INFS7233, Decision Support Systems (Course Semester 3)

TextBook yang dipergunakan adalah Decision Support Sytems and Intelligent Systems, 7th edition oleh Turban, Aronson, Liang and Sharda.

Perkuliahan dimulai dengan penjelasan overview materi, system penilaian dan lecture resources. Dilanjutkan dengan introduction yaitu data management, decision making and business intelligence.

Decision making, modelling and analysis: Simon’s 4 phases of decision making (intelligence, design, choice, implementation); models terdiri dari normative dan descriptive models (a simplified representation of reality, simplifications through assumptions, represent systems or problems with various degree of abstraction, decision variables, result variables, uncontrollable variable); the modelling process (conceptualization of problems, abstraction to quantitative or qualitative forms, determining the relationship among the decision, result and uncontrollable variables).

Datawarehouse: subject oriented, integrated, time variant, non-volatile, web based, relational multidimentional, client server, real time, include metadata.

Business Analytics:
Real-time Business Intelligent (BI), automated decision support (ADS) and competitive intelligent, web intelligence, need for integration.

BI/BA projects fail: failure to recognize BI project as cross-organizational business initiatives, weak business sponsors, unwilling business representatives from functional areas, lack of skilled staff, no software release concept, no work breakdown structure, no business analysis, no appreciation of the negative impact of poor data, no understanding of the use of metadata, too much reliance on disparate methods.

Data Mining: exploration and analysis, by automatic or semi-automatic means, of large quantities of data in order to obtain insight into data and discover meaningful patterns, rules and models for strategic business decision. 3 Metode untuk mengidentifikasi pola data: Simple model (OLAP, SQL Query), Intermediate Model (Regression, decision tree), complex models (neural network). Data mining tasks: classification, clustering, association rules, interactive analysis, prediction, forecasting.

CRM: konsep new marketing: relationship oriented, share of wallet oriented, all customer not equal, marketers manage demand, relationship marketing, individual marketing, manage customer experience, focus on existing customers, dialogue oriented, customer lifetime value.
CRM refers to web-based, enterprise, partner relationship management, collaborative, supplier relationship management, dan mobile CRM. Some analytical CRM application: product/service profitability, customer profiling, customer lifetime value analysis, campaign analysis, customer buying behaviour, sales channel analysis, sales analysis, call center analysis, market segment analysis. Analytical CRM Technologies: Data warehousing, ETL(data cleansing and warehouse loading), OLAP (Report generation and ad hoc reporting), data mining (pattern discovery, customer segmentation and classification, prediction models, and scoring), text mining (emails, documented complains, business contract, service description).

SCM: meningkatkan integrasi dan kolaborasi antara internal proses dalam organisasi dengan supplier (upstream) dan customer (downstream). Penggunaan teknologi untuk sharing informasi dan teamwork untuk membangun proses yang efisien dan efektif untuk menciptakan customer satisfaction.

Intelligent Systems: major components of BI: datawarehouse (DW), business analytics (BA), business performance management (BPM), user interface (UI). Pentingnya me-manage knowledge dalam perusahaan untuk menciptakan competitive advantage dan membuat keputusan strategi. Tujuan expert system adalah mentransfer expertise dari seorang expert ke system computer dan orang lain dengan cara: knowledge acquisition (interview), knowledge representation, knowledge inferencing, dan knowledge transfer. Untuk permasalahan yang lebih tidak pasti (uncertain) dipergunakan diantaranya bayes theorem, fuzzy logic, artificial neural network dan genetic algorithm.

BPM: menerapkan closed-loop process (Strategize, Plan, Monitor, Act and Adjust). BPM methodology adalah diantaranya balanced scorecard dengan membantu menterjemahkan financial, customer, internal process, dan learning and growth menjadi a set of actionable initiatives.