SISTEM INFORMASI REKOMENDASI PEKERJAAN BERDASARKAN NILAI AKADEMIK MAHASISWA POLITEKNIK NEGERI MALANG MENGGUNAKAN METODE WEIGHTED PRODUCT DAN SIMPLE ADDITIVE WEIGHTING

Purwo Saputro, Irfan (2023) SISTEM INFORMASI REKOMENDASI PEKERJAAN BERDASARKAN NILAI AKADEMIK MAHASISWA POLITEKNIK NEGERI MALANG MENGGUNAKAN METODE WEIGHTED PRODUCT DAN SIMPLE ADDITIVE WEIGHTING. Diploma thesis, Jurusan Teknologi Informasi.

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Abstract

Pekerjaan mempunyai beberapa bidang yang membutuhkan keahlian khusus dalam melakukan pekerjaan tersebut. Keahlian tersebut dapat diperoleh dengan menempuh pendidikan di perguruan tinggi. Politeknik yang merupakan Pendidikan Tinggi Vokasi memiliki ciri-ciri mengutamakan dalam menerapkan aspek-aspek praktis yang didukung oleh teori yang tepat. Kemudian dilakukan penelitian sistem rekomendasi pekerjaan berdasarkan nilai akademik mata kuliah praktikum dengan mengimplementasikan Metode Wighted Product dan Simple Additive Weighting. Sistem digunakan untuk merekomendasikan pekerjaan dengan hasil perankingan sesuai dengan nilai mata kuliah praktikum mahasiswa dengan nilai yang ada di setiap alternatif pekerjaan. Terdapat alternatif pekerjaan dalam bidang Teknologi Informasi yang berhubungan dengan kriteria mata kuliah praktikum berdasarkan nilai yang diperoleh mahasiswa Program Studi Diploma IV Teknik Informatika Jurusan Teknologi Informasi Politeknik Negeri Malang. Pada metode Simple Additive Weighting dilakukan perkalian penjumlahan dari bobot yang sudah dilakukan perhitungan relatif bobot nilai mata kuliah dari metode Weighted Product dan nilai normalisasi matriks dari nilai kriteria setiap alternatif pekerjaan. Hasil kedua metode tersebut dilakukan perhitungan akurasi menggunakan Confusion Matrix dengan nilai akurasi 77,5% untuk Metode Wighted Product dan nilai akurasi 82,5% untuk Metode Kombinasi Simple Additive Weighting dan Weighted Product. Berdasarkan hasil penelitian akurasi yang dilakukan sistem tersebut dapat merekomendasikan pekerjaan sesuai dengan nilai mata kuliah yang di diperoleh mahasiswa. Profession have several fields that certainly require special expertise in doing the job. This skill can be obtained in many ways. One of them is studying at university. Polytechnic which is Vocational Education has the characteristics of prioritizing practical aspects supported by appropriate theory. Then, a job recommendation system is researched based on the academic course grade of the practicum by implementing the Weighted Product and Simple Additive Weighting methods. There are alternative jobs in the field of Information Technology related to the criteria for practicum course grades obtained by students of the Study Program in Informatics Engineering, Information Technology Department, State Polytechnic of Malang. In the Weighted Product method, it is multiplying to connect the rating criteria, the rating of each criterion for each alternative must be raised to the first rank with the criterion weight. In the Simple Additive Weighting method, the multiplication of the sum of the weights has been carried out by calculating the relative weight values of the Weighted Product method and the matrix normalized values of the criteria for each alternative job. Then from the results of the two methods, a comparison accuracy calculation is carried out with the score is 99.5% for the Weighted Product method and 99.7% for the Simple Additive Weighting and Weighted Product combination method. The conclusions according by the system can recommend jobs with ranking results according to the grades of student practicum courses based on the results of the scores obtained in each alternative job.

Item Type: Thesis (Diploma)
Uncontrolled Keywords: Pekerjaan, Pendidikan Vokasi, Weighted Product, Simple Additive Weighting
Subjects: A Computer Science > Computer Programming
A Computer Science > Applied Computer Science
Divisions: Jurusan Teknologi Informasi > Teknik Informatika
Depositing User: Irfan Purwo Saputro
Date Deposited: 11 Jan 2024 01:55
Last Modified: 11 Jan 2024 01:55
URI: http://repota.jti.polinema.ac.id/id/eprint/821

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