{"title":"对甘蔗产量波动的分析","authors":"Ratna Ekawati","doi":"10.36055/jiss.v7i1.10857","DOIUrl":null,"url":null,"abstract":"Received: 31 Maret 2021 Revision: 25 Oktober 2021 Accepted: 26 Oktober 2021 Sugar production owned by PT X (Persero) for the last 10 years still shows fluctuation. One of the factors is climate, including rainfall. Judging from the development, sugarcane is still vulnerable to the climate. Even so, there are still strategies to reduce the resulting risks, including by means of an appropriate cropping system. However, the safety stock of raw materials cannot be maintained because the quality of the sugarcane deteriorates very quickly. Therefore, sugarcane is continuously sourced in varying quantities and qualities from hundreds of geographically dispersed varieties and supplied to the milling process and due to changing weather conditions so that throughout the year, the time window must be considered for harvesting. Fuzzy logic is a science of uncertainty that has superior ability to process reasoning in language. In fuzzy logic theory, it is known that the concept of fuzzy systems is used in the prediction process and generally contains four stages: fuzzification, formation of fuzzy rules, fuzzy inference system reasoning, and defuzzification. Variable rainfall (mm/year), average yield (%/year), total sugarcane production (million tonnes/year) based on a triangular model of incremental uncertainty as an information attribute in the Fuzzy Inference System (FIS). The selection obtained by using the fuzzy inference system is approximately 5 points from the uncertainty factor that arises from the effect of the input on the total output of the resulting sugar cane production.","PeriodicalId":111822,"journal":{"name":"Journal Industrial Servicess","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analisis fluktuasi jumlah produksi gula tebu perbandingan bertahap triangular fuzzy inference system\",\"authors\":\"Ratna Ekawati\",\"doi\":\"10.36055/jiss.v7i1.10857\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Received: 31 Maret 2021 Revision: 25 Oktober 2021 Accepted: 26 Oktober 2021 Sugar production owned by PT X (Persero) for the last 10 years still shows fluctuation. One of the factors is climate, including rainfall. Judging from the development, sugarcane is still vulnerable to the climate. Even so, there are still strategies to reduce the resulting risks, including by means of an appropriate cropping system. However, the safety stock of raw materials cannot be maintained because the quality of the sugarcane deteriorates very quickly. Therefore, sugarcane is continuously sourced in varying quantities and qualities from hundreds of geographically dispersed varieties and supplied to the milling process and due to changing weather conditions so that throughout the year, the time window must be considered for harvesting. Fuzzy logic is a science of uncertainty that has superior ability to process reasoning in language. In fuzzy logic theory, it is known that the concept of fuzzy systems is used in the prediction process and generally contains four stages: fuzzification, formation of fuzzy rules, fuzzy inference system reasoning, and defuzzification. Variable rainfall (mm/year), average yield (%/year), total sugarcane production (million tonnes/year) based on a triangular model of incremental uncertainty as an information attribute in the Fuzzy Inference System (FIS). The selection obtained by using the fuzzy inference system is approximately 5 points from the uncertainty factor that arises from the effect of the input on the total output of the resulting sugar cane production.\",\"PeriodicalId\":111822,\"journal\":{\"name\":\"Journal Industrial Servicess\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal Industrial Servicess\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36055/jiss.v7i1.10857\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal Industrial Servicess","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36055/jiss.v7i1.10857","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
收稿日期:31 market 2021修订日期:2021年10月25日接收日期:2021年10月26日PT X (Persero)过去10年的糖产量仍有波动。其中一个因素是气候,包括降雨。从发展情况来看,甘蔗仍然容易受到气候的影响。即便如此,仍有一些策略可以减少由此带来的风险,包括采用适当的种植制度。然而,由于甘蔗的质量迅速恶化,原料的安全库存无法维持。因此,甘蔗从数百个地理上分散的品种中以不同的数量和质量不断采购,并供应给碾磨过程,由于天气条件的变化,因此在全年中,必须考虑收割的时间窗口。模糊逻辑是一门研究不确定性的科学,具有超强的语言推理能力。在模糊逻辑理论中,已知在预测过程中使用模糊系统的概念,一般包含四个阶段:模糊化、模糊规则的形成、模糊推理系统推理和去模糊化。可变降雨量(mm/年),平均产量(%/年),甘蔗总产量(万吨/年)基于增量不确定性三角形模型作为模糊推理系统(FIS)中的信息属性。使用模糊推理系统得到的选择,与投入对最终甘蔗生产总产量的影响所产生的不确定性因素约为5分。
Analisis fluktuasi jumlah produksi gula tebu perbandingan bertahap triangular fuzzy inference system
Received: 31 Maret 2021 Revision: 25 Oktober 2021 Accepted: 26 Oktober 2021 Sugar production owned by PT X (Persero) for the last 10 years still shows fluctuation. One of the factors is climate, including rainfall. Judging from the development, sugarcane is still vulnerable to the climate. Even so, there are still strategies to reduce the resulting risks, including by means of an appropriate cropping system. However, the safety stock of raw materials cannot be maintained because the quality of the sugarcane deteriorates very quickly. Therefore, sugarcane is continuously sourced in varying quantities and qualities from hundreds of geographically dispersed varieties and supplied to the milling process and due to changing weather conditions so that throughout the year, the time window must be considered for harvesting. Fuzzy logic is a science of uncertainty that has superior ability to process reasoning in language. In fuzzy logic theory, it is known that the concept of fuzzy systems is used in the prediction process and generally contains four stages: fuzzification, formation of fuzzy rules, fuzzy inference system reasoning, and defuzzification. Variable rainfall (mm/year), average yield (%/year), total sugarcane production (million tonnes/year) based on a triangular model of incremental uncertainty as an information attribute in the Fuzzy Inference System (FIS). The selection obtained by using the fuzzy inference system is approximately 5 points from the uncertainty factor that arises from the effect of the input on the total output of the resulting sugar cane production.