Implementasi Metode Analytical Network Process (ANP) dan Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk Retensi Pelanggan Flexi

Mutia Darmayanti

Informasi Umum

Kode

113071128

Klasifikasi

629.8 - Automatic control engineering

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Otomation

Dilihat

375 kali

Informasi Lainnya

Abstraksi

ABSTRAKSI: Kata Kunci : ABSTRACT: Flexi is one of the company that supply cellular services, to avoid losing customer, Flexi implemented the retention system to give special privelege to the customers. Determing which customer that will receive the retention system can be done by analyzing the data of Flexi’s customer usage that qualifiy some criterias. To acquite the score of customers , require both subjective and objective evaluation. ANP and TOPSIS method can be used as alternative to determine which customer to be given the privellege.<br><br>In this Final Assignment, a system retention is created to help determing togive special privilege with used ANP and TOPSIS method, in this application ANP method will be use as subjective evaluation tool by giving score for each criteria and alternative, while TOPSIS method use as objective evaluation tool by considering the range of positive and negative ideal solution. From ANP and TOPSIS evaluation we could produce score to sort or to rank which customer to be given retention.<br><br>This Final Assignment purpose is to implementation ANP and TOPSIS method, from experimental result will be acquired different output in between ANP and TOPSIS only method and ANP-TOPSIS method . The data will be analyzed in each criteria by comparing the change in each criteria score, it is also possible to analyze the effect of each critea score final sortment of customer to be given the special privellage. The result of analysis shows the criteria that has most effect to the customer scoring is criteria A1 (Flexi to Flexi phone user) while the scoring is criteria A7 (Ringbacktone user).Keyword: Retention, ANP, TOPSIS