1Departemen Ilmu Kelautan, Fakultas Pertanian, Universitas Trunojoyo Madura, Indonesia
2PT Garam Sumenep, Indonesia
BibTex Citation Data :
@article{JKT16139, author = {Tifani Noviasari and Nike Nuzula and Makhfud Efendy and Angga Febrianto and Ahmad Darmadi}, title = {Peramalan Curah Hujan Terhadap Produktivitas Garam Di Gersik Putih Sumenep}, journal = {Jurnal Kelautan Tropis}, volume = {26}, number = {1}, year = {2023}, keywords = {Cuaca; Produksi Garam; Kuantitas Produksi Garam; Pegaraman Gersik Putih}, 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 N ovember 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. }, issn = {2528-3111}, pages = {9--18} doi = {10.14710/jkt.v26i1.16139}, url = {https://ejournal2.undip.ac.id/index.php/jkt/article/view/16139} }
Refworks Citation Data :
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.
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