DATA MINING USING CLUSTERING METHODS TO SUPPORT DECISION MAKING FOR SALES SERVICE LEVEL AT CABLE BROADCAST SUBSCRIPTIONS

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1 DATA MINING USING CLUSTERING METHODS TO SUPPORT DECISION MAKING FOR SALES SERVICE LEVEL AT CABLE BROADCAST SUBSCRIPTIONS RESEARCH BOBBY SANJAYA ( ) Graduate Program in Computer Studies Master of Information Technology Bina Nusantara University Jakarta 2011

2 DATA MINING USING CLUSTERING METHODS TO SUPPORT DECISION MAKING FOR SALES SERVICE LEVEL AT CABLE BROADCAST SUBSCRIPTIONS RESEARCH BOBBY SANJAYA ( ) A Thesis Submitted to the Faculty In Partial Fulfillment of the Requirements For Master Degree in Information Technology Field of Interest: Business Intelligence ii

3 DATA MINING USING CLUSTERING METHODS TO SUPPORT DECISION MAKING FOR SALES SERVICE LEVEL AT CABLE BROADCAST SUBSCRIPTIONS RESEARCH BOBBY SANJAYA ( ) 1st Supervisor : 2nd Supervisor: Bambang Heru Iswanto, S.Si., M.Si., Dr.rer.nat Agus Widodo, B.Sc., MT. Date: 9 / 21 / 2011 Date: 9 / 21 / 2011 iii

4 PERNYATAAN STATEMENT Dengan ini saya, Nama : Bobby Sanjaya NIM : Judul tesis : Data Mining Using Clustering Methods To Support Decision Making For Sales Service Level At Cable Broadcast Subscription Memberikan kepada Universitas Bina Nusantara hak non-eksklusif untuk menyimpan, memperbanyak, dan menyebarluaskan tesis karya saya secara keseluruhan atau hanya sebagian atau hanya ringkasannya saja, dalam bentuk format tercetak dan atau elektronik. Menyatakan bahwa saya akan mempertahankan hak exclusive saya untuk menggunakan seluruh atau sebagian isi tesis sayaguna pengembangan karya di masa depan, misalnya bentuk artikel, buku, perangkatlunak, ataupun sistem informasi. Hereby grant to my school, Bina Nusantara University, the non-exclusive right to archive, reproduce, and distribute my thesis, in whole or in part, whether in the form of printed and electronic formats. I acknowledge that I retain exclusive rights of my thesis by using all or part of it in the future work or outputs, such as article, book, software, and information system. Jakarta, 16Agustus 2011 Bobby Sanjaya iv

5 HALAMAN PERNYATAAN STATEMENT PAGE Saya, nama Bobby Sanjaya, NIM menyatakan dengan sebenar-benarnya bahwa tesis saya berjudul Data Mining dengan Metoda-metoda Clustering Untuk Mendukung Pengambilan Keputusan Pada Service Level Sales Dari Perusahaan Kabel Tayang adalah merupakan gagasan dan hasil penelitian/proyek saya sendiri dengan bimbingan Dosen Pembimbing. Saya juga menyatakan dengan sebenarnya bahwa isi tesis ini tidak merupakan jiplakan dan bukan pula dari karya orang lain, kecuali kutipan dari literature dan atau hasil wawancara tertulis yang saya acu dan telah saya sebutkan di Daftar Acuan dan Daftar Pustaka. Demikian pernyataan ini saya buat dengan sebenarnya dan saya bersedia menerima sanksi apabila ternyata pernyataan saya ini tidak benar. I, NameBobby Sanjaya, Student ID truly acknowledge that my thesis with title Data Mining Using Clustering Methods To Support Decision Making For Sales Service Level At Cable Broadcast Subscription is my concept and project result with guidance from supervisor. I, also truly acknowledge that content of this thesis are not copyed and not from another people work, except my citation from literature or written interview result and already write in reference list and bibliography list. That s my acknowledge were truly made and if in reality this acknowledge weren t true, I willing sanction. Jakarta, 16 Agustus 2011 Yang menyatakan Bobby Sanjaya v

6 AKNOWLEDGEMENTS I would like to offer my gratitude to God Almighty for His guidance during the making of this thesis. I also offer my deepest gratitude for all of those who has helped me: 1. My thesis counselors, Bambang Heru Iswanto, S.Si., M.Si., Dr.rer.nat and Agus Widodo, B.Sc., MT., thank you for the guidance for the subject of interest. 2. Every lecturer I met during my master study that has given me the idea for what should I follow. 3. My sister whom has given many encourage for me to go through this trial. 4. My friends from college and workplaces, every support you have given to me really means very much. 5. To every family and relations that has given me their advices and support. I hope that this thesis would be useful for future study and therefore I offer my humble apology for anything lacks from this writings. Jakarta, August2011 Bobby Sanjaya vi

7 TABLE OF CONTENT Title i Statement Title.... ii Supervisor Approval. iii Statement. iv Statement Page Acknowledgements. v. vi Abstract. vii Table of Content. viii List of Figures.. x List of Tables.. xi Chapter 1. Introduction Background Statement of Problems Goal of Study Benefit of Study 4 Chapter 2. Literature Review Data Mining Clustering Methods Self-Organizing Maps K-Means Expectation-Maximization Mixture Model Principal Component Analysis Normalization Chi-Square Test. 23 viii

8 2. 5. Service Level in Sales Direct Sales Market Place Multi-Level Marketing Strategies Study Motivation.. 32 Chapter 3. Methodology Conceptual Study Study Purpose Preprocessing Feature Selection Normalization Principal Component Analysis Clustering Analysis Validation and Evaluation Data Mining Tools. 47 Chapter 4. Results and Analysis Preprocessing Principal Component Analysis Cluster Analysis Direct Sales Clustering Modern Stores Clustering Multi-Level Marketing (MLM) Clustering Result Analysis 76 Chapter 5. Conclusion. 79 References. 81 Appendices. 85 ix

9 LIST OF FIGURES Figure Example of How SOM Works in Detecting Clusters by Defining (Upper) and Locating the Intended Cluster (Below) 10 Figure SOM training process. 12 Figure Clustering results using 10 clusters (shown by projection into 2d space) using the sample training image. K-means clustering without applying kernel transformation (left) is compared with kernel k-means clustering (right). 14 Figure K-Means distant and close nodes. 16 Figure GMM fitting examples from EM estimates 18 Figure Process Thinking and Learning Hierarchy. 32 Figure The Breadth and Depth of CRM Process Organization. 32 Figure The Centers of Five Clusters Compared on the Same Graph. This Simple Visualization Technique (called Parallel Coordinates) Helps Identify Interesting Clusters 34 Figure 2. 9.SOM learning process 36 Figure Performance evalutation of previous cluster research method 37 Figure Conceptual study of research 39 Figure Research Process. 40 Figure Flowchart of clustering process for this study. 46 Figure Synapse s SOM Training sessions. 54 Figure SOM cluster mapping. 58 Figure SOM cluster mapping for Modern Stores 65 Figure SOM cluster mapping for MLM. 71 x

10 LIST OF TABLES Table Generated Meta-Thematic Categories. 30 Table 4. 1a. Result of data collection, before initial data preprocessing. 50 Table 4. 1b. Result of data collection, after initial data preprocessing. 51 Table Result after normalization. 52 Table Results from univariate continuous statistics. 52 Table PCA analysis. 53 Table Summary of SOM cluster training. 55 Table SOM on Direct Sales. 56 Table Direct Sales cluster summaries. 57 Table K-Means for Direct Sales. 59 Table Summary of K-Means for Direct Sales. 60 Table Contingency Chi-Square analysis on SOM & K-Means clusters. 60 Table EM for Direct Sales. 61 Table EM Summaries for Direct Sales. 61 Table Contingency Chi-Square analysis on SOM & EM clusters. 62 Table Contingency Chi-Square analysis on K-Means & EM clusters. 62 Table SOM on Modern Stores. 63 Table Modern Stores SOM cluster summaries. 64 Table K-Means for Modern Stores. 66 Table Summary of K-Means for Modern Stores. 66 Table Modern Stores Chi-Square analysis on SOM & K-Means clusters. 67 Table EM for Modern Stores. 68 Table EM Summaries for Modern Stores. 68 Table Modern Store Chi-Square analysis on SOM & EM clusters. 69 Table Modern Store Chi-Square analysis on K-Means & EM clusters. 69 xi

11 Table SOM on MLM 70 Table SOM cluster summaries for MLM 70 Table K-Means for MLM 72 Table Summary of K-Means for MLM 72 Table MLM s Chi-Square analysis on SOM & K-Means clusters 73 Table EM for MLM 74 Table EM Summaries for MLM 74 Table MLM s Chi-Square analysis on SOM & EM clusters 75 Table MLM s Chi-Square analysis on K-Means & EM clusters 75 xii