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All Journal Jurnal Informatika Journal of Engineering and Technological Sciences
Tota Simatupang
Industrial Systems and Techno-economics Research Group, Industrial Technology Faculty, Institut Teknologi Bandung Jalan Ganesha 10, Bandung 40132,
Computer Science & IT Engineering

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The Application of a Decision-making Approach based on Fuzzy ANP and TOPSIS for Selecting a Strategic Supplier Govindaraju, Rajesri; Akbar, Muhammad I.; Gondodiwiryo, Leksananto; Simatupang, Tota
Journal of Engineering and Technological Sciences Vol 47, No 4 (2015)
Publisher : ITB Journal Publisher, LPPM ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (320.425 KB) | DOI: 10.5614/j.eng.technol.sci.2015.47.4.5

Abstract

Supplier selection becomes very important when used in the context of strategic partnerships because of the long-term orientation of the relationship. This paper describes the application of a decision-making approach for selecting a strategic partner (supplier). The approach starts with defining a set of criteria that fits the company’s condition. In the next steps, a combination of fuzzy-ANP and TOPSIS methods is used to determine the weight for each criterion and rank all the alternatives. The application of the approach in an Indonesian manufacturing company showed that the three factors that got the highest weight were “geographical location”, “current operating performance”, and “reliability”. Geographical location got the highest weight because it affects many other factors such as reaction to changes in demand, after-sales service, and delivery lead-time.  Application of the approach helps decision-makers to gain effectiveness and efficiency in the decision-making process because it facilitates them to express their group’s collective preferences  while also providing opportunities for members to express their individual preferences. Future research can be directed at combining qualitative and quantitative criteria to develop the best criteria and methods for the selection of the best suppliers based on fuzzy ANP and TOPSIS.
PERANCANGAN SISTEM PREDIKSI CHURN PELANGGAN PT. TELEKOMUNIKASI SELULER DENGAN MEMANFAATKAN PROSES DATA MINING Govindaraju, Rajesri; Simatupang, Tota; Samadhi, TMA. Ari
Jurnal Informatika Vol 9, No 1 (2008): MAY 2008
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (413.782 KB) | DOI: 10.9744/informatika.9.1.33-42

Abstract

The purpose of this research is to design a customer churn prediction system using data mining approach. This system is able to perform data integration, data cleaning, data transformation, sampling and data splitting, prediction model building, predicting customer churn, and show the results in certain agreed forms. Churn prediction variables were identified based on earlier research reports that include customer information, payment method, call pattern, complaint data, telecommunication services usage and change of telecommunication services usage behavior data. The preferred mining technique used is the classification with decision tree algorithm. The decision tree can present visual model which represents customer churn and non churn pattern behavior. This system was tested using Kartu Halo customer data in Bandung area and testing result showed 70,94% accuracy of the prediction model. Abstract in Bahasa Indonesia : Penelitian ini bertujuan merancang sistem prediksi churn pelanggan yang memanfaatkan proses data mining. Sistem yang dihasilkan dapat melakukan integrasi data, pembersihan data, transformasi data, sampling dan pemisahan data, konstruksi model prediksi, memprediksi churn pelanggan dan menampilkan hasil prediksi dalam format laporan tertentu yang diperlukan. Identifikasi variabel-variabel prediksi churn dilakukan berdasarkan model prediksi churn yang telah dikembangkan pada penelitian terdahulu yang antara lain mencakup informasi mengenai pelanggan, metode pembayaran, data percakapan, data penggunaan jenis-jenis layanan telekomunikasi dan data yang menggambarkan perubahan perilaku penggunaan layanan telekomunikasi tersebut. Teknik mining yang dipilih adalah teknik klasifikasi dengan algoritma decision tree. Decision tree menghasilkan model visual yang merepresentasikan pola perilaku pelanggan yang churn dan tidak churn. Uji coba sistem yang dilakukan menggunakan data pelanggan Kartu Halo daerah Bandung menghasilkan tingkat akurasi model prediksi sebesar 70,94%. Kata Kunci : customer relationship management (CRM), churn, data mining, decision tree, sistem prediksi churn.
Co-Authors Joko Siswanto Leksananto Gondodiwiryo, Leksananto Muhammad I. Akbar, Muhammad I. Rajesri Govindaraju Reni Amaranti Roland Y.H. Silitonga Senator Nur Bahagia TMA. Ari Samadhi