SIMULTANEOUS EQUATIONS MODELLING USING 2SLS AND 3SLS METHODS FOR FISHERMEN TERM OF TRADE OF INDONESIA

After being set as one of national target, Fishermen Term of Trade (NTN) has become a vital indicator for fisherman's welfare. For years, NTN is calculated based on the price of goods and services both in terms of production, costs and household consumption. While cost of consumption is based on actual data which was collected every month, the production refers to the volume of the base year, so it is less accurate in describing the actual condition. At the other side, dealing with State Budget planning, government needs to know how macroeconomic assumptions affect fisherman welfare. Therefore, the purpose of this study is to find a comprehensive model that simultaneously links the production side and economic indicator to predict NTN. Another focus is to investigate which estimation method is better, between Two Stage Least Squares (2SLS), as a single equation approach, and Three Stage Least Squares (3SLS), as a system approach. The study of Indonesian data from January 2008 – December 2012 shows that there are significant simultaneous relationships among production, macro assumption and NTN. The 3SLS gives better parameter estimates since it has less Mean Square Error (MSE) with R-sq=62.75%. But, in order to fit the NTN, the 2SLS gives a better prediction. Keywords: fishermen terms of trade, simultaneous model, 2SLS, 3SL

Evaluation of Fund Usage and KJMU Potential Recipients Modeling using Classification Tree and EasyEnsemble

(Kartu Jakarta Mahasiswa Unggul (KJMU) was one of Jakarta Provincial Government main program in education. This program aims to help students from poor family with excellent grades to continue higher education. This research was started by conducting survey to 354 recipient who entered college between 2016-2018 to see how they use KJMU funds. Even though they claim knowing how to manage their funds surprisingly education expenses come in fifth position out of 7 types of expenses and their incomes only covers 64.55% of their primary expenses. The main cause of these problems suspected because the candidates for KJMU recipients did not match the requirement. That is why this study continues by finding the right methods for classify the candidates. Since the recipient of KJMU is minority compares to majority people in Jakarta which born in 1997-2000 there is class imbalance issue in making classification model. If this issue not resolved well it will cause accuracy paradox where the prediction will tend toward majority class. This study compared CART (Classification Tree) and EasyEnsemble to find the most suitable model. Classification tree is known with its easy interpretation, high accuracy and fast but this method requires the balanced class that is why we add undersampling techniques into it. EasyEnsemble was designed for handling imbalanced class and it was combinations of UnderBagging and ADABoost. The results show that EasyEnsemble is the best method with the highest F1 score over 10, 50 dan 100 iteration modelling

Evaluation of Simultaneous and Simultaneous Spatial Autoregressive Equation with Three Stage Least Square Method (Case Study on GRDP, Poverty and Unemployment Data in Papua in 2018)

In the simultaneous equation (SM), the dependent variable in an equation could be an independent variable in another equation. Dependent variables are called endogenous variables and independent variables are called exogenous variables. If the observations in SM are locations and contain spatial autocorrelation, then a spatial dependency model can be added. Adding dependencies to endogenous variables is modeled as spatial autoregressive regression (SAR). Addition of SAR to the SM model hereinafter referred to as simultaneous spatial autoregressive regression (SM SAR). Estimation of parameters in the SM SAR can use the Three Stage Least Square (3SLS) method as used in SM. This study aims to predict this SM SAR model on GRDP, poverty and unemployment data in Papua in 2018. SM consists of three equations. The weight matrix used in each equation can be the same or a combination of inverse distance, rook contiguity, exponential weight and K-NN matrices. The results showed the addition of SAR in SM could reduce MSE by 0.31and an increase in R2 by 4.68% compared to the SM model

PEMODELAN PERSAMAAN STRUKTURAL DENGAN PARTIAL LEAST SQUARE

Pemodelan persamaan structural umumnya menggunakan Linear Structural Relationship, Metode pendugaan yang umumnya digunakan adalah metode Maksimum Likelihood. Pendugaan parameter dengan metode ML dalam LISREL membutuhkan berapa asumsi kritis seperti ukuran sampel minimal 10 kali banyaknya indikaor atau lebih dari 100 unit pengamatan, data menyebar mengikuti sebaran normal. LISREL menyediakan beberapa pendekatan yang dapat digunakan dalam pendugaan paremeter model, diantaranya dengan Bootstrap atau menggunakan metode Weighted Least Square. Namun, kedua pendekatan ini tetap membutuhkan data yang relative besar sehingga untuk model yang kompleks dengan ukuran sampel yang relative kecil dan data tidak menyebar normal dibutuhkan suatu pendekatan baru. Salah satu pendekatan baru yang diperkenalkan oleh Herman Wold, adalah Partial Least Square (PLS) dan sering disebut soft modeling. Dengan menggunakan PLS dimungkinkan melakukan pemodelan persamaan structural dengan ukuran sampel relative kecil dan tidak membuhkan asumsi normal multivariate. Kata Kunci: SEM, PL

SOCIAL ENTREPRENEUER IN ORGANIZATIONAL CULTURE AND ORGANIZATIONAL EFFECTIVENESS IN SUSTAINABILITY OF SEKOLAH PETERNAKAN RAKYAT NGUDI REJEKI KEDIRI

This study aimed to analyze the influence of social entrepreneurs, organizational culture, and organizational effectiveness for the sustainability of the Sekolah Peternakan Rakyat Ngudi Rejeki (SPR). The study population and sample were all members of the Sekolah Peternakan Rakyat Ngudi Rejeki, amounting to 31 SPR members. Interviews and questionnaires did the data collection, and the data was analyzed with the structural equation model - partial least square (SEM-PLS). The results showed that social entrepreneurs have a positive and significant effect on organizational culture, organizational effectiveness, and indirectly on organizational sustainability; organizational culture has a positive and significant effect on organizational effectiveness. Culture has not significantly or indirectly affected sustainability. Organizational effectiveness has not significant effect on organizational sustainability. Keywords: organizational culture, organizational effectiveness, organizational sustainability, Social entrepreneur, SP

PENDEKATAN METODE BAYES UNTUK PENDUGAAN PENGARUH INTERAKSI PADA MODEL AMMI

Multi-locations trials play an important role in plant breeding and agronomic research. Study concerning genotype-environment interaction needed in selection of genotype to be released. AMMI (Additive Main effect and Multiplicative Interaction) is one of statistical technique to analyze data from multi-locations trials. The analysis of AMMI is a combining analysis between additive main effect and principal component analysis. Multi-location sampling data which were collected several years on several planting season used to be analyzed separately. To obtain more comprehensive information of multi-location sampling data, an analysis which combines all the information in several years is needed. One of the alternatives is the Bayesian approach. This method utilizes initial information on the estimated parameters and information from samples. The simulation states that prediction with Bayesian methods will produce a better estimator, because MSE of the Bayesian estimator is smaller the MSE estimator generated using least squares method. Keywords: AMMI, Baye

A SIMULTANEOUS STUDY OF POVERTY RATE , CHILD LABOR AND DROPOUT RATE IN INDONESIA

Poverty is a major cause of child labor and dropout case. Poor families usually encourage their children to work looking for additional income as a way to survive. Based on previous research there is a causal relationship of poverty rate, number of child labor and dropout rate. Characteristics of poverty rate, child labor and dropout rate can be assessed from the demographic characteristics and socioeconomic characteristics are interrelated. This study aims to model the interdependent relationship of poverty rate, child labor and dropout rate in Indonesia and factors that influence them. One appropriate method is used to model the interdependent relationship of these three variables is the simultaneous equation models. From the results of the identification of the model equations were used the method Three Stage Least Square (3SLS) with 3 equations. The number of variables is 11 pieces consist of 3 endogenous variables and 8 predetermined variables. The result showed that child labor in Indonesia is influenced significantly by poverty rate, dropout rate, and percentage of household heads who worked in agriculture. Poverty rate in Indonesia is influenced significantly number of child labor, dropout rate, and percentage of household heads who worked in agriculture. While dropout rate is influenced significantly by number of child labor, percentage of household with members more than six, percentage of household heads who did not complete primary school and percentage of household head who completed basic education. R-square of system is about 66.28%, meaning that total diversity of poverty rate, number of child labor and dropout rate in Indonesia in 2013 which can be explained by the explanatory variables in the system about 66.28%. Keywords: 3 bhaSLS, simultaneous equation models, poverty, child labor, dropout

The Clustering of the Aquaculture Fisheries Companies in Indonesia Using the K-Prototypes and Two Step Cluster (TSC) Algorithm

Background: Fisheries subsector has an important role in the Indonesian economy, especially for the aquaculture fisheries companies. Each aquaculture fisheries companies has its own characteristics like in terms of technical, financial, staffing, or input and output structures. It is necessary to clustering 258 aquaculture fisheries companies to make it easier to identify the characteristics of these different companies based on the characteristics of their cluster. One of the method that can be used to grouping objects is cluster analysis. On this study, the clustering process was using the K-Prototypes and Two Step Cluster (TSC) algorithm because the data that used in this study was the mixed data type (13 numerical and 8 categorical variables). Then this study would choose the best algorithm by the smallest ratio between the standard deviation within the cluster (SW) and the standard deviation between cluster (SB). The smallest ratio means that the diversity within clusters is quite homogeneous, while the diversity between clusters is heterogeneous. Based on the comparison of the ratio between SW and SB from the k-prototypes and the TSC algorithm, the k-prototypes algorithm with 6 clusters was the best algorithm for clustering the aquaculture fisheries companies in Indonesia. The result showed that the cluster 5 was the best cluster and the cluster 6 was the worst cluster related to the condition of the aquaculture fisheries companies in Indonesia. Cluster 5 which is characterized by most of the central companies in the form of PT and do the enlargement of sea water fish in fishpond and has a high numerical variable value. Cluster 6 which is characterized by most of the central companies in the form of PT and CV and do the hatchery of land water fish in water tubs and has the lowest value compared to other clusters

SURVIVAL ANALYSIS OF CUSTOMER IN POSTPAID TELECOMMUNICATION INDUSTRY

Currently, the business competition in mobile telecommunication industry among providers in Indonesia is tighter and it has given rise to a phenomenon of customer defection which has serious consequences for the business performance. In the current circumstances, customers are faced numerous options to be selected that probably cause them at risk to get churn. Therefore, it becomes one of the challenges encountered by Division of Loyalty and Retention to makes the efforts of decreasing customer defection. So that it is important conducting a model of churn practically applied to predict tendency of customer churn and also recognizing the prognostic factors influence customer churn. Survival analysis modelling, such as Cox’s proportional hazard model, was very successful in previous research, which investigatedthe relationship between survival time and possible prognostic factors. Based on the research, Cox’s proportional hazard model of customer lifetime is effective to distinguish relative risk between churn customers and others, and also between which loyal customers and with other short time customers with their significant prognostic factors. Afterwards the simulation of the survival probability estimated over time with particular possible combination of the most significant characteristics affecting tendency of churn, are able to predict such information of lifetime to churn event and compare the survival performance of one another. Finally, the results of this research is able to yield simple, helpful and applicable results as the principle of taking decission for optimizing their customer retention and/or treatment resources in their customer retention efforts for the company.Key words : Churn, Cox’s proportional hazard model, customer retention, survival analysis and telecommunication industry

Gini Ratio Prediction by Estimating the Components Based on the Ybarra-Lohr Model Small Area Estimation with Estimated Sampling Variance

Gini ratio is one of the tools used to measure income inequality, so it is necessary to know the value of Gini ratio to a smaller regional level such as a subdistrict. According to Badan Pusat Statistik (BPS), the components of the Gini ratio are the average per capita expenditure and the relative frequency of households for each expenditure class in the subdistrict. Per capita expenditure data available through SUSENAS is designed to obtain national statistics down to the district level so that estimates are made for the level of subdistrict expenditure classes. Direct estimation for a small sample can cause significant standard errors therefore Small Area Estimation (SAE) with Logarithm Transformation is used to estimate the average per capita expenditure for each subdistrict expenditure class in Depok City 2020. The Ybarra-Lohr area-level model was used because of the availability of auxiliary data with measurement error. Previously, the sampling variance required for estimating the average per capita expenditure was estimated by comparing several estimation methods. As sampling variance estimation method, probability distribution produces an estimate of the average per capita expenditure with the smallest RRMSE, with a random effect variance and goodness of Ybarra-Lohr model are  = 0.686 and = 0.929. The best result of the average per capita expenditure estimation for each expenditure class is used to obtain Gini ratio for each subdistrict in Depok City 2020