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BukuUsulan Sistem Informasi Manajemen Penjualan Berdasarkan Konsep Sales Force Automation (Studi Kasus: Divisi Sales PT. XYZ, Jakarta)
Bibliografi
Author: ROMUALDA, PATRICIA ; Triyanti, Vivi (Advisor)
Topik: Sales Force Automation; SDLC; Sales Management Information System
Bahasa: (ID )    
Penerbit: Program Studi Teknik Industri Fakultas Teknik Unika Atma Jaya     Tempat Terbit: Jakarta    Tahun Terbit: 2018    
Jenis: Theses - Undergraduate Thesis
Fulltext: Patricia Romualda’s Undergraduate Theses.pdf (14.89MB; 16 download)
Abstract
PT. XYZ is one of the companies that distributing electrical equipment from major suppliers. As the distributor company, sales and logistic activities are the main in survival of PT. XYZ. One of the problems experienced in these activities is the inability of the current information system to support the needs of data that a more and more. The symptoms are the large number of deals the unconscious lost, management cannot see performance clearly, there are duplication of data, and lack of quick response to customers. So the problems facing the companies is the difficulty in monitoring and assessing the performance of the activities, felt less in decision-making due to the limited data that is generated and displayed.Therefore this study will discuss about the design of management information system of sales proposals that use sales force automation concept as support in sales activities. This proposal of information system in the form of prototype based on website. This information system design method using Systems Development Life Cycle that consists of 4 major phases, namely planning, analysis, design and implementation. As for likert scale is used in the calculation of performance information. Based on the results of the trials of the use of information systems, this proposal gives rise in the value of performance information on the needs of the company. As for the use of sales force automation model as a reference in designing needs help in easing the process monitor and provide data more valuable to do deep analysis.
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