Konvergensi
Vol 17 No 2 (2021)

HYBRID JOB RECOMMENDATION SYSTEM PADA PERGURUAN TINGGI

Kartika, Bara Alpa Yoga (Unknown)
Setyati, Endang (Unknown)



Article Info

Publish Date
10 Feb 2022

Abstract

ABSTRACT Job vacancies are information that is needed by all job seekers, especially students and alumni of a college, many universities already have a career center system, but most of the systems are just information without any processing in it. In this paper, we will discuss how job recommendations are made and presented back to job seekers by combining the Cosine Similarity and Alternating Least Squares algorithms. Based on the experiments conducted, the average Precision value is 0.75. Keywords: Vacancies, Jobs, Hybrid Recommendation, Alternating Least Squares ABSTRAKLowongan pekerjaan merupakan suatu informasi yang sangat diperlukan oleh semua para pencari kerja terlebih lagi para mahasiswa maupun alumni suatu perguruan tinggi, banyak perguruan tinggi yang sudah mempunyai suatu sistem career center namun kebanyakan dari sistem hanya sebagai informasi saja tanpa ada suatu pemrosesan didalamnya. Dalam paper ini akan membahas tentang bagaimana rekomendasi pekerjaan dibuat dan ditampilkan kembali kepada para pencari kerja dengan menggabungkan algoritma Cosine Similarity dan Alternating Least Squares. Berdasarkan percobaan yang dilakukan dihasilkan rata – rata nilai Precesion sebesar 0.75 Kata Kunci: Lowongan, Pekerjaan, Hybrid Recommendation, Alternating Least Squares

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Journal Info

Abbrev

KONVERGENSI

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Environmental Science

Description

Konvergensi Teknologi Informasi & Komunikasi Journal is created as a means of communication and dissemination for researchers to publish research articles or conceptual articles. The Konvergensi Teknologi Informasi & Komunikasi Journal accepts articles related to the topic in Computer Science and ...