23 research outputs found
A Buffer Stocks Model for Stabilizing Price in Duopoly-Like Market
No full textThis paper presents the staple-food distribution problem in agro-industry. There is a great difference
of staple-food supplies in the harvest-season and in the planting-season meanwhile the demand is relatively
constant. This situation will trigger price-volatility and shortage of staple-food, and it causes opportunity-losses for the stakeholders (producer, consumer, wholesaler/trader, and the government). For stabilizing the
price, the government has several stabilization policies; one of them is market-intervention policy by using
buffer-stocks schemes. The market-intervention policy should be utilized for improving producer’s profit, for
cutting consumer’s expenditure, and for sustaining wholesaler’s margin-profit by implementing price-support
and price-stabilization. In duopoly-like market, we assume that there are only two market-players in the
distribution system. The objective of this research is to determine the instruments for operating Market-Intervention Program which consist of the quantity, time, and price of the buffer-stocks schemes. The problem
was solved using 3 approaches. First, a comparative cost/benefit analysis between free-market and
intervention-market can be used to formulate the objective function of each stakeholders. Second, the
integration of optimization model and econometrics model were use to develop the decision-variables subject
to the expectation of stakeholders, the buffer-stocks requirement, and the dynamics price equilibrium
properties. Third, model market with Inventory was applied for solving the market-price equilibrium. The
result could be used to analyze such the staple-food distribution system, incorporating the configuration of
duo-producers, duo market-buyers, and duo-consumers.
Keywords: buffer-stocks, duopoly-like market, market-intervention program, model market with inventory,
and staple-food distribution system
A Buffer Stocks Model for Stabilizing Price of Commodity under Limited Time of Supply and Continuous Consumption
No full textStaple foods, in developing countries especially in Indonesia, have extremely volatile among harvest
and planting season caused by inelastic of supply-demand and price disparity. When a staple food is shortage
in market, it will trigger crisis of economics, political and social because it concerns with food security. This
paper develops a buffer stock model for stabilizing price of commodity under limited time of supply and
continuous consumption. The performance criterion of model will consider financial loss of producer, consumer
and government side when market is interfered by price-stabilization program and price-support program
simultaneously. The price fluctuation will be stabilized by market operation where buffer stocks are bought
from domestic and import supply point. This paper provides a price band policy that attempts to bound
domestic price variation between a set of upper and lower bounds on the level of domestic prices. We consider
three sets of problems reflecting different three prices elasticity from 4 period of supply and demand.
Numerical examples are found to be consistent with empirical estimates regarding the relationship price
elasticity with price band and with government budget for the agenda of assisting household to assure
availability a staple food with enough amounts at rational prices.
Keywords: buffer stocks, price band, stabilization, limited time of supply, staple foods
BUFFER STOCK MODEL FOR STABILIZING PRICE WITH CONSIDERING THE EXPECTATION STAKEHOLDERS IN THE STAPLE-FOOD DISTRIBUTION SYSTEM
No full textThe extremely different supplies between the harvest season and the planting season are one
of serious problem in the staple-food distribution system. In free-market mechanism, this
extreme difference will trigger price-volatility and shortage of staple-food. This situation
causes opportunity-losses for the stakeholders (producer, consumer, agent and government) in
the staple-food distribution system. The government has got incurred losses because the
government cannot achieve food-security for the households. The government has several
price stabilization policies; one of them is market intervention policy by using buffer stock
schemes to stabilize price and to reduce losses for the stakeholders. The objective of this
research is to determine the buffer stock schemes required for market-intervention program.
In the previous researches, the buffer stock models have been developed separately based on
optimization and econometrics methods. Optimizations methods have been used to determine
the level of availability with schemes consist of time and quantity of buffer stock.
Econometrics methods have been used to determine the equilibrium price by using the
selling-price and the amount of buffer stock. In this research, the integration of optimization
model (multi-objectives programming) and econometrics model are used to develop a buffer
stock model with the decision variables that consist of quantity, time, and price.
Key Words: Buffer Stock Model, Market-Intervention, Price-Stabilizatio
PERANCANGAN SISTEM PREDIKSI CHURN PELANGGAN PT. TELEKOMUNIKASI SELULER DENGAN MEMANFAATKAN PROSES DATA MINING
No full textThe 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
PERANCANGAN SISTEM PREDIKSI CHURN PELANGGAN PT. TELEKOMUNIKASI SELULER DENGAN MEMANFAATKAN PROSES DATA MINING
No full textThe 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
Model Integrasi Penjadwalan Produksi Batch dan Penjadwalan Perawatan dengan Kendala Due Date
No full textThis paper discusses the integration model of batch production and preventive maintenance scheduling on a single machine producing an item to be delivered at a common due date. The machine is a deteriorating machine that requires preventive maintenance to ensure the availability of the machine at a desired service level. Decision variables of the model are the number of preventive maintenances, the schedule, length of production runs, as well as the number of batches, batch sizes and the production schedule of the resulting batches for each production run. The objective function of the model is to minimize the total cost consisting of inventory costs during parts processing, setup cost and cost of preventive maintenance. The results show three important points: First, the sequence of optimal batches always follows the SPT (short processing time). Second, variation of preventive maintenance unit cost does not influence the sequence of batches. Third, the first production run length from production starting time is smaller than the next production run length and this pattern continues until the due date. When in process inventory unit cost is increased, the pattern will continue until a specified cost limit, and beyond the limit the pattern will change to be the opposite pattern
E-Business Initiatives in Indonesian Manufacturing SMEs
No full textThe role of information technology (IT) in improving companies’ competitiveness, including small and medium enterprises (SMEs), has been widely accepted. But, the IT investment will be in vain, if SMEs do not align their business and IT. There is a need to develop a framework of business-IT alignment. The framework development requires an understanding of the patterns of IT implementation in supporting SMEs’ business (e-business initiatives). This paper presents an empirical study on e-business initiatives in Indonesian manufacturing SMEs. The study uses 41 business processes that are grouped into three business focuses: supplier side, internal side and customer side. Based on the complexity of IT support to business processes, supplier side score, internal side score, customer side score and global score can be calculated. These scores are used to develop e-business initiative groups by using cluster analysis. After validated using discriminant analysis, the cluster analysis gives five e-business initiatives. First initiative is e-business implementation in three sides of business focuses, although in the early stage. Second initiative is IT implementation with internal side focus. Third initiative is e-business with customer side focus. The fourth is initiative that focuses on internal and customer side. The last is e-business initiative that balances and extends IT implementation on the three sides of business focuses. Then, this paper explains the differences between e-business initiatives
Model Integrasi Penjadwalan Produksi Batch dan Penjadwalan Perawatan dengan Kendala Due Date
No full textThis paper discusses the integration model of batch production and preventive maintenance scheduling on a single machine producing an item to be delivered at a common due date. The machine is a deteriorating machine that requires preventive maintenance to ensure the availability of the machine at a desired service level. Decision variables of the model are the number of preventive maintenances, the schedule, length of production runs, as well as the number of batches, batch sizes and the production schedule of the resulting batches for each production run. The objective function of the model is to minimize the total cost consisting of inventory costs during parts processing, setup cost and cost of preventive maintenance. The results show three important points: First, the sequence of optimal batches always follows the SPT (short processing time). Second, variation of preventive maintenance unit cost does not influence the sequence of batches. Third, the first production run length from production starting time is smaller than the next production run length and this pattern continues until the due date. When in process inventory unit cost is increased, the pattern will continue until a specified cost limit, and beyond the limit the pattern will change to be the opposite pattern
