BibTex Citation Data :
@article{JSINBIS37507, author = {Muhammad Ibrahim and Mustafid Mustafid}, title = {Sistem Jaminan Mutu dan Prediksi pada Rantai Pasok Ikan dari Perikanan Sungai}, journal = {Jurnal Sistem Informasi Bisnis}, volume = {11}, number = {1}, year = {2021}, keywords = {Rantai pasok Systems; Prediction Model; Quality Assurance; Fuzzy Tsukamoto; Fuzzy Mamdani}, abstract = { The supply chain system with quality assurance and fish prediction has important role for producers and consumers regarding the need for fresh fish to be consumed in certain size. The research aims to design quality assurance and predictive model for the fish supply chain system so that it is always available to consumers. The Fuzzy Tsukamoto method approach is used to design prediction model for required fish based on the fish provided by fishermen, and Fuzzy Mamdani approach is used to design model for quality assurance of fish needs that consumers need every week and month. This supply chain system is designed with upstream fishermen and fish sellers and as downstream fish retailers and fish consumers, while data analysis uses quantitative data sourced from fishermen and fish sellers and fish consumers. The prediction system and fish quality assurance provide output as a material for decision making in order to obtain information for agents and consumers that they can provide and supply fish as needed. A case study was conducted on the river fishery sector in Kota Bangun District. }, issn = {2502-2377}, pages = {43--50} doi = {10.21456/vol11iss1pp43-50}, url = {https://ejournal.undip.ac.id/index.php/jsinbis/article/view/37507} }
Refworks Citation Data :
The supply chain system with quality assurance and fish prediction has important role for producers and consumers regarding the need for fresh fish to be consumed in certain size. The research aims to design quality assurance and predictive model for the fish supply chain system so that it is always available to consumers. The Fuzzy Tsukamoto method approach is used to design prediction model for required fish based on the fish provided by fishermen, and Fuzzy Mamdani approach is used to design model for quality assurance of fish needs that consumers need every week and month. This supply chain system is designed with upstream fishermen and fish sellers and as downstream fish retailers and fish consumers, while data analysis uses quantitative data sourced from fishermen and fish sellers and fish consumers. The prediction system and fish quality assurance provide output as a material for decision making in order to obtain information for agents and consumers that they can provide and supply fish as needed. A case study was conducted on the river fishery sector in Kota Bangun District.
Article Metrics:
Last update:
Last update: 2024-12-19 22:09:49
Authors who submit the manuscripts to Journal JSINBIS must understand and agree that if the manuscript is accepted for publication, the copyright of the article belongs to JSINBIS and Diponegoro University as the journal publisher.
Copyright includes the exclusive right to reproduce and provide articles in all forms and media, including reprints, photographs, microfilm and any other similar reproductions, as well as translations. The author reserves the rights to the following:
JSINBIS and Diponegoro University and the Editors make every effort to ensure that no false or misleading data, opinions or statements are published in this journal. The content of articles published in JSINBIS is the sole and exclusive responsibility of the respective authors.
Copyright transfer agreement can be found here: [Copyright transfer agreement in doc] and [Copyright transfer agreement in pdf].
JSINBIS (Jurnal Sistem Informasi Bisnis) is published by the Magister of Information Systems, Post Graduate School Diponegoro University. It has e-ISSN: 2502-2377 dan p-ISSN: 2088-3587 . This is a National Journal accredited SINTA 2 by RISTEK DIKTI No. 48a/KPT/2017.
Journal JSINBIS which can be accessed online by http://ejournal.undip.ac.id/index.php/jsinbis is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
View My Stats