scholarly journals Metode Dekomposisi Multiplikatif Rata-rata Bergerak Untuk Peramalan Tingkat Produksi Padi Ladang Sulawesi Tengah

2019 ◽  
Vol 8 (2) ◽  
Author(s):  
Faldi Christiawan Kadoena ◽  
Rais Rais ◽  
Lilies Handayani
Keyword(s):  
Decomposition Method ◽  
Moving Average ◽  
Seasonal Pattern ◽  
Rice Production ◽  
Multiplicative Decomposition ◽  
Random Components ◽  
Research Procedure ◽  
Central Sulawesi ◽  
Forecast Field ◽  
Tracking Signal

Field rice is a rice plants that is planted in a sedentary or shifting location. This study aims to forecast field rice production using the Multiplicative Decomposition method of moving average, and to determine the size of forecasting accuracy using Tracking signal, data used is the data from Central Sulawesi Province Field rice production in 2008-2016 obtained from the Agriculture Service of Central Sulawesi Province The research procedure is begun by analyzing the components of decomposition, namely the components of trend (T), seasonal (S), cyclic (C) and random components (I) then multiplies the value of these components. Forecasting results using the decomposition method helping by the Minitab 18 application in 2017 show that the pattern of the data contains a declining trend with the equation Yt = 1895.60 - 7.97 × t, and has a strong seasonal pattern with the expected pattern of data that increases or decreases in certain months such as March, April, August and December. The forecasting results obtained are at the control limit of Tracking signal which is between -4 to +4 that means the forecasting of rice production in the province of Central Sulawesi in 2017 using the moving average Multiplicative Decomposition method is valid

scholarly journals Optimizing Production Process through Production Planning and Inventory Management in Motorcycle Chains Manufacturer

2018 ◽  
Vol 9 (2) ◽  
pp. 43
Author(s):  
Shelvy Kurniawan ◽  
Steven Sanjaya Raphaeli
Keyword(s):  
Production Planning ◽  
Inventory Management ◽  
Decomposition Method ◽  
Moving Average ◽  
Order Quantity ◽  
Production Schedule ◽  
Multiplicative Decomposition ◽  
Additive Decomposition ◽  
Transportation Model ◽  
Total Cost

Based on the data, there were still shortages of production from year to year and demand wereunstable in motorcycle chains manufacturer in Indonesia. To overcome these problems, the purpose of this research was to make production planning and inventory control consisting of forecasting, aggregate planning, Master Production Schedule (MPS), and Material RequirementsPlanning (MRP). Forecasting used the additive decomposition method (average of all data), multiplicative decomposition (centered on moving average), and winter method (additive and multiplicative). Aggregate planning used chase strategy, level strategy, and transportation model. Moreover, MRP used lot for lot, Economic Order Quantity (EOQ), and Periodic Order Quantity (POQ) methods. The test shows several results. First, the best forecasting is additive decomposition (average of all data) with MAD value of 3.033,57, MSE with 13.590.490,and MAPE with 10,083%. Second, the best aggregate planning is transportation model with the total cost of Rp7.708.398.390,00. Last, the best MRP method is the lot for lot with total cost Rp7.162.567.653,00.

scholarly journals PERAMALAN PRODUK DOMESTIK BRUTO (PDB) SEKTOR PERTANIAN, KEHUTANAN, DAN ‎PERIKANAN MENGGUNAKAN SINGULAR SPECTRUM ANALYSIS (SSA)

2019 ◽  
Vol 8 (1) ◽  
pp. 68-80
Author(s):  
Desy Tresnowati Hardi ◽  
Diah Safitri ◽  
Agus Rusgiyono
Keyword(s):  
Gross Domestic Product ◽  
Spectrum Analysis ◽  
Time Series Data ◽  
Seasonal Pattern ◽  
Singular Spectrum Analysis ◽  
Domestic Product ◽  
Series Data ◽  
Percentage Error ◽  
Singular Spectrum ◽  
Tracking Signal

Forecasting is the process of estimating conditions in the future by testing conditions from the past. One of the forecasting methods is Singular Spectrum Analysis (SSA) which aim of SSA is to make a decomposition of the original series into the sum of a small number of independent and interpretable components such as a slowly varying trend, oscillatory components and a structureless noise. Gross Domestic Product data in the agriculture, forestry, and fisheries sector are time series data with trend and seasonal pattern so that it can be processed using the SSA method. The forecasting process of SSA method uses the main parameter (L) of 21 obtained by the Blind Source Separation (BSS) method. From forecasting, acquired group of 3 groups. Forecasting resulted the value of Mean Absolute Percentage Error (MAPE) is 1.59% and the value of tracking signal is 2.50, which indicates that the results of forecasting is accurate. Keywords: Forecasting, Gross Domestic Product in the agriculture, forestry, and fisheries sector, Singular Spectrum Analysis (SSA)

scholarly journals The Identification of Rice Varieties Used in Central Sulawesi

2021 ◽  
Vol 232 ◽  
pp. 03013
Author(s):  
Femmi Norfahmi ◽  
Komalawati Komalawati ◽  
Muh. Afif Juradi ◽  
Mardiana Mardiana ◽  
F.F. Munier
Keyword(s):  
Secondary Data ◽  
Rice Production ◽  
Rice Varieties ◽  
Local Varieties ◽  
Rice Productivity ◽  
Pests And Diseases ◽  
High Yielding Varieties ◽  
Central Sulawesi

Central Sulawesi’s rice productivity in 2019 was lower compared to that in 2018. One of the problems for the low productivity of paddy in Central Sulawesi is the application of low quality of seeds. Ministry of Agriculture through Central Sulawesi AIAT has introduced a numbers of new high yielding varieties (HYV) to increase rice production and productivity. To support the dissemination of new HYV, it is important to study the rice varieties that mostly used by farmers in Central Sulawesi. The objectives of this study are to identify the rice varieties and the preferred characteristics of rice varieties that farmers usually used in Central Sulawesi. This study used primary and secondary data. Data were analyzed descriptively and presented in tables and graphs. The results show that most farmers in Central Sulawesi use Mekongga, Ciherang, and Cisantana varieties, and local varieties such as Peluncur, Dewi, Ntabone and others. Farmers generally prefer varieties which tend to produce higher yields and resistant to pests and diseases. To maintain the availability of the varieties in Central Sulawesi, it is important to train farmers to become breeders.

scholarly journals Identifikasi dan Tingkat Penerapan Inovasi Teknologi Padi Sawah di Kabupaten Parigi Moutong Sulawesi Tengah

Jurnal Agro ◽  
10.15575/809 ◽  
2016 ◽  
Vol 3 (1) ◽  
pp. 25-35
Author(s):  
Syafruddin Syafruddin
Keyword(s):  
Technology Innovation ◽  
Field Research ◽  
Source Area ◽  
Buffer Zone ◽  
Research Field ◽  
Rice Production ◽  
Survey Method ◽  
Achievement Level ◽  
Technology Application ◽  
Central Sulawesi

Pencapaian tingkat swasembada dan ketahanan pangan khususnya beras tidak terlepas dari beberapa dukungan seperti sumberdaya alam dan penerapan inovasi teknologi. Kabupaten Parigi Moutong merupakan salah satu wilayah penghasil beras yang cukup besar di Sulawesi Tengah yang diharapkan dapat menjadi sumber pertumbuhan baru produksi beras Nasional di Indonesia. Pemerintah Daerah menetapkan wilayah ini, sebagai daerah penyangga beras terbesar di Sulawesi Tengah. Tujuan dari Penelitian ini adalah untuk : 1. Mengidentifikasi berbagai permasalahan dan tingkat penerapan inovasi teknologi pertanian di Kabupaten Parigi Moutong dan 2. Menetapkan arahan dan alternatif teknologi yang potensial untuk pengembangan lahan di Kabupaten Parigi Moutong. Penelitian ini dilaksanakan sebanyak dua tahap yaitu tahap 1 Desk study dan 2. Penelitian Lapangan. Desk study dilakukan dengan cara penelusuran pustaka dan diskusi dengan stake holders lainnya. Untuk Penelitian lapangan dilaksanakan dengan menggunakan metode survey dengan melakukan pengamatan kondisi sosial ekonomi dan budaya serta pengamatan tingkat penerapan inovasi teknologi melalui pendekatan Partisifatif Rural Aprasial atau Pengenalan Desa Secara Partisifatif (PRA). Pelaksanaan penelitian dilakukan selama 2 bulan yaitu dari bulan Juni hingga bulan Juli 2014. Hasil penelitian menunjukkan bahwa terdapat potensi perluasan areal persawahan dan peningkatan luas tanam karena didukung oleh iklim dan irigasi yang cukup baik. Tingkat penerapan teknologi masih cukup rendah terutama penggunaan varietas unggul, benih unggul dan bermutu serta pemupukan. The achievement level of self-sufficiency and food security, particularly in rice production should be supported by natural resources and the application of technology innovation.  Parigi Moutong Regency is one of the largest rice producer areas in Central Sulawesi, which is expected to be a new growth source area of national rice production in Indonesia. Local government has set this region as the largest rice buffer zone in Central Sulawesi. The aim of this study was to: 1) Identify the problems and the application level of agricultural technology innovation in Parigi Moutong Regency and 2) Setting the direction and potential of alternative technologies for the development of rice land area in the Regency of Parigi Moutong. This research had two steps, namely : 1) desk study and 2) field research. Field research method was done using a survey method of observing socio-economic and cultural conditions as well as the observation of the level of technology innovation through Participative Rural Appraisal (PRA) approach or partisipative village introduction. The research was conducted from June to July 2014. The result shows that there is a potential for expansion and improvement of rice cultivation acreage because it is supported by the suitable climate condition and well-managed irrigation facilities. However, the level of technology application is still relatively low, especially in the use of improved varieties, improved and quality seed and also proper fertilization.

scholarly journals Technical note: Decomposing a time series into independent trend, seasonal and random components

2018 ◽  
Author(s):  
Dongqin Yin ◽  
Hannah Slatford ◽  
Michael L. Roderick
Keyword(s):  
Time Series ◽  
Traditional Approach ◽  
Linear Trend ◽  
Moving Average ◽  
Climatic Variability ◽  
Original Data ◽  
Technical Note ◽  
Decomposition Approach ◽  
Random Components ◽  
Original Time

Abstract. Many time series observations in hydrology and climate show large seasonal variations and it has long been common practice to separate the original data into trend, seasonal and random components. We were interested in using that decomposition approach as a basis for understanding variability in hydro-climatic time series. For that purpose, it is desirable that the trend, seasonal and random components are independent so that the variance of the original time series equals the sum of the variances of the three components. We show that the resulting decomposition with the trend component traditionally estimated either as a linear trend or a moving average does not produce components that are independent. Instead we introduce the rarely adopted two-way ANOVA model into studies of hydro-climatic variability and define the trend as equal to the annual anomaly. This traditional approach produces a decomposition with three independent components. We then use global land precipitation data to demonstrate a simple application showing how this decomposition method can be used as a basis for comparing hydro-climatic variability. We anticipate that the three-part decomposition based on the two-way ANOVA approach will prove useful for future applications that seek to understand the space-time dimensions of hydro-climatic variability.

scholarly journals FORECASTING ARRIVAL OF FOREIGN TOURISTS USING SEASONAL ARIMA BOX-JENKINS

2021 ◽  
Vol 15 (2) ◽  
pp. 223-230
Author(s):  
Nur Ilmayasinta
Keyword(s):  
Moving Average ◽  
Seasonal Pattern ◽  
Secondary Data ◽  
Autoregressive Integrated Moving Average ◽  
Tourism Sector ◽  
Existing Data

Indonesia's economy is influenced by many factors, including the tourism sector. Through this tourism sector, it is possible for many foreign tourists to visit Indonesia. There are so many foreign tourists who come to Indonesia, forecasting is needed to find out the estimates of foreign tourists in the following months based on existing data. The method that used is the Seasonal Autoregressive Integrated Moving Average (SARIMA) method. The foreign tourist’s coming to Indonesia through Soekarno Hatta Airport were taken from the center agency on statistics (BPS) Indonesia. Data on the number of foreign tourists who come to Indonesia through Soekarno Hatta Airport is data with a seasonal pattern. The data used is secondary data obtained from Soekarno Hatta Airport for the period January 2010 to June 2015. In this case it is used to predict the value of the data for the next 6 months using the best model is the . Forecasting results show the number of each month increases from the previous year. In July it showed the highest yield of 342536, which was 297878 in the previous year. Forecasting results show the number of each month increases from the previous year. In July, the highest yield was 342536, which was 297878 in the previous year.

scholarly journals The effect of climate variables on the incidence of Crimean Congo Hemorrhagic Fever (CCHF) in Zahedan, Iran

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Sairan Nili ◽  
Narges Khanjani ◽  
Yunes Jahani ◽  
Bahram Bakhtiari
Keyword(s):  
Goodness Of Fit ◽  
Moving Average ◽  
Seasonal Pattern ◽  
Generalized Additive Models ◽  
Hemorrhagic Fever ◽  
Additive Models ◽  
Meteorological Variables ◽  
Fatality Rate ◽  
Crimean Congo Hemorrhagic Fever ◽  
Sarima Models

Abstract Background The Crimean-Congo Hemorrhagic fever (CCHF) is endemic in Iran and has a high fatality rate. The aim of this study was to investigate the association between CCHF incidence and meteorological variables in Zahedan district, which has a high incidence of this disease. Methods Data about meteorological variables and CCHF incidence was inquired from 2010 to 2017 for Zahedan district. The analysis was performed using univariate and multivariate Seasonal Autoregressive Integrated Moving Average (SARIMA) models and Generalized Additive Models (GAM) using R software. AIC, BIC and residual tests were used to test the goodness of fit of SARIMA models, and R2 was used to select the best model in GAM/GAMM. Results During the years under study, 190 confirmed cases of CCHF were identified in Zahedan district. The fatality rate of the disease was 8.42%. The disease trend followed a seasonal pattern. The results of multivariate SARIMA showed the (0,1,1) (0,1,1)12 model with maximum monthly temperature lagged 5 months, forecasted the disease better than other models. In the GAM, monthly average temperature lagged 5 months, and the monthly minimum of relative humidity and total monthly rainfall without lag, had a nonlinear relation with the incidence of CCHF. Conclusions Meteorological variables can affect CCHF occurrence.

scholarly journals Determining economic news about China in global news feed: Evidence from Global Database of Events, Language and Tone

2019 ◽  
Vol 4 (2) ◽  
pp. 272-285
Author(s):  
Yicheng Zhu
Keyword(s):  
International Economic ◽  
Moving Average ◽  
Seasonal Pattern ◽  
News Coverage ◽  
Chinese Economy ◽  
Stock Index ◽  
Global Database ◽  
Economic News ◽  
Moving Average Model ◽  
Model Versus

Current literature on economic news coverage mainly focuses on the economic news about domestic economy. This study asks a further question: will international economic news be accurately reflecting the economic performance of a foreign country? This study takes China as the target country and economic news coverage from other countries from the Global Database of Events, Language and Tone for this research and constructs a Poisson Lagged Regression model for news volume and compares autoregressive conditional heteroskedasticity model versus autoregressive integrated moving average model for economic news tone change. The results show that international economic news coverage is largely different from domestic news coverage, and the attention of foreign news on Chinese economy is negativity related to the performance of the Shanghai Stock Index. Moreover, the economic news tone about China’s economy showed a seasonal pattern.

scholarly journals Pengendalian Kualitas Produksi Dengan Metode Six Sigma Pada Industri UMKM Terhadap Jumlah Permintaan Kerudung

2020 ◽  
Vol 5 (1) ◽  
pp. 63
Author(s):  
SOFI NURRIYANTI YANTI ◽  
Mahasin Maulana Ahmad
Keyword(s):  
Six Sigma ◽  
Raw Materials ◽  
Moving Average ◽  
Exponential Smoothing ◽  
The Past ◽  
A Value ◽  
Forecasting Methods ◽  
Research Procedure ◽  
Using Data ◽  
Research Show

Forecasting is a method used to estimate a situation in the future by using data in the past. This study aims to analyze the supply of raw materials using forecasting methods, and determine the amount of demand, determine the causes of defects in production by providing suggestions for improvement in the process of making a veil. The steps of this research procedure are carried out several stages including moving average, exponential smoothing, define, measure, analyze, improve, control. The results of this research show that the defect of hood products is not neat stitching, the fabric used is wrinkled, there are holes in the fabric hood, ink is not suitable for printing, the environment is less conducive so workers are less focused when working. For the results of calculations from six sigma obtained Defect per Million Opportunity value obtained a value of 1916.33 and a sigma value of 4.391.ABSTRAK Peramalan adalah suatu metode yang dilakukan untuk memperkirakan suatu keadaan dimasa yang akan datang  dengan menggunakan data di masa lalu. Penelitian ini bertujuan untuk menganalisis persediaan bahan baku dengan menggunakan metode peramalan, serta menentukan jumlah permintaan kebutuhan, mengetahui penyebab terjadinya cacat pada produksi dengan memberikan usulan perbaikan pada proses pembuatan kerudung. Langkah prosedur penelitian ini dilakukan beberapa tahapan antara lain moving average, exponential smoothing, define, measure, analyze, improve, control. Hasil penelitian yang didapatkan jenis defect produk kerudung antara lain jahitan kurang rapi, kain yang digunakan kusut, terdapat lubang pada kain kerudung, tinta pada warna tidak sesuai saat cetak, lingkungan yang kurang kondusif sehingga pekerja kurang fokus saat bekerja. Untuk hasil dari perhitungan dari six sigma didapatkan nilai Defect per Million Opportunity diperoleh nilai sebesar 1916,33 dan nilai sigma sebesar 4,391.

Sign in / Sign up

Export Citation Format

Share Document