ANALISIS PROFIL AKADEMIK ALUMNI DENGAN MENGGUNAKAN METODE KLASTERISASI K-MEANS

Dewi Anggraini, Irya Wisnubhada, Paulus Mudjihartono

Abstract


Universities are currently required to have the ability to compete by utilizing all its resources. In addition to the resources of facilities, infrastructure, and human, data and information systems are some resources that can be used to improve the ability to compete. One of the elements that must be considered in the development of a college is to be able to compete data alumni academic. STIKOM Uyelindo Kupang have sufficient academic alumni data to be analyzed. With alumni academic data clustering, decision makers can identify the characteristics of alumni profiles. Characteristics of alumni profiles can then provide an overview and consideration of the development of university policies related to alumni. In this paper, k -means algorithm is used for the data mengklasterisasi academic graduates with the purpose of showing the characteristics of the profile information of alumni. Clustering results with 226 data from three study programs (S1/D3 informatics engineering and information systems S1), and with k = 3, the group acquired sufficient data points to a pattern of firm alumni profiles can support the decision.


Keywords


Data Analysis, Academic Alumni Profiles,clustering, K - means clustering algorithm.

References


Abriyansyah G.S, (2010). Data Mining dan Knowledge Discovery in Database, Tugas DM dan KDD Institut Sains Terapan dan Teknologi Surabaya.

Agusta, Y. P. (2007). K-means - Penerapan, Permasalahan, dan Metode Terkait. Jurnal Sistem dan Informatika , vol 3.

Andayani Sri, (2007). Pembentukan Cluster Dalam Knowledge Discovery in Database dengan Algoritma K-means, SEMNAS Matematika dan Pendidikan matematika “Trend penelitian Matematika dan Pendidikan Matematika di Era Global”.

Huda N.M, (2010). Aplikasi Data Mining Untuk Menampilkan Informasi Tingkat Kelulusan Mahasiswa, Tugas Akhir Fakultas Matematika dan Ulmu Pengetahuan Alam Universitas Diponegoro.

Kurniawan Ari., Hariadi Mochamad, (2010). Klasterisasi Kompetensi Guru Menggunakan Penilaian Portofolio Sertifikasi Guru Dengan Menggunakan Data Mining, Telematika, Institut Teknologi Sepuluh Nopember Surabaya.

Kusnawi, (2007). Pengantar Solusi Data Mining, Seminar Nasional teknologi (SNT), ISSN 1978-9777.

Luthfi E.T, (2009). Penerapan Data Mining Algoritma Asosiasi Untuk Meningkatkan Penjualan, Jurnal DASI Vol. 10, No. 1, ISSN : 1411-3201.

Mathuriya Nitu., Bansal Dr Ashish, (2012). Comparison of K-means and Backpropagation Data Mining Algorithms, International Journal of Computer Technology and Electronics Engineering (ICJTEE), Vol. 2, ISSN : 2249-6343

Meinanda M.H., Annisa metri., Muhandri Narendi., Suryadi Kadarsyah, (2009). Prediksi Masa Studi Sarjana dengan Artificial Neural Network, Intenetworking Indonesia journal Institut teknologi Bandung Vol. 1 No. 2, ISSN : 1942-9703.

Wahyudi E.K., Jananto Arief., Narwati, (2011). Analisa Profil Data Mahasiswa Baru Terhadap Program Studi Yang Dipilih di Perguruan Tinggi Swasta Jawa Tengah dengan Menggunakan Teknik Data Mining, Jurnal teknologi Informasi DINAMIK Vol 16 No. 1.

Yusuf Ahmad., Ginardi hari., Arieshanti Isye, (2012). Pengembangan Perangkat Lunak Prediktor Nilai Mahasiswa Menggunakan Metode Spectral Clustering dan Bagging Regresi Linier, Jurnal Teknik ITS, vol 1, ISSN 2301-9271.


Refbacks

  • There are currently no refbacks.