scholarly journals Implementasi Graph Clustering Algorithm Modification Maximum Standard Deviation Reduction (MMSDR) dalam Clustering Provinsi di Indonesia Menurut Indikator Kesejahteraan Rakyat

Faktor Exacta ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 73
Author(s):  
Nurfidah Dwitiyanti ◽  
Septian Wulandari ◽  
Noni Selvia
Keyword(s):  
Economic Growth ◽  
Standard Deviation ◽  
Clustering Algorithm ◽  
Graph Clustering ◽  
Public Welfare ◽  
Poor People ◽  
Equitable Distribution ◽  
Maximum Standard Deviation ◽  
Central Statistics

<p>The population of Indonesia from year to year has increased. The increase in population must also be accompanied by increased economic growth in Indonesia. The increase in economic growth in Indonesia is marked by the reduction in the number of poor people in Indonesia. In addition, the increase in economic growth is reflected in the equitable distribution of public income in the country. Even though there are still many Indonesian people who are not yet prosperous in economic terms. To overcome, it is necessary to have clustering and characteristics of 34 provinces in Indonesia by implementing the Modification Maximum Standard Deviation Reduction (MMSDR) graph clustering algorithm. The data used are indicators of public welfare in 2017 obtained from the Central Statistics Agency. There are 9 indicators of community welfare used in this research. There are four stages in the MMSDR algorithm namely the "MST", "Subdivide", "Biggest Stepping" and "Create Clusters" processes. The results of this study can be seen from the distance between the nodes or between one province and another province produced 22 clusters. From the cluster results obtained using the MMSDR algorithm on welfare data, there are many clusters formed with cluster members formed at most two nodes (province).</p><p> Keywords: MMSDR, Clustering, Welfare of People</p>

Inclusive Growth with Zakat

2015 ◽  
Vol 54 (4I-II) ◽  
pp. 997-1010
Author(s):  
Muhammad Mazhar Iqbal
Keyword(s):  
Economic Growth ◽  
Aggregate Demand ◽  
Economic Consequences ◽  
Poor People ◽  
Kuznets Curve ◽  
Inclusive Growth ◽  
Marginal Productivity ◽  
The Social

Zakat is an annual religious levy that is collected from rich Muslims and its proceeds are disbursed among poor people of the society. It has many spiritual and social merits. For example, it purifies the hearts of zakat-givers as they give away a part of their wealth, one of the most precious things in their lives, seeking the pleasure of God without requiring any worldly gains whatsoever. It bridges the social gap between „haves‟ and „have-nots.‟ This study analyses, however, only economic consequences of Zakat for economic growth. They cannot be appreciated duly unless one understands the following concepts of modern economics; various theories of consumption, aggregate demand, stagnation thesis, consumption puzzle, marginal productivity of capital and Kuznets curve.

scholarly journals An Optimal and Stable Algorithm for Clustering Numerical Data

Algorithms ◽  
2021 ◽  
Vol 14 (7) ◽  
pp. 197
Author(s):  
Ali Seman ◽  
Azizian Mohd Sapawi
Keyword(s):  
Standard Deviation ◽  
Real World ◽  
Clustering Algorithm ◽  
Numerical Data ◽  
Zero Point ◽  
The Other ◽  
Suitable Alternative ◽  
Stable Algorithm ◽  
Real World Applications

In the conventional k-means framework, seeding is the first step toward optimization before the objects are clustered. In random seeding, two main issues arise: the clustering results may be less than optimal and different clustering results may be obtained for every run. In real-world applications, optimal and stable clustering is highly desirable. This report introduces a new clustering algorithm called the zero k-approximate modal haplotype (Zk-AMH) algorithm that uses a simple and novel seeding mechanism known as zero-point multidimensional spaces. The Zk-AMH provides cluster optimality and stability, therefore resolving the aforementioned issues. Notably, the Zk-AMH algorithm yielded identical mean scores to maximum, and minimum scores in 100 runs, producing zero standard deviation to show its stability. Additionally, when the Zk-AMH algorithm was applied to eight datasets, it achieved the highest mean scores for four datasets, produced an approximately equal score for one dataset, and yielded marginally lower scores for the other three datasets. With its optimality and stability, the Zk-AMH algorithm could be a suitable alternative for developing future clustering tools.

Efficient Vector Partitioning Algorithms for Graph Clustering

2020 ◽  
Vol 1 (2) ◽  
pp. 101-123
Author(s):  
Hiroaki Shiokawa ◽  
Yasunori Futamura
Keyword(s):  
Social Networks ◽  
Large Scale ◽  
Clustering Algorithm ◽  
Ground Truth ◽  
Graph Clustering ◽  
Mining Communities ◽  
Fine Grained ◽  
Efficient Vector ◽  
Public Datasets ◽  
Many Core

This paper addressed the problem of finding clusters included in graph-structured data such as Web graphs, social networks, and others. Graph clustering is one of the fundamental techniques for understanding structures present in the complex graphs such as Web pages, social networks, and others. In the Web and data mining communities, the modularity-based graph clustering algorithm is successfully used in many applications. However, it is difficult for the modularity-based methods to find fine-grained clusters hidden in large-scale graphs; the methods fail to reproduce the ground truth. In this paper, we present a novel modularity-based algorithm, \textit{CAV}, that shows better clustering results than the traditional algorithm. The proposed algorithm employs a cohesiveness-aware vector partitioning into the graph spectral analysis to improve the clustering accuracy. Additionally, this paper also presents a novel efficient algorithm \textit{P-CAV} for further improving the clustering speed of CAV; P-CAV is an extension of CAV that utilizes the thread-based parallelization on a many-core CPU. Our extensive experiments on synthetic and public datasets demonstrate the performance superiority of our approaches over the state-of-the-art approaches.

scholarly journals Foreign Direct Investment, Economic Freedom and Economic Growth: Evidence from Developing Countries

2016 ◽  
Vol 8 (11) ◽  
pp. 200 ◽  
Author(s):  
Md. Shakib Hossain
Keyword(s):  
Economic Growth ◽  
Developing Countries ◽  
Foreign Direct Investment ◽  
Standard Deviation ◽  
Poisson Regression ◽  
Direct Investment ◽  
Economic Freedom ◽  
Random Effect ◽  
Estimating Equation ◽  
Generalized Estimating Equation

<p class="Default">This paper has explores the interplay between economic freedom, foreign direct investment and economic growth using panel data analysis for a sample of 79 developing countries from 1998 to 2014 by considering the level of economic freedom, as provided by the “Heritage Foundation”. Panel unit root, pedroni residual co-integration test, generalized least square (GLS), feasible GLS (FGLS), pooled OLS, random effect, fixed effect, poisson regression, prais-winsten, generalized method of movement (GMM) and generalized estimating equation (GEE) methods have used to estimates the relationship. According to the OLS and generalized method of movement the coefficient implies that a one standard deviation improvement in business freedom, trade freedom, size, investment freedom, property rights, freedom from corruption, labor freedom, financial freedom, fiscal freedom, monetary freedom increases FDI by 21.4%, 15.6%, 21.6%, 17.5%, 11.55, 9.1%, 6.9%, 8.5%, 7.4%, 10.3% and 56.1%, 45.3%, 58.3%, 51.6%, 33.7%, 39.2%, 47.4%, 41.6%, 32.5%, 38.5% points respectively and  for the economic variable ,the coefficient implies that a one standard deviation improvement in GDPG and GDPPC increases FDI by 24.1%, 17.4% and 30.2%, 33.4% points respectively. By using the other method like random effect, fixed effect, poisson regression, prais-winsten and generalized estimating equation (GEE) method explores that economic freedom in the host country is a positive determinants of FDI inflows in developing countries and also the result suggests that foreign direct investment is positively correlated with the economic growth in the host countries.</p>

scholarly journals Pengaruh Investasi Dan Inflasi Terhadap Jumlah Penduduk Miskin di Kabupaten Jember Tahun 2000-2015

2019 ◽  
Vol 6 (1) ◽  
pp. 81
Author(s):  
Abdul Latif Hamzah ◽  
Anifatul Hanim ◽  
Herman Cahyo
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Secondary Data ◽  
Poor People ◽  
Poverty Level ◽  
Total Investment ◽  
Year 2000 ◽  
Very High

Conditions in Jember Regency from year to year economic growth is quite high, but the poverty level is very high as well. This study aims to determine the effect of investment and inflation on the number of poor people in the district of Jember in 2000- 2015. The method used in this research is multiple linear regression. The data used are secondary data formed in time series, the data used include investment, inflation in Jember district for 16 years in the year 2000-2015. Based on the results of the research, it can be seen that investment variables do not significantly affect the number of poor people in Jember, while Inflation has a significant effect on the number of poor people in Jember. Keywords: total investment, inflation, and poor people.

Sign in / Sign up

Export Citation Format

Share Document