{"title":"Peramalan Curah Hujan Terhadap Produktivitas Garam Di Gersik Putih Sumenep","authors":"Tifani Noviasari, Nike Ika Nuzula, Makhfud Efendy, Angga Arifta Febrianto, A. Darmadi","doi":"10.14710/jkt.v26i1.16139","DOIUrl":null,"url":null,"abstract":"Salt production in Madura Island is running by evaporation method (solar evaporator). Thus, the process of salt production is highly dependent on weather factors. Weather conditions is one of the determinants of the success of salt production targets. In this study aims to determine the forecasting process of rainfall in support of salt production process at PT Garam Gersik Putih Sumenep. The method used to analyze rainfall data on PT Garam Gersik Putih in 2022 is the box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) is one of the time series forecasting methods using values in the past as dependent variables and independent variables. From the forecast results, it is known that Gersik Putih Pheasant has 9 dry dasarian with an estimated production of 27,360 tons. Saltworks Gersik Putih has 456 plots of crystallization land with a total land area of 126.36 Ha. The results of weather forecasting analysis can determine the time of pre-production , salt production and post-production of salt. Pre-production of salt is an activity of preparation and maintenance of infrastructure to maximize the upcoming dry season. Pre-production of salt is carried out from January to May. Salt production activities are processing sea water into salt crystals that take place from June to early november. At the peak of drought in 1 plot of land crystallization can produce 3-6 tons in one harvest. Post salt production is the activity of transporting salt from pheasant land to olo warehouse which is carried out from November to December due to the increase in rainfall intensity. The box-Jenkins integrated Moving Average (ARIMA) Autoregressive Model applied has a pearson coefficient correlation level of 0,94%. The correlation value of the pearson coefficient shows that forecasting is very good, adequate and feasible to use. Produksi garam di Pulau Madura dilakukan dengan menggunakan metode penguapan (solar evaporator). Proses produksi garam bergantung pada curah hujan. Curah hujan menjadi penentu keberhasilan produksi garam. Pada penelitian ini bertujuan untuk mengetahui proses peramalan curah hujan dalam mendukung proses produksi garam pada PT Garam Gersik Putih Sumenep. Metode peramalan data curah hujan pada PT Garam Gersik Putih tahun 2022 adalah model Autoregressive Integrated Moving Average (ARIMA) Boox-Jenkins. ARIMA Boox-Jenkins adalah salah satu metode peramalan menggunakan nilai variabel independen dan variabel dependen. Dari hasil prakiraan diketahui bahwa pegaraman Gersik Putih memiliki ±9 dasarian kering dengan estimasi hasil produksi sebesar 27.360 ton. Pegaraman Gersik Putih memiliki 456 petak lahan kristalisasi dengan jumlah luas lahan 126,36 Ha. Hasil analisis peramalan cuaca juga dapat menentukan kapan berlangsungnya pra produksi garam, produksi garam serta pasca produksi garam. Pra produksi garam merupakan kegiatan persiapan dan pemeliharaan sarana prasarana untuk memaksimalkan musim kemarau mendatang. Pra produksi garam dilaksanakan pada bulan januari hingga mei. Kegiatan produksi garam yaitu mengolah air laut hingga menjadi kristal garam yang berlangsung bulan juni hingga november awal. Pada puncak kemarau dalam 1 petak lahan kristalisasi dapat menghasilkan 3 – 6 ton dalam sekali panen. Pasca produksi garam adalah kegiatan pengangkutan garam dari lahan pegaraman menuju gudang olo yang dilaksanakan bulan november hingga desember karena kenaikan intensitas curah hujan. Model Autoregressive Integrated Moving Average (ARIMA) Boox-Jenkins yang diterapkan memiliki tingkat korelasi koefisien pearson sebesar 0,94%. Nilai korelasi koefisien pearson tersebut layak untuk digunakan untuk metode peramalan.","PeriodicalId":53001,"journal":{"name":"Jurnal Kelautan Tropis","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Kelautan Tropis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14710/jkt.v26i1.16139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Salt production in Madura Island is running by evaporation method (solar evaporator). Thus, the process of salt production is highly dependent on weather factors. Weather conditions is one of the determinants of the success of salt production targets. In this study aims to determine the forecasting process of rainfall in support of salt production process at PT Garam Gersik Putih Sumenep. The method used to analyze rainfall data on PT Garam Gersik Putih in 2022 is the box-Jenkins Autoregressive Integrated Moving Average (ARIMA) model. Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) is one of the time series forecasting methods using values in the past as dependent variables and independent variables. From the forecast results, it is known that Gersik Putih Pheasant has 9 dry dasarian with an estimated production of 27,360 tons. Saltworks Gersik Putih has 456 plots of crystallization land with a total land area of 126.36 Ha. The results of weather forecasting analysis can determine the time of pre-production , salt production and post-production of salt. Pre-production of salt is an activity of preparation and maintenance of infrastructure to maximize the upcoming dry season. Pre-production of salt is carried out from January to May. Salt production activities are processing sea water into salt crystals that take place from June to early november. At the peak of drought in 1 plot of land crystallization can produce 3-6 tons in one harvest. Post salt production is the activity of transporting salt from pheasant land to olo warehouse which is carried out from November to December due to the increase in rainfall intensity. The box-Jenkins integrated Moving Average (ARIMA) Autoregressive Model applied has a pearson coefficient correlation level of 0,94%. The correlation value of the pearson coefficient shows that forecasting is very good, adequate and feasible to use. Produksi garam di Pulau Madura dilakukan dengan menggunakan metode penguapan (solar evaporator). Proses produksi garam bergantung pada curah hujan. Curah hujan menjadi penentu keberhasilan produksi garam. Pada penelitian ini bertujuan untuk mengetahui proses peramalan curah hujan dalam mendukung proses produksi garam pada PT Garam Gersik Putih Sumenep. Metode peramalan data curah hujan pada PT Garam Gersik Putih tahun 2022 adalah model Autoregressive Integrated Moving Average (ARIMA) Boox-Jenkins. ARIMA Boox-Jenkins adalah salah satu metode peramalan menggunakan nilai variabel independen dan variabel dependen. Dari hasil prakiraan diketahui bahwa pegaraman Gersik Putih memiliki ±9 dasarian kering dengan estimasi hasil produksi sebesar 27.360 ton. Pegaraman Gersik Putih memiliki 456 petak lahan kristalisasi dengan jumlah luas lahan 126,36 Ha. Hasil analisis peramalan cuaca juga dapat menentukan kapan berlangsungnya pra produksi garam, produksi garam serta pasca produksi garam. Pra produksi garam merupakan kegiatan persiapan dan pemeliharaan sarana prasarana untuk memaksimalkan musim kemarau mendatang. Pra produksi garam dilaksanakan pada bulan januari hingga mei. Kegiatan produksi garam yaitu mengolah air laut hingga menjadi kristal garam yang berlangsung bulan juni hingga november awal. Pada puncak kemarau dalam 1 petak lahan kristalisasi dapat menghasilkan 3 – 6 ton dalam sekali panen. Pasca produksi garam adalah kegiatan pengangkutan garam dari lahan pegaraman menuju gudang olo yang dilaksanakan bulan november hingga desember karena kenaikan intensitas curah hujan. Model Autoregressive Integrated Moving Average (ARIMA) Boox-Jenkins yang diterapkan memiliki tingkat korelasi koefisien pearson sebesar 0,94%. Nilai korelasi koefisien pearson tersebut layak untuk digunakan untuk metode peramalan.
马杜拉岛的盐生产采用蒸发法。因此,盐的生产过程在很大程度上取决于天气因素。天气条件是盐生产目标能否成功的决定因素之一。本研究旨在确定支持PT Garam Gersik Putih Sumenep盐生产过程的降雨预测过程。用于分析PT Garam Gersik White 2022年降雨量数据的方法是box-Jenkins自回归综合移动平均(ARIMA)模型。Box-Jenkins自回归综合移动平均(ARIMA)是一种将过去的值作为因变量和自变量的时间序列预测方法。根据预测结果可知,格什克普提山鸡有9个干基,预计产量27360吨。盐厂Gersik Putih拥有456块结晶土地,总土地面积为126.36公顷。天气预报分析的结果可以确定盐的生产前、生产盐和生产后的时间。盐的预生产是一项准备和维护基础设施的活动,以最大限度地利用即将到来的旱季。盐的预生产在1月至5月进行。盐生产活动是在6月至11月初将海水加工成盐晶体。在干旱高峰期,在1块土地上结晶,一次收获可生产3-6吨。盐后生产是指由于降雨强度的增加,在11月至12月期间将盐从野鸡地运输到olo仓库的活动。应用的box-Jenkins综合移动平均(ARIMA)自回归模型的pearson系数相关水平为0.94%。皮尔逊系数的相关值表明,预测是非常好的、充分的和可行的。马杜拉岛的盐生产是使用太阳能蒸发器的方法进行的。盐的生产过程取决于降雨量。雨滴是制盐成功的关键。本研究的目的是找出降雨恢复的过程,以支持PT Sumenep白桃大蒜的盐生产过程。预测2022年PT White Peach Salt降雨量数据的方法是自回归综合移动平均(ARIMA)模型Boox-Jenkins。ARIMA Boox-Jenkins是使用自变量和因变量值的记录方法之一。根据预测可知,白桃种植有±9个干基,预计产量为27360吨。白桃农场有456块结晶地块,面积126.36公顷。天气分析的结果还可以确定盐生产前、盐生产和盐生产后的时间。盐前生产是一项准备和保持预测方式的活动,以最大限度地提高明年冬天的产量。盐的生产在1月至5月之间进行。盐生产活动是将海水加工成盐晶体,从6月持续到11月初。在薄雾的顶端,在一层结晶土地上一次可生产3-6吨。盐陷阱是11月至12月由于降雨强度的增加而发生的从农田到嗅觉的盐运输活动。自回归综合移动平均(ARIMA)模型Boox-Jenkins预计具有0.94%的pearson系数相关水平。皮尔逊系数的相关值值得用于记录方法。