OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD
Interpolation is a method to determine the value that is between two values and is known from the data. In some cases, the data obtained is incomplete due to limitations in data collection. Interpolation techniques can be used to obtain approximate data. In this study, the Lagrange interpolation met...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Pattimura
2023-09-01
|
| Series: | Barekeng |
| Subjects: | |
| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7582 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849407865392988160 |
|---|---|
| author | Eka Susanti Fitri Maya Puspita Evi Yuliza Siti Suzlin Supadi Oki Dwipurwani Novi Rustiana Dewi Ahmad Farhan Ramadhan Ahmad Rindarto |
| author_facet | Eka Susanti Fitri Maya Puspita Evi Yuliza Siti Suzlin Supadi Oki Dwipurwani Novi Rustiana Dewi Ahmad Farhan Ramadhan Ahmad Rindarto |
| author_sort | Eka Susanti |
| collection | DOAJ |
| description | Interpolation is a method to determine the value that is between two values and is known from the data. In some cases, the data obtained is incomplete due to limitations in data collection. Interpolation techniques can be used to obtain approximate data. In this study, the Lagrange interpolation method of degree 2 and degree 3 is used to interpolate the data on rice demand. A trapezoidal fuzzy number expresses the demand data obtained from the interpolation. The other parameters are obtained from company data related to rice supplies and are expressed as trapezoidal fuzzy numbers. The interpolation accuracy rate is calculated using Mean Error Percentage (MAPE). The second-degree interpolation method produces a MAPE value of 30.76 percent, while the third-degree interpolation has a MAPE of 32.92 percent. The quantity of order respectively 202677 kg, 384610 kg, 1012357 kg, 1447963 kg, and a Total inventory cost of Rp. 129231797951. |
| format | Article |
| id | doaj-art-b72e0c3dca1f4f17a9aa819feff06c54 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2023-09-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-b72e0c3dca1f4f17a9aa819feff06c542025-08-20T03:35:55ZengUniversitas PattimuraBarekeng1978-72272615-30172023-09-011731215122010.30598/barekengvol17iss3pp1215-12207582OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHODEka Susanti0Fitri Maya Puspita1Evi Yuliza2Siti Suzlin Supadi3Oki Dwipurwani4Novi Rustiana Dewi5Ahmad Farhan Ramadhan6Ahmad Rindarto7Science Doctoral Program, Mathematic and Natural Science, Universitas Sriwijaya, IndonesiaDepartment of Mathematics, Universitas Sriwijaya, IndonesiaDepartment of Mathematics, Universitas Sriwijaya, IndonesiaInstitute of Mathematics Sciences, University of Malaya, MalaysiaDepartment of Mathematics, Universitas Sriwijaya, IndonesiaDepartment of Mathematics, Universitas Sriwijaya, IndonesiaDepartment of Mathematics, Universitas Sriwijaya, IndonesiaDepartment of Mathematics, Universitas Sriwijaya, IndonesiaInterpolation is a method to determine the value that is between two values and is known from the data. In some cases, the data obtained is incomplete due to limitations in data collection. Interpolation techniques can be used to obtain approximate data. In this study, the Lagrange interpolation method of degree 2 and degree 3 is used to interpolate the data on rice demand. A trapezoidal fuzzy number expresses the demand data obtained from the interpolation. The other parameters are obtained from company data related to rice supplies and are expressed as trapezoidal fuzzy numbers. The interpolation accuracy rate is calculated using Mean Error Percentage (MAPE). The second-degree interpolation method produces a MAPE value of 30.76 percent, while the third-degree interpolation has a MAPE of 32.92 percent. The quantity of order respectively 202677 kg, 384610 kg, 1012357 kg, 1447963 kg, and a Total inventory cost of Rp. 129231797951.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7582fuzzy eoqlagrange interpolationtrapezoidal fuzzy number |
| spellingShingle | Eka Susanti Fitri Maya Puspita Evi Yuliza Siti Suzlin Supadi Oki Dwipurwani Novi Rustiana Dewi Ahmad Farhan Ramadhan Ahmad Rindarto OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD Barekeng fuzzy eoq lagrange interpolation trapezoidal fuzzy number |
| title | OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD |
| title_full | OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD |
| title_fullStr | OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD |
| title_full_unstemmed | OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD |
| title_short | OPTIMIZATION OF RICE INVENTORY USING FUZZY INVENTORY MODEL AND LAGRANGE INTERPOLATION METHOD |
| title_sort | optimization of rice inventory using fuzzy inventory model and lagrange interpolation method |
| topic | fuzzy eoq lagrange interpolation trapezoidal fuzzy number |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7582 |
| work_keys_str_mv | AT ekasusanti optimizationofriceinventoryusingfuzzyinventorymodelandlagrangeinterpolationmethod AT fitrimayapuspita optimizationofriceinventoryusingfuzzyinventorymodelandlagrangeinterpolationmethod AT eviyuliza optimizationofriceinventoryusingfuzzyinventorymodelandlagrangeinterpolationmethod AT sitisuzlinsupadi optimizationofriceinventoryusingfuzzyinventorymodelandlagrangeinterpolationmethod AT okidwipurwani optimizationofriceinventoryusingfuzzyinventorymodelandlagrangeinterpolationmethod AT novirustianadewi optimizationofriceinventoryusingfuzzyinventorymodelandlagrangeinterpolationmethod AT ahmadfarhanramadhan optimizationofriceinventoryusingfuzzyinventorymodelandlagrangeinterpolationmethod AT ahmadrindarto optimizationofriceinventoryusingfuzzyinventorymodelandlagrangeinterpolationmethod |