kinerja yang rendah atau kurang. Analisis Principal Component Analysis (PCA)memnampilkan hasil klastering yang baik tanpa tumpang tindih. Kata kunci: Data mining, K-Means clustering, Elbow Method, Silhoutte Score, Kinerja                    Akademik  
SISTEM INFORMASI PENERIMAAN PESERTA MAGANG BERBASIS WEB MENGGUNAKAN LARAVEL DI PT SEMEN PADANG Gumelta, Riyang; Rahayu, Diana; Sy, Yulia Jihan; Nasution, Muhammad Ibrahim
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.v8i3.4154

Abstract

Abstract: The internship recruitment process at PT Semen Padang was previously conducted manually, leading to issues such as data duplication, delays in selection, and limited information transparency. This study aims to design and implement a web-based information system to digitalize the entire internship registration and selection process. The system was developed using the Laravel framework and MySQL database, adopting the waterfall development method consisting of requirements analysis, system design (using Figma and Draw.io), implementation, and black-box testing. The results show that the system effectively improves the registration process, expedites document verification, and provides real-time selection status updates for applicants. Key features include online registration, document upload, status monitoring, admin verification, and automated report generation. Based on the testing results, all features function as intended without significant issues. In conclusion, the system contributes to enhanced data accuracy, operational efficiency, and transparency in the internship admission process. The system also has potential for future enhancements, such as automated notifications and academic system integration. Keywords: Information system, internship, Laravel, MySQL, waterfall, digitalization, transparency, efficiency Abstrak: Proses penerimaan peserta magang di PT Semen Padang sebelumnya dilakukan secara manual, yang menimbulkan berbagai kendala seperti duplikasi data, keterlambatan proses seleksi, dan minimnya transparansi informasi. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem informasi berbasis web untuk mendigitalisasi proses seleksi magang secara menyeluruh. Sistem dikembangkan menggunakan framework Laravel dan database MySQL, dengan pendekatan metode pengembangan waterfall yang terdiri atas tahapan analisis kebutuhan, perancangan sistem (menggunakan Figma dan Draw.io), implementasi, serta pengujian menggunakan metode black-box. Hasil penelitian menunjukkan bahwa sistem mampu meningkatkan efisiensi proses pendaftaran, mempercepat verifikasi dokumen oleh admin, serta memberikan akses informasi seleksi secara real-time kepada peserta. Fitur utama sistem meliputi pendaftaran online, unggah dokumen persyaratan, pemantauan status seleksi, verifikasi data oleh admin, dan cetak laporan otomatis. Berdasarkan hasil pengujian, seluruh fitur berfungsi sesuai kebutuhan tanpa ditemukan kendala signifikan. Kesimpulannya, sistem ini berkontribusi dalam meningkatkan akurasi data, efisiensi operasional, dan transparansi proses penerimaan peserta magang. Sistem ini juga memiliki potensi untuk dikembangkan lebih lanjut dengan penambahan notifikasi otomatis dan integrasi sistem akademik kampus. Kata kunci: Sistem informasi, magang, Laravel, MySQL, waterfall, digitalisasi, transparansi, efisiensi.
Co-Authors Andre Febrian Kasmar Bunga Amalia Cipto Prabowo David Azis Diana Rahayu, Diana Edwar Rosman Efendi, Novi Eltri Erpita Eva Oktavia Febria Rahim Febrina, Yerri Kurnia Fryonanda, Harfebi Gumelta, Riyang Habib Alfarizzi Hasibuan, Rajimar Suhal Katrina Flomina G Miftahul Hasanah Mirawati Mirawati Muhammad Alfi Raifan Nofianti Nofianti Nurhaliza Hasanah Rasyidah, - Revika Mastanora Rudi Pranata SY, Yulia Jihan Taruma Leo Wijaya Ulfa, Ulia Widya Febriani Wirda Nissa Yerri Kurnia Febrina Yuhefizar Yuhefizar Yulhaniva Yulhaniva