IMPROVING SUBSIDIZED UREA FERTILIZER DEMAND FORECASTING ACCURACY USING SIX SIGMA DMAIC AT PT PUPUK INDONESIA (PERSERO)
PT Pupuk Indonesia is the holding company of 5 (five) fertilizer-producing subsidiaries, namely PT Pupuk Iskandar Muda, PT Pupuk Sriwidjaja Palembang, PT Pupuk Kujang Cikampek, PT Petrokimia Gresik and PT Pupuk Kalimantan Timur, which annually produces 9,362,500 tons of urea fertilizer. The produ...
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id-itb.:748612023-07-24T11:02:30ZIMPROVING SUBSIDIZED UREA FERTILIZER DEMAND FORECASTING ACCURACY USING SIX SIGMA DMAIC AT PT PUPUK INDONESIA (PERSERO) Jati, Susatyo Manajemen umum Indonesia Theses Six Sigma DMAIC, Time series forecasting, Urea fertilizer, Accuracy, PT Pupuk Indonesia INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/74861 PT Pupuk Indonesia is the holding company of 5 (five) fertilizer-producing subsidiaries, namely PT Pupuk Iskandar Muda, PT Pupuk Sriwidjaja Palembang, PT Pupuk Kujang Cikampek, PT Petrokimia Gresik and PT Pupuk Kalimantan Timur, which annually produces 9,362,500 tons of urea fertilizer. The production is divided to meet the needs of subsidized fertilizers, non-subsidized fertilizers, and other fertilizer raw materials. PT Pupuk Indonesia received an order from the government to distribute subsidized fertilizers in Indonesia through a contract with the Ministry of Agriculture. Based on this, PT Pupuk Indonesia prioritizes production to fulfill subsidized fertilizers and the rest produces nonsubsidized fertilizers for commercial sale. In implementing the distribution of subsidized fertilizers, it is necessary to carry out sales planning considering that the needs in the field are not necessarily in accordance with the allocations set by the Government. This is to anticipate if production is too high it will cause high stock and increased inventory costs, but on the one hand, these products can be optimized for sales of non-subsidized products. This research aims to identify optimal solutions to overcome significant differences between projections and actual demand at PT Pupuk Indonesia. Through the Six Sigma DMAIC method, problem analysis was carried out and it was found that sales forecasting problems had not used the right method. Therefore, a time series method is proposed using decomposition time series, focusing on the analysis of seasonal patterns, trends, and residuals. Historical data on demand for subsidized urea fertilizer from PT Pupuk Indonesia is used as a basis for analysis. The practical implications of this research highlight the importance of PT Pupuk Indonesia adopting a more scientific and in-depth forecasting approach to managing urea fertilizer supplies. By applying the time series decomposition method, companies can improve forecasting accuracy and reduce the risk of inventory not matching demand. This will optimize operational efficiency and increase customer satisfaction. text |
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Manajemen umum Jati, Susatyo IMPROVING SUBSIDIZED UREA FERTILIZER DEMAND FORECASTING ACCURACY USING SIX SIGMA DMAIC AT PT PUPUK INDONESIA (PERSERO) |
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PT Pupuk Indonesia is the holding company of 5 (five) fertilizer-producing subsidiaries,
namely PT Pupuk Iskandar Muda, PT Pupuk Sriwidjaja Palembang, PT Pupuk Kujang
Cikampek, PT Petrokimia Gresik and PT Pupuk Kalimantan Timur, which annually
produces 9,362,500 tons of urea fertilizer. The production is divided to meet the needs of
subsidized fertilizers, non-subsidized fertilizers, and other fertilizer raw materials. PT
Pupuk Indonesia received an order from the government to distribute subsidized fertilizers
in Indonesia through a contract with the Ministry of Agriculture. Based on this, PT Pupuk
Indonesia prioritizes production to fulfill subsidized fertilizers and the rest produces nonsubsidized
fertilizers for commercial sale.
In implementing the distribution of subsidized fertilizers, it is necessary to carry out sales planning considering that the needs
in the field are not necessarily in accordance with the allocations set by the Government. This is to anticipate if production is too high it will
cause high stock and increased inventory costs, but on the one hand, these products can be
optimized for sales of non-subsidized products.
This research aims to identify optimal solutions to overcome significant differences
between projections and actual demand at PT Pupuk Indonesia. Through the Six Sigma
DMAIC method, problem analysis was carried out and it was found that sales forecasting
problems had not used the right method. Therefore, a time series method is proposed using
decomposition time series, focusing on the analysis of seasonal patterns, trends, and
residuals. Historical data on demand for subsidized urea fertilizer from PT Pupuk Indonesia
is used as a basis for analysis.
The practical implications of this research highlight the importance of PT Pupuk Indonesia
adopting a more scientific and in-depth forecasting approach to managing urea fertilizer
supplies. By applying the time series decomposition method, companies can improve
forecasting accuracy and reduce the risk of inventory not matching demand. This will
optimize operational efficiency and increase customer satisfaction.
|
format |
Theses |
author |
Jati, Susatyo |
author_facet |
Jati, Susatyo |
author_sort |
Jati, Susatyo |
title |
IMPROVING SUBSIDIZED UREA FERTILIZER DEMAND FORECASTING ACCURACY USING SIX SIGMA DMAIC AT PT PUPUK INDONESIA (PERSERO) |
title_short |
IMPROVING SUBSIDIZED UREA FERTILIZER DEMAND FORECASTING ACCURACY USING SIX SIGMA DMAIC AT PT PUPUK INDONESIA (PERSERO) |
title_full |
IMPROVING SUBSIDIZED UREA FERTILIZER DEMAND FORECASTING ACCURACY USING SIX SIGMA DMAIC AT PT PUPUK INDONESIA (PERSERO) |
title_fullStr |
IMPROVING SUBSIDIZED UREA FERTILIZER DEMAND FORECASTING ACCURACY USING SIX SIGMA DMAIC AT PT PUPUK INDONESIA (PERSERO) |
title_full_unstemmed |
IMPROVING SUBSIDIZED UREA FERTILIZER DEMAND FORECASTING ACCURACY USING SIX SIGMA DMAIC AT PT PUPUK INDONESIA (PERSERO) |
title_sort |
improving subsidized urea fertilizer demand forecasting accuracy using six sigma dmaic at pt pupuk indonesia (persero) |
url |
https://digilib.itb.ac.id/gdl/view/74861 |
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1822007513109757952 |