DEMAND FORECAST ANALYSIS FOR INFLUENZA VACCINE CASE STUDY: PT. BIO FARMA (PERSERO)

• Main Author: Jundi, Muhammad
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/72437
• Institution: Institut Teknologi Bandung

An influenza vaccine could play a very significant role in reversing the influenza pandemic. For a vaccine to have such an impact, it must be widely available and adopted and taken up rapidly in the countries most affected. A demand forecasting model provides a valuable tool that can guide R&D spending decisions and identify policy actions to help achieving these goals. PT. Bio Farma (Persero) is the one and only stated-owned vaccine manufacturer to humans in Indonesia and the largest in Southeast Asia that has been dedicated itself in order to produce vaccines and anti-sera of international quality. One of PT. Bio Farma (Persero)’s product is flubio vaccine which are clear suspensions or slightly turbid, contain haemagglutinin of influenza virus antigen. PT. Bio Farma (Persero) did not get the opportunity to gain maximum profit from the flubio vaccine because of inadequate demand forecast. This study aimed to understand the most suitable demand forecast method for PT. Bio Farma (Persero)’s influenza vaccine. There are six demand forecasting methods used in this study, which are Moving Average, Exponential Smoothing, Holt’s Model, Winter’s Model, Seasonal ARIMA, and Causal Method. The demand data from third quarter of 2010 until second quarter of 2016 are used in this study. One of those methods which has the lowest errors will be recommended to the company to implement. This study found that from these six methods, Seasonal ARIMA is the most suitable method for PT. Bio Farma (Persero)’s influenza vaccine because it gives less errors than other methods.