scholarly journals Peramalan Data Inflow dan Outflow Uang Kartal Bank Indonesia Provinsi DKI Jakarta Menggunakan Model ARIMAX dan SARIMAX

2021 ◽  
Vol 4 (2) ◽  
pp. 87
Author(s):  
Atika Amalia ◽  
Etik Zukhronah ◽  
Sri Subanti
Keyword(s):  
Time Series ◽  
Crucial Role ◽  
Forecasting Model ◽  
Gregorian Calendar ◽  
Monthly Data ◽  
Sample Data ◽  
The Difference

<p><strong>A</strong><strong>bstract</strong><strong>.</strong> DKI Jakarta Province plays a crucial role as the center of government and economy in Indonesia. The description of currency inflows and outflows is highly required before Bank Indonesia formulates the appropriate policies to control the circulation of money. The monthly data of currency inflow and outflow of Bank Indonesia of DKI Jakarta show a significant increase in each year particularly before, during, and after Eid al-Fitr. The determination of Eid al-Fitr does not follow the Gregorian calendar but based on the Islamic calendar. The difference in the use of the Gregorian and Islamic calendars in a time series causes a calendar variation. Thus, the determination of Eid al-Fitr in the Gregorian calendar changes as it goes forward eleven days each year or one month every three years. This study aims to obtain the best model and forecast currency inflows and outflows of Bank Indonesia DKI Jakarta using the ARIMAX and SARIMAX models. The study used in-sample data from January 2009 to December 2018 and out-sample data from January to October 2019. The best model was selected based on the smallest out-sample MAPE value. The result showed that the best forecasting model of inflow was ARIMAX (1,0,1). Meanwhile, the best forecasting model for outflow was SARIMAX (2,0,1)(0,0,1)<sup>12</sup>.</p><p><strong>Keywords: </strong>ARIMAX, calendar variation, forecasting, SARIMAX</p>

scholarly journals Peramalan Banyak Pengunjung Pantai Pandasimo Bantul Menggunakan Regresi Runtun Waktu dan Seasonal Autoregressive Integrated Moving Average Exogenous

2021 ◽  
Vol 4 (1) ◽  
pp. 57
Author(s):  
Tito Tatag Prakoso ◽  
Etik Zukhronah ◽  
Hasih Pratiwi
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Moving Average ◽  
Seasonal Pattern ◽  
Series Data ◽  
Gregorian Calendar ◽  
Time Series Regression ◽  
Autoregressive Integrated Moving Average ◽  
Past Data

<p>Forecasting is a ways to predict what will happen in the future based on the data in the past. Data on the number of visitors in Pandansimo beach are time series data. The pattern of the number of visitors in Pandansimo beach is influenced by holidays, so it looks like having a seasonal pattern. The majority of Indonesian citizens are Muslim who celebrate Eid Al-Fitr in every year. The determination of Eid Al-Fitr does not follow the Gregorian calendar, but based on the Lunar calendar. The variation of the calendar is about the determination of Eid Al-Fitr which usually changed in the Gregorian calendar, because in the Gregorian calendar, Eid Al-Fitr day will advance one month in every three years. Data that contain seasonal and calendar variations can be analyzed using time series regression and Seasonal Autoregressive Integrated Moving Average Exogenous  (SARIMAX) models. The aims of this study are to obtain a better model between time series regression and SARIMAX and to forecast the number of Pandansimo beach visitors using a better model. The result of this study indicates that the time series regression model is a better model. The forecasting from January to December 2018 in succession are 13255, 6674, 8643, 7639, 13255, 8713, 22635, 13255, 13255, 9590, 8549, 13255 visitors.</p><strong>Keywords: </strong>time series regression, seasonal, calendar variations, SARIMAX, forecasting

Dynamic Evaluation Model of Enterprise Informatization Level and its Application

2011 ◽  
Vol 201-203 ◽  
pp. 738-743
Author(s):  
Wu Yong Qian ◽  
Yao Guo Dang ◽  
Chen Yu Lin
Keyword(s):  
Time Series ◽  
Evaluation Model ◽  
Matrix Norm ◽  
Dynamic Evaluation ◽  
Enterprise Informatization ◽  
Evaluation Models ◽  
The Difference ◽  
Static Evaluation

The existing evaluation models of enterprise informatization level are mostly static evaluation model. And they can’t meet the need of dynamic evaluation of enterprise informatization level. According to the principle of priority information, this paper proposes a new method to determine time series weights based on matrix norm. By using the driving principle of the difference, this paper gives a determination of index weights. And based on time series weights and determination of index weights, the paper establishes a dynamic evaluation model of enterprise informatization level, and gives the calculation steps. Through the case study, this paper tests the validity of the model.

scholarly journals Model Variasi Kalender pada Regresi Runtun Waktu untuk Peramalan Jumlah Pengunjung Grojogan Sewu

2021 ◽  
Vol 4 (2) ◽  
pp. 67
Author(s):  
Etik Zukhronah ◽  
Winita Sulandari ◽  
Isnandar Slamet ◽  
Sugiyanto Sugiyanto ◽  
Irwan Susanto
Keyword(s):  
Time Series ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Mean Square ◽  
Gregorian Calendar ◽  
Time Series Regression ◽  
Sarima Model ◽  
Sarima Models

<p><strong>Abstract.</strong> Grojogan Sewu visitors experience a significant increase during school holidays, year-end holidays, and also Eid al-Fitr holidays. The determination of Eid Al-Fitr uses the Hijriyah calendar so that the occurrence of Eid al-Fitr will progress 10 days when viewed from the Gregorian calendar, this causes calendar variations. The objective of this paper is to apply a calendar variation model based on time series regression and SARIMA models for forecasting the number of visitors in Grojogan Sewu. The data are Grojogan Sewu visitors from January 2009 until December 2019. The results show that time series regression with calendar variation yields a better forecast compared to the SARIMA model. It can be seen from the value of  root mean square error (<em>RMSE</em>) out-sample of time series regression with calendar variation is less than of SARIMA model.</p><p><strong>Keywords: </strong>Calendar variation, time series regression, SARIMA, Grojogan Sewu</p>

scholarly journals The <sup>3</sup>He flux gauge in the Sargasso Sea: a determination of physical nutrient fluxes to the euphotic zone at the Bermuda Atlantic time series site

2015 ◽  
Vol 12 (5) ◽  
pp. 4183-4211
Author(s):  
R. H. R. Stanley ◽  
W. J. Jenkins ◽  
S. C. Doney ◽  
D. E. Lott,
Keyword(s):  
Time Series ◽  
Noble Gas ◽  
Euphotic Zone ◽  
Consistent Estimate ◽  
New Production ◽  
Net Community Production ◽  
Mode Water ◽  
Nitrate Flux ◽  
The Difference

Abstract. We provide a new determination of the annual mean physical supply of nitrate to the euphotic zone in the western subtropical North Atlantic based on a three year time-series of measurements of tritiugenic 3He from 2003 to 2006 in the surface ocean at the Bermuda Atlantic Time-series Study (BATS) site. We combine the 3He data with a sophisticated noble gas calibrated air–sea gas exchange model to constrain the 3He flux across the sea–air interface, which must closely balance the upward 3He flux into the euphotic zone. The product of the 3He flux and the observed subsurface nitrate-3He relationship provides an estimate of the minimum rate of new production in the BATS region. We also applied the gas model to an earlier time series of 3He measurements at BATS in order to recalculate new production fluxes for the 1985 to 1988 time period. The observations, despite an almost three-fold difference in the nitrate-3He relationship, yield a roughly consistent estimate of nitrate flux. In particular, the nitrate flux from 2003–2006 is estimated to be 0.65 ± 0.3 mol m-2 y-1, which is ~ 40% smaller than the calculated flux for the period from 1985 to 1988. The difference between the time periods, which is barely significant, may be due to a real difference in new production resulting from changes in subtropical mode water formation. Overall, the nitrate flux is larger than most estimates of export fluxes or net community production fluxes made locally for BATS site, which is likely a reflection of the larger spatial scale covered by the 3He technique and potentially also by decoupling of 3He and nitrate during obduction of water masses from the main thermocline into the upper ocean.

FRACTIONAL DETERMINATIONS OF URINARY 17-KETOSTEROIDS IN HYPEREMESIS GRAVIDARUM

1962 ◽  
Vol 41 (1) ◽  
pp. 123-128 ◽  
Author(s):  
Pentti A. Järvinen ◽  
Sykkö Pesonen ◽  
Pirkko Väänänen
Keyword(s):  
Hyperemesis Gravidarum ◽  
First Trimester ◽  
Control Group ◽  
Before And After ◽  
Daily Urine ◽  
First Trimester Of Pregnancy ◽  
The Difference

ABSTRACT The fractional determination of 17-ketosteroids in the daily urine was performed in nine cases of hyperemesis gravidarum and in four control cases, in the first trimester of pregnancy both before and after corticotrophin administration. The excretion of total 17-KS is similar in the two groups. Only in the hyperemesis group does the excretion of total 17-KS increase significantly after corticotrophin administration. The fractional determination reveals no difference between the two groups of patients with regard to the values of the fractions U (unidentified 17-KS), A (androsterone) and Rest (11-oxygenated 17-KS). The excretion of dehydroepiandrosterone is significantly higher in the hyperemesis group than in the control group. The excretion of androstanolone seems to be lower in the hyperemesis group than in the control group, but the difference is not statistically significant. The differences in the correlation between dehydroepiandrosterone and androstanolone in the two groups is significant. The high excretion of dehydroepiandrosterone and low excretion of androstanolone in cases of hyperemesis gravidarum is a sign of adrenal dysfunction.

EVALUASI PROYEKSI DEMAND BARANG DAN PENUMPANG PELABUHAN DI PROVINSI MALUKU

2019 ◽  
Vol 19 (2) ◽  
pp. 101-110
Author(s):  
Adrian Firdaus ◽  
M. Dwi Yoga Sutanto ◽  
Rajin Sihombing ◽  
M. Weldy Hermawan
Keyword(s):  
Time Series ◽  
Projection Method ◽  
Development Plan ◽  
Master Plan ◽  
Port Development ◽  
Loading And Unloading ◽  
The Difference ◽  
Existing Data

Abstract Every port in Indonesia must have a Port Master Plan that contains an integrated port development plan. This study discusses one important aspect in the preparation of the Port Master Plan, namely the projected movement of goods and passengers, which can be used as a reference in determining the need for facilities at each stage of port development. The case study was conducted at a port located in a district in Maluku Province and aims to evaluate the analysis of projected demand for goods and passengers occurring at the port. The projection method used is time series and econometric projection. The projection results are then compared with the existing data in 2018. The results of this study show that the econometric projection gives adequate results in predicting loading and unloading activities as well as the number of passenger arrival and departure in 2018. This is indicated by the difference in the percentage of projection results towards the existing data, which is smaller than 10%. Whereas for loading and unloading activities, time series projections with logarithmic trends give better results than econometric projections. Keywords: port, port master plan, port development, unloading activities  Abstrak Setiap pelabuhan di Indonesia harus memiliki sebuah Rencana Induk Pelabuhan yang memuat rencana pengem-bangan pelabuhan secara terpadu. Studi ini membahas salah satu aspek penting dalam penyusunan Rencana Induk Pelabuhan, yaitu proyeksi pergerakan barang dan penumpang, yang dapat dipakai sebagai acuan dalam penentuan kebutuhan fasilitas di setiap tahap pengembangan pelabuhan. Studi kasus dilakukan pada sebuah pelabuhan yang terletak di sebuah kabupaten di Provinsi Maluku dan bertujuan untuk melakukan evaluasi ter-hadap analisis proyeksi demand barang dan penumpang yang terjadi di pelabuhan tersebut. Metode proyeksi yang dipakai adalah proyeksi deret waktu dan ekonometrik. Hasil proyeksi selanjutnya dibandingkan dengan data eksisting tahun 2018. Hasil studi ini menunjukkan bahwa proyeksi ekonometrik memberikan hasil yang cukup baik dalam memprediksi aktivitas bongkar barang serta jumlah penumpang naik dan turun di tahun 2018. Hal ini diindikasikan dengan selisih persentase hasil proyeksi terhadap data eksisting yang lebih kecil dari 10%. Sedangkan untuk aktivitas muat barang, proyeksi deret waktu dengan tren logaritmik memberikan hasil yang lebih baik daripada proyeksi ekonometrik. Kata-kata kunci: pelabuhan, rencana induk pelabuhan, pengembangan pelauhan, aktivitas bongkar barang

THE SUBJECT FIELD OF INSTITUTIONAL EDUCATION: THE SENSE AND PROSPECTS OF DEVELOPMENT IN UKRAINE

2020 ◽  
pp. 25-38
Author(s):  
Irina Mordous
Keyword(s):  
Decisive Role ◽  
Subject Field ◽  
National Education ◽  
Progressive Development ◽  
Separate Area ◽  
Economic Transformations ◽  
The Difference ◽  
The Individual ◽  
Political Economic

The development of modern civilization attests to its decisive role in the progressive development of institutions. They identified the difference between Western civilization and the rest of the world. Confirmation of the institutional advantages of the West was its early industrialization. The genesis and formation of institutionalism in its ideological and conceptualmethodological orientation occurs as a process alternative to neoclassic in the context of world heterodoxia, which quickly spread in social science. Highlighting institutional education as a separate area of sociocultural activity is determined by the factor of differentiation of institutional theory as a whole. A feature of institutional education is its orientation toward the individual and his/her transformation into a personality. The content of institutional education is revealed through the analysis of the institution, which includes a set of established customs, traditions, ways of thinking, behavioral stereotypes of individuals and social groups. The dynamics of socio-political, economic transformations in Ukraine requires a review of the foundations of national education and determination of the prospects for its development in the 21st century in the context of institutionalism.

scholarly journals A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 455 ◽  
Author(s):  
Hongjun Guan ◽  
Zongli Dai ◽  
Shuang Guan ◽  
Aiwu Zhao
Keyword(s):  
Time Series ◽  
Information Entropy ◽  
Stock Exchange ◽  
Time Series Forecasting ◽  
High Order ◽  
Stock Index ◽  
Neutrosophic Set ◽  
Forecasting Model ◽  
Forecasting Models ◽  
Proposed Model

In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data. Then, the upward trend of each of fluctuation data is mapped to the truth-membership of a neutrosophic set, while a falsity-membership is used for the downward trend. Information entropy of high-order fluctuation time series is introduced to describe the inconsistency of historical fluctuations and is mapped to the indeterminacy-membership of the neutrosophic set. Finally, an existing similarity measurement method for the neutrosophic set is introduced to find similar states during the forecasting stage. Then, a weighted arithmetic averaging (WAA) aggregation operator is introduced to obtain the forecasting result according to the corresponding similarity. Compared to existing forecasting models, the neutrosophic forecasting model based on information entropy (NFM-IE) can represent both fluctuation trend and fluctuation consistency information. In order to test its performance, we used the proposed model to forecast some realistic time series, such as the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), the Shanghai Stock Exchange Composite Index (SHSECI), and the Hang Seng Index (HSI). The experimental results show that the proposed model can stably predict for different datasets. Simultaneously, comparing the prediction error to other approaches proves that the model has outstanding prediction accuracy and universality.

scholarly journals Load forecasting of refrigerated display cabinet based on CEEMD–IPSO–LSTM combined model

Open Physics ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 360-374
Author(s):  
Yuan Pei ◽  
Lei Zhenglin ◽  
Zeng Qinghui ◽  
Wu Yixiao ◽  
Lu Yanli ◽  
...  
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Data ◽  
Load Forecasting ◽  
Series Data ◽  
Forecasting Model ◽  
Combined Model ◽  
Forecasting Accuracy ◽  
Forecasting Method ◽  
Consumption Reduction

Abstract The load of the showcase is a nonlinear and unstable time series data, and the traditional forecasting method is not applicable. Deep learning algorithms are introduced to predict the load of the showcase. Based on the CEEMD–IPSO–LSTM combination algorithm, this paper builds a refrigerated display cabinet load forecasting model. Compared with the forecast results of other models, it finally proves that the CEEMD–IPSO–LSTM model has the highest load forecasting accuracy, and the model’s determination coefficient is 0.9105, which is obviously excellent. Compared with other models, the model constructed in this paper can predict the load of showcases, which can provide a reference for energy saving and consumption reduction of display cabinet.

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