scholarly journals ANALISIS EKONOMI RUMAHTANGGA PETANI SAYURAN DI KABUPATEN KAMPAR

2020 ◽  
Vol 21 (2) ◽  
pp. 113-125
Author(s):  
Yuliana Sari Dewi ◽  
Djaimi Bakce ◽  
Syaiful Hadi
Keyword(s):  
Least Square ◽  
Two Stage

Penelitian ini bertujuan untuk menganalisis ekonomi rumahtangga petani sayuran di Kabupaten Kampar. Penelitian ini menggunakan pendekatan ekonometrik dengan metode Two Stage Least Square (2SLS). Hasil penelitian menunjukkan: Pertama, produksi sayuran dipengaruhi secara responsif oleh total alokasi waktu kerja dalam usahatani. Kedua, alokasi waktu kerja dalam usahatani dan penggunaan tenaga kerja luar rumahtangga tidak responsif terhadap pendapatan dalam usahatani dan alokasi waktu kerja luar usahatani. Alokasi waktu kerja luar usahatani tidak responsif terhadap pendapatan dari luar usahatani, alokasi waktu kerja dalam usahatani, dan angkatan kerja petani. Ketiga, pendapatan rumahtangga di luar usahatani tidak responsif terhadap alokasi waktu kerja luar usahatani, pendidikan petani dan umur petani. Keempat, konsumsi pangan dan non pangan tidak responsif terhadap investasi pendidikan petani. Kelima, investasi pendidikan, investasi usahatani, pengeluaran leisure serta tabungan dipengaruhi secara responsif oleh pendapatan total rumahtangga. Keenam, simulasi peningkatan harga sayur dan penurunan harga pupuk berdampak positif terhadap rumahtangga petani sayuran, sedangkan peningkatan upah tenaga kerja berdampak negatif terhadap ekonomi rumahtangga petani sayuran. Terakhir, implikasi kebijakan yang dapat diambil pemerintah dalam rangka meningkatkan ekonomi rumahtangga petani sayuran di Kabupaten Kampar adalah dengan melakukan pembinaan terhadap petani sayuran di Kabupaten Kampar sehingga mutu dan produktivitas sayuran yang dihasilkan mengalami peningkatan serta menetapkan harga pupuk yang bersaing dan stabil.

scholarly journals A Compound Wind Power Forecasting Strategy Based on Clustering, Two-Stage Decomposition, Parameter Optimization, and Optimal Combination of Multiple Machine Learning Approaches

Energies ◽  
2019 ◽  
Vol 12 (18) ◽  
pp. 3586 ◽  
Author(s):  
Sizhou Sun ◽  
Jingqi Fu ◽  
Ang Li
Keyword(s):  
Wind Power ◽  
Large Scale ◽  
Wind Farm ◽  
Search Algorithm ◽  
Interpolation Method ◽  
Least Square ◽  
Support Vector ◽  
Two Stage ◽  
Wind Power Forecasting ◽  
Power Forecasting

Given the large-scale exploitation and utilization of wind power, the problems caused by the high stochastic and random characteristics of wind speed make researchers develop more reliable and precise wind power forecasting (WPF) models. To obtain better predicting accuracy, this study proposes a novel compound WPF strategy by optimal integration of four base forecasting engines. In the forecasting process, density-based spatial clustering of applications with noise (DBSCAN) is firstly employed to identify meaningful information and discard the abnormal wind power data. To eliminate the adverse influence of the missing data on the forecasting accuracy, Lagrange interpolation method is developed to get the corrected values of the missing points. Then, the two-stage decomposition (TSD) method including ensemble empirical mode decomposition (EEMD) and wavelet transform (WT) is utilized to preprocess the wind power data. In the decomposition process, the empirical wind power data are disassembled into different intrinsic mode functions (IMFs) and one residual (Res) by EEMD, and the highest frequent time series IMF1 is further broken into different components by WT. After determination of the input matrix by a partial autocorrelation function (PACF) and normalization into [0, 1], these decomposed components are used as the input variables of all the base forecasting engines, including least square support vector machine (LSSVM), wavelet neural networks (WNN), extreme learning machine (ELM) and autoregressive integrated moving average (ARIMA), to make the multistep WPF. To avoid local optima and improve the forecasting performance, the parameters in LSSVM, ELM, and WNN are tuned by backtracking search algorithm (BSA). On this basis, BSA algorithm is also employed to optimize the weighted coefficients of the individual forecasting results that produced by the four base forecasting engines to generate an ensemble of the forecasts. In the end, case studies for a certain wind farm in China are carried out to assess the proposed forecasting strategy.

scholarly journals ANALISIS PERMINTAAN DAN PENAWARAN UANG DI INDONESIA

2019 ◽  
Vol 5 (1) ◽  
pp. 1-8
Author(s):  
Arwin Arwin ◽  
Said Muhammad ◽  
Raja Masbar
Keyword(s):  
Interest Rate ◽  
Money Supply ◽  
World Bank ◽  
Money Demand ◽  
National Income ◽  
Secondary Data ◽  
Real Income ◽  
Least Square ◽  
Two Stage ◽  
Data Processing Method

This study aims to determine the determinants of the money demand and money supply function in Indonesia. To formulate the equation between money demand (Md) and money supply (Ms) using LM function by looking at the effect of real income and interest rate. The data in this study constitutes Indonesia's economic data from 1986 to 2015 drawn from secondary data sources such as Bank Indonesia (BI), Central Bureau of Statistics (BPS), International Financial Statistics (IFS), International Monetary Funds (IMF) and World Bank . The Data Processing method used is to use the equations and completed with Two Stage Least Square. The results showed that the balance occurred at the national income level of 277559.05 billion Rupiah with an interest rate of 7.05%. Keywords: Demand and Supply of Money, Gross Domestic Product, Interest Rate, Inflation, and Exchange Rate. Abstrak Penelitian ini bertujuan untuk megetahui determinan dari fungsi permintaan uang dan penawaran uang di Indonesia. Untuk merumuskan persamaan antara permintaan uang (Md) dengan penawaran uang (Ms) menggunakan fungsi LM dengan melihat pengaruh pendapatan riil dan tingkat suku bunga. Data dalam penelitian ini merupakan data perekonomian Indonesia dari tahun 1986 – 2015 yang diambilkan dari sumber data sekunder baik seperti Bank Indonesia(BI), Badan Pusat Statistik (BPS), Internasional Financial Statistics (IFS), International Monetary Funds ( IMF) dan World Bank. Metode Pengolahan datayang digunakan adalah menggunakan persamaan simultan dan diselesaikan dengan Two Stage Least Square. Hasil penelitian menunjukkan bahwa keseimbangan terjadi pada tingkat pendapatan nasional sebesar 277559.05 milyar Rupiah dengan tingkat bunga sebesar 7,05%. 

scholarly journals KETERKAITAN MANAGERIAL OWNERSHIP DAN LEVERAGE TERHADAP NILAI PERUSAHAAN: DALAM KONTEK HUBUNGAN KEAGENAN PERUSAHAAN DI INDONESIA

2021 ◽  
Vol 5 (1) ◽  
pp. 160
Author(s):  
Margarita Ekadjaja ◽  
Rorlen Rorlen ◽  
Fanny Andriani Setiawan ◽  
Kartika Nuringsih
Keyword(s):  
Decision Making ◽  
Firm Value ◽  
Agency Costs ◽  
Least Square ◽  
Managerial Ownership ◽  
Corporate Value ◽  
Manufacturing Companies ◽  
Positive Interaction ◽  
Two Stage ◽  
The Relationship

Manajemen dan nilai perusahaan memiliki keterkaitan yang tidak dapat dipisahkan.  Dimana manajemen perusahaan merupakan penggerak roda perusahaan dan berorientasi pada nilai perusahaan. Peran seorang manajer adalah memaksimalkan kekayaan bagi pemegang saham.  Namun, manajer yang tidak memiliki kepemilikan saham yang signifikan di perusahaan dapat memilih untuk memaksimalkan keuntungan bersih mereka sendiri dengan mengorbankan pemilik perusahaan. Akibatnya, pemilik terpaksa mengeluarkan biaya agensi untuk memastikan bahwa manajemen perusahaan bertindak dengan cara yang tepat. Cara untuk mengurangi biaya agensi adalah memaksa perusahaan untuk meningkatkan hutang. Tujuan penelitian adalah  menguji hubungan simultan pertukaran antara ownership, leverage, dan nilai perusahaan sehubungan dengan keagenan pada perusahaan manufaktur di Indonesia dari tahun 2012-2018. Penelitian ini menambah pemahaman mengenai keterkaitan antara ownership dengan leverage, dan nilai perusahaan. Analisis data untuk argumen tentang keterkaitan simultan antara  ownership, leverage, dan nilai perusahaan melalui data panel regresi berganda 2 SLS (Two Stage Least Square). Bidang penelitian ini diperluas dengan mempertimbangkan model empiris di mana ownership dan leverage masing-masing diperlakukan sebagai variabel endogen atau ditentukan bersama.  Dalam metode 2 SLS ada 2 kali variabel yang diobservasi secara simultan untuk menghindari bayes sehingga variabel tersebut tidak bias, di mana variabel managerial ownership dan Leverage merupakan determinan non linier nilai perusahaan sebagai bagian integral dari pengambilan keputusan perusahaan dalam kerangka keagenan.  Persamaan Regresi hasil uji 2SLS memunjukkan keterkaitan nilai perusahaan dengan managerial ownership dan leverage. Hasil menunjukkan interaksi positif  tidak signifikan antara managerial ownerhip dengan nilai perusahaan, interaksi positif signifikan antara nilai perusahaan dengan leverage, dan interaksi yang negatif signifkan antara managerial ownership dengan leverage. Management and corporate value have an inseparable relationship. Where the company management is the driving force of the company and oriented to corporate values. The role of a manager is to maximize wealth of shareholders. However, managers who do not have a significant share in the company may choose to maximize their own net profits at the expense of the company owners. As a result, the owners are forced to incur agency costs to ensure that company management acts in an appropriate manner. The way to reduce agency costs is to force the company to increase debt. The research objective is to examine the exchange simultaneous relationship between ownership, leverage, and corporate value with respect to agency in manufacturing companies in Indonesia from 2012-2018. This study adds to the understanding of the relationship between ownership and leverage, and corporate value. Data analysis for arguments about the simultaneous relationship between ownership, leverage, and firm value through 2 SLS (Two Stage Least Square) multiple regression panel data. This field of research is extended by considering empirical models in which ownership and leverage are treated as endogenous or co-determined variables, respectively. Ownership and Leverage as an integral part of corporate decision making within an agency framework, which in turn will affect the value of the company. In the SLS 2 method, there are 2 variables that are observed simultaneously to avoid bayes so that the variable is not biased, in which the managerial ownership and leverage variables are nonlinear determinant corporate value as an integral part of corporate decision making within the agency framework, which in turn will affect firm value. The 2SLS regression equation results show the relationship between firm value and managerial ownership and leverage. The results prove that there is a positive interaction between managerial ownership between firm value, a significant positive interaction between firm value and leverage, and a significant negative interaction between managerial ownership and leverage.

ANALISIS PENGARUH TRANSACTION COST TERHADAP HOLDING PERIOD SAHAM BIASA.

2008 ◽  
Vol 4 (2) ◽  
pp. 116
Author(s):  
Eko Budi Santoso
Keyword(s):  
Statistical Method ◽  
Transaction Cost ◽  
Time Horizon ◽  
Market Value ◽  
Least Square ◽  
Common Stock ◽  
Two Stage ◽  
Holding Period ◽  
Bid Ask Spread

The moin pwpose of this sndy is to test the effect of transaction cost totntdins period of common stock This srudy iwestigates whether investorswith longer (shorter) hwestment time horizon lold common stockswith higher (owe) bid-qsk spred as a prory of tronsaction cost. Besides,thk study also added two independent voiables such as marketvalue and variance ofrefirn-The statistical method ued in this study is two-stage least square regressionsbecause the itnestorb tnlding period md the bid-ask spreadfor each stoch are simultoteously determined. The result shows that bidask spred related positivefu ord significott to holding period. The bidask spread, morket yalue, and varianee of return have a significant Kqruords: Trqtsaction Cost, Bid-Ask Spread, Holding Period, Market Value, Variance of Return

Identification of continuous-time hybrid “Box–Jenkins” systems with multiple unknown time delays using two-stage parameter estimation algorithm

2019 ◽  
Vol 36 (6) ◽  
pp. 2111-2130
Author(s):  
Yamna Ghoul
Keyword(s):  
Continuous Time ◽  
Time Delays ◽  
Least Square ◽  
Identification Algorithm ◽  
Recursive Least Square ◽  
Two Stage ◽  
Content Type ◽  
Single Output ◽  
Multiple Input ◽  
Unknown Time Delays

Purpose This study/paper aims to present a separable identification algorithm for a multiple input single output (MISO) continuous time (CT) hybrid “Box–Jenkins”. Design/methodology/approach This paper proposes an optimal method for the identification of MISO CT hybrid “Box–Jenkins” systems with unknown time delays by using the two-stage recursive least-square (TS-RLS) identification algorithm. Findings The effectiveness of the proposed scheme is shown with application to a simulation example. Originality/value A two-stage recursive least-square identification method is developed for multiple input single output continuous time hybrid “Box–Jenkins” system with multiple unknown time delays from sampled data. The proposed technique allows the division of the global CT hybrid “Box–Jenkins” system into two fictitious subsystems: the first one contains the parameters of the system model, including the multiple unknown time delays, and the second contains the parameters of the noise model. Then the TS-RLS identification algorithm can be applied easily to estimate all the parameters of the studied system.

scholarly journals Tax Morale and Compliance Behavior: First Evidence on a Causal Link

2012 ◽  
Vol 12 (1) ◽  
Author(s):  
Martin Halla
Keyword(s):  
Tax Evasion ◽  
Recent Literature ◽  
Causal Effect ◽  
Causal Link ◽  
Least Square ◽  
Least Square Estimation ◽  
Two Stage ◽  
Tax Morale ◽  
Actual Compliance ◽  
Compliance Behavior

Abstract Recent literature on tax evasion emphasizes the importance of moral considerations to explain compliance behavior. As a consequence scholars aim to identify factors that shape this so-called tax morale. However, the causal link between tax morale and actual compliance behavior is not established yet. Exploiting exogenous variation in tax morale – given by the inherited part of tax morale of American-born from their ancestors country of origin – our Two-Stage Least Square Estimation provides first evidence on a causal effect of tax morale on the size of the underground production.

Calculation of Speed Ratio of Two-Stage Helical Gear Reducer for Minimum Mass

2013 ◽  
Vol 274 ◽  
pp. 149-152
Author(s):  
Cheng Yi Pan
Keyword(s):  
Least Square Method ◽  
Helical Gear ◽  
Least Square ◽  
Speed Ratio ◽  
Minimum Mass ◽  
Contact Strength ◽  
Strength Condition ◽  
Total Speed ◽  
Two Stage ◽  
Optimum Speed

This paper analyses distribution of the total speed ratio of two-stage helical gear reducer. On the minimum mass and contact strength condition , the optimum speed ratio equation is derived. By means of the least square method, the fitting formula of calculating optimum speed ratio on minimum mass candition is obtained. Using this formula, the optimum speed ratio of two-stage helical gear reducer having minimum mass can be found quickly and accurately.

scholarly journals Partial Least Square Discriminant Analysis Based on Normalized Two-Stage Vegetation Indices for Mapping Damage from Rice Diseases Using PlanetScope Datasets

Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1901 ◽  
Author(s):  
Yue Shi ◽  
Wenjiang Huang ◽  
Huichun Ye ◽  
Chao Ruan ◽  
Naichen Xing ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Vegetation Indices ◽  
Partial Least Square ◽  
Least Square ◽  
Two Stage
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