Please use this identifier to cite or link to this item: https://repositori.uma.ac.id/handle/123456789/22683
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dc.contributor.advisorLubis, Andre Hasudungan-
dc.contributor.authorNani, Tri-
dc.date.accessioned2024-01-16T05:45:45Z-
dc.date.available2024-01-16T05:45:45Z-
dc.date.issued2023-09-
dc.identifier.urihttps://repositori.uma.ac.id/handle/123456789/22683-
dc.description89 Halamanen_US
dc.description.abstractPenelitian ini bertujuan untuk memecahkan masalah seleksi rekrutmen karyawan kasir di Next Premium Barbershop dengan membangun sistem pendukung keputusan. Sistem pendukung keputusan dibangun untuk menghidarkan ada nya subjektifitas-subjektifitas keputusan yang di hasilkan dengan menggunakan metode SWARA (Stepwise Weight Assessment Ratio Analysis) yang berfungsi sebagai analisa pembobotan terhadap kriteria secara objektif kemudian metode ARAS (Additive Ratio Assessment) yang berfungsi sebagai alat pemberian nilai atau rangking berdasarkan nilai yang telah dimiliki alternatif sebelumnya. Kriteria yang digunakan terdiri, Hasil Tes Tertulis, Pendidikan, Penguasaan Komputer, Lama Pengalaman Kerja, Memiliki Kendaraan, Usia. Hasil yang diperoleh dari studi kasus penelitian ini menunjukkan bahwa proses pembobotan dengan metode SWARA mendapatkan bobot kriteria yaitu W1=0,368, W2=0,286, W3=0,182, W4=0,098, W5=0,046 dan W6=0,019. Berdasarkan perhitungan yang dilakukan maka pelamar yang berada pada rangking pertama adalah Fitri budiarti dengan nilai nilai derajat utilitas sebesar 0.968. This study aims to solve the problem of selecting cashier employee recruitment at Next Premium Barbershop by creating a decision support system. The system is built to avoid the subjectivity of decisions by using the SWARA (Stepwise Weight Assessment Ratio Analysis) method which employs as an objective weighting analysis of criteria. The ARAS (Additive Ratio Assessment) method implemented as a means of assigning values or ranking based on the value that has been owned by the previous alternative. The criteria used consist of Test Results, Education, Level Computer Mastery, Work Experience, Owning a Vehicle, Age. The results indicate that the weighting process using the SWARA method obtains criteria weights namely W1=0.368, W2=0.286, W3=0.182, W4=0.098, W5=0.046 and W6=0.019. Based on the calculations made, the applicant who is in the first rank is Fitri Budiarti with a utility degree value of 0.968.en_US
dc.language.isoiden_US
dc.publisherUniversitas Medan Areaen_US
dc.relation.ispartofseriesNPM;178160091-
dc.subjectsistem pendukung keputusanen_US
dc.subjectstepwise weight assessment ratio analysisen_US
dc.subjectadditive ratio assessmenten_US
dc.subjectdecision support systemen_US
dc.titlePenerapan Metode ARAS Dalam Perekrtutan Kasir Terbaik dengan Pembobotan Objektif Metode SWARA Pada Next Premium Barbershopen_US
dc.title.alternativeApplication of the ARAS Method in Recruiting the Best Cashier with Objective Weighting of the SWARA Method at Next Premium Barbershopen_US
dc.typeThesisen_US
Appears in Collections:SP - Informatic Engineering

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