Requirement Volatility, Standardization and Knowledge Integration in Software Projects: An Empirical Analysis on Outsourced IS Development Projects

Information systems development (ISD) projects are highly complex, with different groups of people having  to collaborate and exchange their knowledge. Considering the intensity of knowledge exchange that takes place in outsourced ISD projects, in this study a conceptual model was developed, aiming to examine the influence of four antecedents, i.e. standardization, requirement volatility, internal integration, and external integration, on two dependent variables, i.e. process performance and product performance. Data  were collected from 46 software companies in four big cities in Indonesia. The collected data were examined to verify the proposed theoretical model using the partial least square structural equation modeling (PLS-SEM) technique. The results show that process performance is significantly influenced by internal integration and standardization, while product performance is  significantly influenced by external integration and  requirement volatility. This study contributes  to a better understanding of how knowledge integration can be managed in outsourced ISD projects in view of increasing their success

The Application of a Decision-making Approach based on Fuzzy ANP and TOPSIS for Selecting a Strategic Supplier

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

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

The Application of a Decision-making Approach Based on Fuzzy ANP and TOPSIS for Selecting a Strategic Supplier

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

Change Management Perspectives in an ERP Module Implementation: A Case Study in a Telecommunication Company

Successful Enterprise Resource Planning (ERP) projects require change management to support the integration of the ERP systems into work environment because ERP imple¬men¬tations involve lots of changes on technical infrastructures, business processes, organization structure, rules and skills of people in the organization. This study was aimed to explain the challenges in implementing an ERP module in a Indonesian telecommunication company, focusing on the change management process involves in the project. A case study at a tele¬com¬munication company was used to collect empirical data and to analyses important aspects of project arrangements that will have an impact on the change management process accompanying the ERP implementation project. The following two aspects of changes were analyzed as the impact of ERP implementation: changes in individual behaviors and changes in the organisational practices. Based on the empirical study, two important aspects of change management effectiveness in the project and post-project stage were highlighted: alignment of the organization structure to support IT-business collaboration and alignment of employee orientation towards effective use of ERP systems. Besides, this study also highlighted that it is important to plan and execute change management process in the post-project stage to obtain benefits from ERP implementation

Modeling policy mix to improve the competitiveness of indonesian palm oil industry

Purpose: The purpose of this research is to develop a model that will explain the impact of government policies to the competitiveness of palm oil industry. The model involves two commodities in this industry, namely crude palm oil (CPO) and refined palm oil (RPO), each has different added value. Design/methodology/approach: The model built will define the behavior of government in controlling palm oil industry, and their interactions with macro-environment, in order to improve the competitiveness of the industry. Therefore the first step was to map the main activities in this industry using value chain analysis. After that a conceptual model was built, where the output of the model is competitiveness of the industry based on market share. The third step was model formulation. The model is then utilized to simulate the policy mix given by government in improving the competitiveness of Palm Oil Industry. Findings: The model can accommodate government’s policy mix which is then optimized. The model has been built structurally based on hierarchical multi-level system approach, while in the process element, the subprocesses are built using VCA approach. The model can simulate industry performance, and show that such government policy mix can improve the competitiveness of Indonesian palm Oil Industry. Research limitations/implications: The model was developed using only some policies which give direct impact to the competitiveness of the industry. For macro environment input, only price is considered in this model. Practical implications: The model can simulate the output of the industry for various government policies mix given to the industry. The techno-economic aspect is also discussed. Originality/value: This research develops a model that can represent the structure and relationship between industry, government and macro environment, using value chain analysis and hierarchical multilevel system approach