MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHM
As a maritime country, shrimp commodity production in Indonesia is very high and continues to increase. However, because shrimp is a perishable food, we need a detection device. This is because conventional methods that are widely used by the community in detecting freshness of shrimp are only based...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Mercu Buana
2020-11-01
|
| Series: | Jurnal Ilmiah SINERGI |
| Subjects: | |
| Online Access: | https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/8216 |
| _version_ | 1797721526013788160 |
|---|---|
| author | Aliefia Noor Evi J. Aisyah D. A. T. Safitri Mustari Mustari Yuant Tiandho |
| author_facet | Aliefia Noor Evi J. Aisyah D. A. T. Safitri Mustari Mustari Yuant Tiandho |
| author_sort | Aliefia Noor |
| collection | DOAJ |
| description | As a maritime country, shrimp commodity production in Indonesia is very high and continues to increase. However, because shrimp is a perishable food, we need a detection device. This is because conventional methods that are widely used by the community in detecting freshness of shrimp are only based on the smell. Of course, this is a problem when shrimp are packed in closed containers. In this paper, a method for detecting shrimp is proposed using the Melastoma malabathricum L. - based label indicator. The high content of flavonoids in the extracts allows the changing the colour of the label from red to grey due to the interaction between the label with the OH- group that arises from the shrimp spoilage process. The colour that appears on the label indicator will correlate with the level of shrimp freshness. By increasing detection effectiveness, the classification is performed using the nearest-neighbours algorithm, which is equipped with an image processing mechanism in the form of colour quantization. There are four classifications used to express the quality of shrimp, namely "acceptable," "just acceptable," "unacceptable," and "more unacceptable." The accuracy of applying this method is 71.9%, with the majority of detection errors occurring in the "acceptable" class. Based on these results, it can be stated that the label indicators prepared in this study are very promising to be developed into intelligent packaging components. |
| first_indexed | 2024-03-12T09:34:31Z |
| format | Article |
| id | doaj.art-cc7b580eb7674856ad482a0a7edb12c1 |
| institution | Directory Open Access Journal |
| issn | 1410-2331 2460-1217 |
| language | English |
| last_indexed | 2024-03-12T09:34:31Z |
| publishDate | 2020-11-01 |
| publisher | Universitas Mercu Buana |
| record_format | Article |
| series | Jurnal Ilmiah SINERGI |
| spelling | doaj.art-cc7b580eb7674856ad482a0a7edb12c12023-09-02T13:48:56ZengUniversitas Mercu BuanaJurnal Ilmiah SINERGI1410-23312460-12172020-11-01251697410.22441/sinergi.2021.1.0093749MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHMAliefia Noor0Evi J.1Aisyah D. A. T. Safitri2Mustari Mustari3Yuant Tiandho4Department of Physics, Faculty of Engineering, Universitas Bangka BelitungDepartment of Physics, Faculty of Engineering, Universitas Bangka BelitungDepartment of Physics, Faculty of Engineering, Universitas Bangka BelitungDepartment of Physics, Faculty of Engineering, Universitas Bangka BelitungDepartment of Physics, Faculty of Engineering, Universitas Bangka BelitungAs a maritime country, shrimp commodity production in Indonesia is very high and continues to increase. However, because shrimp is a perishable food, we need a detection device. This is because conventional methods that are widely used by the community in detecting freshness of shrimp are only based on the smell. Of course, this is a problem when shrimp are packed in closed containers. In this paper, a method for detecting shrimp is proposed using the Melastoma malabathricum L. - based label indicator. The high content of flavonoids in the extracts allows the changing the colour of the label from red to grey due to the interaction between the label with the OH- group that arises from the shrimp spoilage process. The colour that appears on the label indicator will correlate with the level of shrimp freshness. By increasing detection effectiveness, the classification is performed using the nearest-neighbours algorithm, which is equipped with an image processing mechanism in the form of colour quantization. There are four classifications used to express the quality of shrimp, namely "acceptable," "just acceptable," "unacceptable," and "more unacceptable." The accuracy of applying this method is 71.9%, with the majority of detection errors occurring in the "acceptable" class. Based on these results, it can be stated that the label indicators prepared in this study are very promising to be developed into intelligent packaging components.https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/8216classification technologyintelligent packagingnearest neighbours algorithmshrimp |
| spellingShingle | Aliefia Noor Evi J. Aisyah D. A. T. Safitri Mustari Mustari Yuant Tiandho MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHM Jurnal Ilmiah SINERGI classification technology intelligent packaging nearest neighbours algorithm shrimp |
| title | MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHM |
| title_full | MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHM |
| title_fullStr | MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHM |
| title_full_unstemmed | MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHM |
| title_short | MELASTOMA MALABATHRICUM L. EXTRACTS-BASED INDICATOR FOR MONITORING SHRIMP FRESHNESS INTEGRATED WITH CLASSIFICATION TECHNOLOGY USING NEAREST NEIGHBOURS ALGORITHM |
| title_sort | melastoma malabathricum l extracts based indicator for monitoring shrimp freshness integrated with classification technology using nearest neighbours algorithm |
| topic | classification technology intelligent packaging nearest neighbours algorithm shrimp |
| url | https://publikasi.mercubuana.ac.id/index.php/sinergi/article/view/8216 |
| work_keys_str_mv | AT aliefianoor melastomamalabathricumlextractsbasedindicatorformonitoringshrimpfreshnessintegratedwithclassificationtechnologyusingnearestneighboursalgorithm AT evij melastomamalabathricumlextractsbasedindicatorformonitoringshrimpfreshnessintegratedwithclassificationtechnologyusingnearestneighboursalgorithm AT aisyahdatsafitri melastomamalabathricumlextractsbasedindicatorformonitoringshrimpfreshnessintegratedwithclassificationtechnologyusingnearestneighboursalgorithm AT mustarimustari melastomamalabathricumlextractsbasedindicatorformonitoringshrimpfreshnessintegratedwithclassificationtechnologyusingnearestneighboursalgorithm AT yuanttiandho melastomamalabathricumlextractsbasedindicatorformonitoringshrimpfreshnessintegratedwithclassificationtechnologyusingnearestneighboursalgorithm |