Penerapan Metode Single Linkage dengan Manhattan Distance Similarity dalam Mengelompokkan Trens Topik Kerja Praktik
DOI:
https://doi.org/10.30595/jrst.v5i1.9083Keywords:
judul kerja praktik, text mining, Manhattan Distance SimilarityAbstract
Data laporan judul kerja praktik (KP) biasanya hanya terkumpul di perpustakaan dan jarang dipubilkasikan ke mahasiswa, hal ini menyebabkan kesulitan bagi mahasiswa yang akan mengkasesnya. Berdasarkan permasalahan tersebut, maka dibuatlah suatu program pada penlitian ini untuk pengelompokkan Trend Topik. Metode yang digunakan dalam penelitian ini adalah Manhattan Distance Similariy dan Single Linkage. Sebelum masuk tahapan text mining, perlu dilakukan perancangan diantaranya perancangan basis data dan antar muka (interface). Tahapan dan text mining adalah mengumpulkan data (collect data), penguraian teks (text mining), penyaringan teks (text filtering), pembobotan kata (calculate term count), similarity, pengelompokan, dan pengujian. Hasil dari penelitian ini adalah program yang dapat mengolah data judul KP menjadi pola kelompok Trend Topik KP. Dari 905 data yang di dapatkan, terbentuk 7 kelompok yaitu Sistem Informasi, Multimedia, Jaringan, Web, Kewirausahaan, Magang, dan Pelatihan. Tetapi dari hasil pengujian Purity Test didapatkan nilai sebesar 0,267, yang artinya Manhattan Distance Similarity dan Single Linkage kurang cocok untuk mengelompokkan Judul KP.
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