FARISI, IMAM (2021) SISTEM REKOMENDASI LOWONGAN PEKERJAAN PADA PERUSAHAAN OUTSOURCING MENGGUNAKAN ALGORITMA TERM FREQUENCY INVERSE DOCUMENT FREQUENCY DAN COSINE SIMILARITY. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Outsourcing company is considered as one of the alternatives which may be used by job seekers for the purpose of finding any employment. The work obtained shall be adjusted by human resources development (HRD) based on curriculum vitae. This research was aimed to help HRD department with the mapping between job seeker’s curriculum vitae and relevant companies so as to avoid manual reading. A system was established in this study by using TF-IDF algorithm for terms weighting and cosine similarity method to find out any conformity between curriculum vitae and the company. The data was processed by a system in the form of pdf file with a specified framework. The framework was composed of three sections namely education, ability, and experience of job seekers. The result of a test conducted using confusion matrix test suggested an accuracy of 76%. . Key words: recommendation system, job vacancy, tf-idf, cosine similarity, text mining Perusahaan outsourcing menjadi salah satu alternatif yang bisa dimanfaatkan oleh pencari kerja dalam mendapatkan sebuah pekerjaan. Pekerjaan yang didapatkan akan disesuaikan berdasarkan daftar riwayat hidup (CV) oleh bagian human resource development (HRD). Penelitian ini bertujuan untuk membantu bagian HRD dalam memetakan antara daftar riwayat hidup pencari kerja dengan perusahaan yang sesuai agar tidak membacanya secara manual. Sistem yang akan dibangun dalam penelitian ini menggunakan algoritma TF-IDF untuk pembobotan kata dan metode cosine similarity untuk mendapatkan kesesuaian antara daftar riwayat hidup dengan perusahaan. Data yang diolah oleh sistem berbentuk file pdf dengan kerangka yang sudah ditentukan. Kerangka tersebut terdiri dari tiga bagian yaitu pendidikan, kemampuan dan pengalaman dari pencari kerja. Hasil uji coba dengan pengujian confusion matrix didapatkan akurasi sebesar 76%. Kata kunci: sistem rekomendasi, lowongan pekerjaan, tf-idf, cosine similarity, text mining
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