PERBANDINGAN PENGOLAHAN DATA PREDIKSI PERSEDIAAN GAS LPG 3KG MENGGUNAKAN REGRESI LINIER BERGANDA DAN K-MEANS - Annisa Rismanitanti; Rima Mawarni; Sidik Rahmatullah; Dwi Marisa Efendi; Sulis Nurbaiti (Jurnal Informatika, 2022)
he oil and natural gas sector is a sector that is used with great importance for Indonesia's national development. An interesting commodity to watch out for in the oil and gas industry is liquefied petroleum gas (LPG). LPG is a hydrocarbon gas that has been liquefied under pressure to facilitate storage, transportation, and handling and the main ingredients consist of propane/C3, butane/C4 or can be mixed to produce mixed LPG..At this time PT. BLORA MUSTIKA does not focus on when household needs increase and when not, the meaning of this is that LPG gas data is not used properly and is only recorded, this of course makes PT BLORA MUSTIKA unable to predict demand from sub-distributors and results in frequent an empty supply of LPG gas causing difficulties for the community to obtain 3 Kg LPG gas. This problem can be calculated and compared with the Multiple Linear Regression and K-Means methods.By using the Multiple Linear Regression and K-Means method, it is hoped that it will make it easier for PT. BLORA MUSTIKA in determining demand predictions from sub-distributors so that there is no shortage of LPG gas supplies and which method can be obtained which is more effective and efficient.