Banyaknya Universitas baru yang bermunculan membuat semakin ketatnya persaingan dalam menarik minat calon mahasiswa. Social Network Analysis (SNA) salah satu metode untuk menganalisis interaksi pengguna media sosial dalam menghasilkan informasi yang dapat mendukung dalam pengambilan keputusan untuk melakukan promosi. Tujuan dari penelitian ini adalah untuk mengetahui keaktifan Universitas dalam melakukan promosi melalui media sosial twitter. Sosial Media Analysis (SNA) menunjukkan aktor (node) dengan nilai degree centrality (sering dihubungi) adalah aktor dengan nama sbmptnfess pada Universitas Dian Nuswantoro dengan nilai sebesar 21 node. Sedangkan aktor yang memiliki jangkauan yang paling dekat (Closseness centrality) Universitas Semarang, Universitas Sultan Agung, Universitas Dian Nuswantor, dan Universitas PGRI Semarang memiliki nilai yang sama. Sehingga aktor dari ke empat universitas tersebut memiliki kedekatan jangkauan sebesar 1.0. Sedangkan Aktor sebagai penghubung yang baik (Betweenness Centrality) adalah Universitas PGRI Semarang dengan nilai tertinggi sebesar 0.010096 dengan aktor turungences.
The improvement of a company performances cannot be separated from the performance of each employee. Periodic evaluation of employee performance becomes a routine task of the Human Resources General Affair (HRGA) team that takes a long time and effort because it is still done manually. The results of employee performance that have been assessed as a reference of determination of rewards and punishment. The Decision Support System (DSS) is made with the aim of making it easier for HRGA to determine employee rewards and punishments based on assessor factors that have been determined by the company. The criteria chosen are attendance, loyalty and responsibility, work competency and work results (quality and quantity results). The DSS methods that can be applied to this process is the Multi-Attributive Border Approximation area Comparison (MABAC) Method. This method is used because consistent in solutions and expert for use in logical decision making. The research data was taken from 11 samplings of bakery division employee performance data for 1 year. Data is obtained from attendance and assessments from supervisors of each division. The results of this research, is a decision support system web based in order to determine the reward and punishment method using MABAC.
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