Rohmanita Duanaputri, S. Sulistyowati, Putra Aulia Insani
{"title":"用线性回归方法分析东爪哇工业部门的电能需求","authors":"Rohmanita Duanaputri, S. Sulistyowati, Putra Aulia Insani","doi":"10.33795/eltek.v20i2.352","DOIUrl":null,"url":null,"abstract":"Abstrak \nPada kehidupan sekarang maupun akan datang, energi listrik menjadi kebutuhan pokok masyarakat. Kebutuhan energi listrik selalu mengalami peningkatan, diikuti meningkatnya pertumbuhan penduduk. Permasalahan akan muncul apabila kebutuhan energi listrik tidak diperkirakan. Maka perlu dilakukan peramalan kebutuhan energi listrik untuk memprediksikan ketersediaan energi listrik di masa mendatang. Pada penelitian ini, dilakukan peramalan kebutuhan energi listrik menggunakan metode regresi linier pada sektor industri di Jawa Timur untuk tahun 2023-2027. Berdasarkan hasil perhitungan prediksi dan MAPE (2009-2021), didapatkan metode regresi linier masih baik dan layak digunakan menurut standar MAPE. Kemudian dibandingkan hasil prediksi dan MAPE (2010-2020) antara metode regresi linear dengan metode time series pada penelitian sebelumnya, didapatkan metode time series menghasilkan prediksi dan MAPE lebih baik dibanding metode regresi linier pada pelanggan listrik, sedangkan pada daya tersambung, energi listrik terjual, dan pendapatan penjualan energi listrik didapatkan metode regresi linier menghasilkan prediksi dan MAPE lebih baik dibanding metode time series. Tetapi, penulis menghitung peramalan kebutuhan energi listrik pada sektor industri di Jawa Timur (2023-2027) hanya menggunakan metode regresi linier. Sehingga dihasilkan akan terjadi kenaikan setiap tahun dengan rata-rata untuk pelanggan listrik sebesar 5.264 pelanggan, daya tersambung sebesar 328,49 MVA, energi listrik terjual sebesar 580,64 GWh, dan pendapatan penjualan energi listrik sebesar 1.065.266,21 Juta Rupiah. Menurut hasil tersebut, maka pasokan energi listrik harus tercukupi dengan merencanakan pengembangan atau penambahan kapasitas pembangkit listrik. \nAbstract \nIn present and future life, electrical energy becomes basic needs of community. Electrical energy needs always increased, followed by increased population growth. Problem will appear if electrical energy needs is not expected. Therefore, it is necessary to forecast electrical energy needs to predict the availability of electrical energy in future. In this study, calculation of forecasting electrical energy needs using linear regression methods in industrial sector in East Java for 2023-2027. Based on calculation results of prediction and MAPE (2009-2021), it is obtained linear regression method is still good and worthy of use according to MAPE standard. Then comparison results of prediction and MAPE (2010-2020) between linear regression method with time series method in previous study, it was obtained that time series method produced predictive and MAPE is better than linear regression methods on electricity customers, while in power connected, electric energy sold, and earnings of electrical energy sales obtained linear regression method produces predictive and MAPE better than time series method. However, authors calculation of electrical energy needs in industrial sector in East Java (2023-2027) only using linear regression methods. So there will be increase every year with average for electricity customers of 5,264 customers, power connected of 328.49 MVA, electric energy sold of 580.64 GWh, and earnings of electrical energy sales of 1,065,266.21 million rupiah. According to results, supply of electrical energy should be fulfilled by planning development or additional power plant capacity.","PeriodicalId":53405,"journal":{"name":"Jurnal Eltek","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Analisis peramalan kebutuhan energi listrik sektor industri di Jawa Timur dengan metode regresi linear\",\"authors\":\"Rohmanita Duanaputri, S. Sulistyowati, Putra Aulia Insani\",\"doi\":\"10.33795/eltek.v20i2.352\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstrak \\nPada kehidupan sekarang maupun akan datang, energi listrik menjadi kebutuhan pokok masyarakat. Kebutuhan energi listrik selalu mengalami peningkatan, diikuti meningkatnya pertumbuhan penduduk. Permasalahan akan muncul apabila kebutuhan energi listrik tidak diperkirakan. Maka perlu dilakukan peramalan kebutuhan energi listrik untuk memprediksikan ketersediaan energi listrik di masa mendatang. Pada penelitian ini, dilakukan peramalan kebutuhan energi listrik menggunakan metode regresi linier pada sektor industri di Jawa Timur untuk tahun 2023-2027. Berdasarkan hasil perhitungan prediksi dan MAPE (2009-2021), didapatkan metode regresi linier masih baik dan layak digunakan menurut standar MAPE. Kemudian dibandingkan hasil prediksi dan MAPE (2010-2020) antara metode regresi linear dengan metode time series pada penelitian sebelumnya, didapatkan metode time series menghasilkan prediksi dan MAPE lebih baik dibanding metode regresi linier pada pelanggan listrik, sedangkan pada daya tersambung, energi listrik terjual, dan pendapatan penjualan energi listrik didapatkan metode regresi linier menghasilkan prediksi dan MAPE lebih baik dibanding metode time series. Tetapi, penulis menghitung peramalan kebutuhan energi listrik pada sektor industri di Jawa Timur (2023-2027) hanya menggunakan metode regresi linier. Sehingga dihasilkan akan terjadi kenaikan setiap tahun dengan rata-rata untuk pelanggan listrik sebesar 5.264 pelanggan, daya tersambung sebesar 328,49 MVA, energi listrik terjual sebesar 580,64 GWh, dan pendapatan penjualan energi listrik sebesar 1.065.266,21 Juta Rupiah. Menurut hasil tersebut, maka pasokan energi listrik harus tercukupi dengan merencanakan pengembangan atau penambahan kapasitas pembangkit listrik. \\nAbstract \\nIn present and future life, electrical energy becomes basic needs of community. Electrical energy needs always increased, followed by increased population growth. Problem will appear if electrical energy needs is not expected. Therefore, it is necessary to forecast electrical energy needs to predict the availability of electrical energy in future. In this study, calculation of forecasting electrical energy needs using linear regression methods in industrial sector in East Java for 2023-2027. Based on calculation results of prediction and MAPE (2009-2021), it is obtained linear regression method is still good and worthy of use according to MAPE standard. Then comparison results of prediction and MAPE (2010-2020) between linear regression method with time series method in previous study, it was obtained that time series method produced predictive and MAPE is better than linear regression methods on electricity customers, while in power connected, electric energy sold, and earnings of electrical energy sales obtained linear regression method produces predictive and MAPE better than time series method. However, authors calculation of electrical energy needs in industrial sector in East Java (2023-2027) only using linear regression methods. So there will be increase every year with average for electricity customers of 5,264 customers, power connected of 328.49 MVA, electric energy sold of 580.64 GWh, and earnings of electrical energy sales of 1,065,266.21 million rupiah. According to results, supply of electrical energy should be fulfilled by planning development or additional power plant capacity.\",\"PeriodicalId\":53405,\"journal\":{\"name\":\"Jurnal Eltek\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jurnal Eltek\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.33795/eltek.v20i2.352\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Eltek","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33795/eltek.v20i2.352","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
无论是现在还是未来,电力都是社会的基本需求。电力需求一直在增加,随之而来的是人口增长。当电力需求得不到预测时,问题就会出现。预测电力未来的可用性是必要的。在这项研究中,电子能源的需求是利用东爪哇工业部门的线性回归方法进行的,一直持续到2023-2027年。根据预测计算和MAPE(2009-2021)的结果,获得了线性回归的方法仍然是好的,并值得按照MAPE的标准使用。然后预测结果相比,MAPE(2010-2020)之间的线性回归的方法与先前的时间系列的研究方法,获得大赛时间产生方法预测和MAPE比线性回归方法在电力客户,而电源连接,电能的价格售出,销售电能得到线性回归方法产生的收入预测和MAPE比时间系列的方法。然而,作者计算了东爪哇工业部门(2023-2027)电力需求的可变只是使用了线性回归方法。因此,电力客户每年平均增加5264人,电力供应为328.49 MVA,电力销售总额为580.64 GWh,电力销售总额为106562662200万卢比,电力销售总额为10656662200万卢比。根据这些结果,电力供应必须通过计划开发或增加发电能力来满足。在现在和未来的生活中,电力基本上满足了社区的需要。电力需求总是在增加,随着人口增长的增长。如果电力需求是预期不到的,问题就会出现。因此,有必要预测未来的电力使用。在这项研究中,电前能量计算需要在2023-2027年的爪哇东产业区使用线性回归方法。基于prediction和MAPE(2009-2021)的计算结果,这仍然是一个线性回归方法,其使用方法与MAPE标准相适应的好处。然后不那么可怜results of prediction and MAPE)(2010-2020)之间线性regression方法和时间系列研究方法在previous,是获得那个时代系列方法由predictive和MAPE是比线性regression方法在电力customers,连通,电力能源电力而在出售了,and earnings of电能源销售获得regression线性方法produces predictive和MAPE比时间系列的方法。However, a.d.d.电气能源计算部门(2023-2027)只使用线性后悔方法。因此,平均每年将增加5.264个客户,328.49 MVA的电源,580.64 GWh的电能销售,以及1065.266亿卢比的电能销售业绩。根据可再生的规定,电力供应应由规划开发或附加型电力工厂电厂满足。
Analisis peramalan kebutuhan energi listrik sektor industri di Jawa Timur dengan metode regresi linear
Abstrak
Pada kehidupan sekarang maupun akan datang, energi listrik menjadi kebutuhan pokok masyarakat. Kebutuhan energi listrik selalu mengalami peningkatan, diikuti meningkatnya pertumbuhan penduduk. Permasalahan akan muncul apabila kebutuhan energi listrik tidak diperkirakan. Maka perlu dilakukan peramalan kebutuhan energi listrik untuk memprediksikan ketersediaan energi listrik di masa mendatang. Pada penelitian ini, dilakukan peramalan kebutuhan energi listrik menggunakan metode regresi linier pada sektor industri di Jawa Timur untuk tahun 2023-2027. Berdasarkan hasil perhitungan prediksi dan MAPE (2009-2021), didapatkan metode regresi linier masih baik dan layak digunakan menurut standar MAPE. Kemudian dibandingkan hasil prediksi dan MAPE (2010-2020) antara metode regresi linear dengan metode time series pada penelitian sebelumnya, didapatkan metode time series menghasilkan prediksi dan MAPE lebih baik dibanding metode regresi linier pada pelanggan listrik, sedangkan pada daya tersambung, energi listrik terjual, dan pendapatan penjualan energi listrik didapatkan metode regresi linier menghasilkan prediksi dan MAPE lebih baik dibanding metode time series. Tetapi, penulis menghitung peramalan kebutuhan energi listrik pada sektor industri di Jawa Timur (2023-2027) hanya menggunakan metode regresi linier. Sehingga dihasilkan akan terjadi kenaikan setiap tahun dengan rata-rata untuk pelanggan listrik sebesar 5.264 pelanggan, daya tersambung sebesar 328,49 MVA, energi listrik terjual sebesar 580,64 GWh, dan pendapatan penjualan energi listrik sebesar 1.065.266,21 Juta Rupiah. Menurut hasil tersebut, maka pasokan energi listrik harus tercukupi dengan merencanakan pengembangan atau penambahan kapasitas pembangkit listrik.
Abstract
In present and future life, electrical energy becomes basic needs of community. Electrical energy needs always increased, followed by increased population growth. Problem will appear if electrical energy needs is not expected. Therefore, it is necessary to forecast electrical energy needs to predict the availability of electrical energy in future. In this study, calculation of forecasting electrical energy needs using linear regression methods in industrial sector in East Java for 2023-2027. Based on calculation results of prediction and MAPE (2009-2021), it is obtained linear regression method is still good and worthy of use according to MAPE standard. Then comparison results of prediction and MAPE (2010-2020) between linear regression method with time series method in previous study, it was obtained that time series method produced predictive and MAPE is better than linear regression methods on electricity customers, while in power connected, electric energy sold, and earnings of electrical energy sales obtained linear regression method produces predictive and MAPE better than time series method. However, authors calculation of electrical energy needs in industrial sector in East Java (2023-2027) only using linear regression methods. So there will be increase every year with average for electricity customers of 5,264 customers, power connected of 328.49 MVA, electric energy sold of 580.64 GWh, and earnings of electrical energy sales of 1,065,266.21 million rupiah. According to results, supply of electrical energy should be fulfilled by planning development or additional power plant capacity.