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Ridwan Pandiya, Ridwan
ST3 Telkom
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Logaritmic Fuzzy Preference Programming Approach for Evaluating University Ranking Optimization Wahyuningrum, Tenia; Pandiya, Ridwan
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.6738

Abstract

Assesing quality university’s website trough webometrics is becoming one of many measures in World Class University. To get good grades, so that it can compete with other universities in the world, it needs to be pursued strategies based on the achievement of the perspective of cost (expenses) and the condition of the availability and readiness of human resource (HR owned) by the institution. Webometrics ranking optimization tailored to the institutional capacity is absolutely necessary, in order to achieve the expected goals effectively and fuel-efficient. Therefore, this paper discussed the application of the Analytical Hierarchy Process with Logarithmic Fuzzy Preference Programming combination proved to covered of the methods FPP on the university web ranking optimization. From the results of sub-criteria weighting based on the perspective of cost and human resources, earned the highest ranking among other factors recommended monitoring the ranking of sites ahrefs (C332) and majesticseo (C331) as well as increasing the number of links from other websites (C321). 
Logaritmic Fuzzy Preference Programming Approach for Evaluating University Ranking Optimization Wahyuningrum, Tenia; Pandiya, Ridwan
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.6738

Abstract

Assesing quality universitys website trough webometrics is becoming one of many measures in World Class University. To get good grades, so that it can compete with other universities in the world, it needs to be pursued strategies based on the achievement of the perspective of cost (expenses) and the condition of the availability and readiness of human resource (HR owned) by the institution. Webometrics ranking optimization tailored to the institutional capacity is absolutely necessary, in order to achieve the expected goals effectively and fuel-efficient. Therefore, this paper discussed the application of the Analytical Hierarchy Process with Logarithmic Fuzzy Preference Programming combination proved to covered of the methods FPP on the university web ranking optimization. From the results of sub-criteria weighting based on the perspective of cost and human resources, earned the highest ranking among other factors recommended monitoring the ranking of sites ahrefs (C332) and majesticseo (C331) as well as increasing the number of links from other websites (C321).
Logaritmic Fuzzy Preference Programming Approach for Evaluating University Ranking Optimization Wahyuningrum, Tenia; Pandiya, Ridwan
Scientific Journal of Informatics Vol 4, No 1 (2017): May 2017
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v4i1.6738

Abstract

Assesing quality university’s website trough webometrics is becoming one of many measures in World Class University. To get good grades, so that it can compete with other universities in the world, it needs to be pursued strategies based on the achievement of the perspective of cost (expenses) and the condition of the availability and readiness of human resource (HR owned) by the institution. Webometrics ranking optimization tailored to the institutional capacity is absolutely necessary, in order to achieve the expected goals effectively and fuel-efficient. Therefore, this paper discussed the application of the Analytical Hierarchy Process with Logarithmic Fuzzy Preference Programming combination proved to covered of the methods FPP on the university web ranking optimization. From the results of sub-criteria weighting based on the perspective of cost and human resources, earned the highest ranking among other factors recommended monitoring the ranking of sites ahrefs (C332) and majesticseo (C331) as well as increasing the number of links from other websites (C321). 
Co-Authors Ismail Bin Mohd Tenia Wahyuningrum