On the Clustering of Islamic Rural Banks Based on Financial Performance

Nazar, Mumna; Maivastri,; Devianto, Dodi; Yozza, Hazmira

doi:10.1109/icaiti.2018.8686755

Cited by 11 publications

(11 citation statements)

References 8 publications

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“…This agglomerative algorithm is done with a bottom-up approach. The clustering procedure with the divisive method is the opposite of the agglomerative method [7].…”

Section: Plus Minus Products Made By a Countrymentioning

confidence: 99%

The Clustering of Southeast Asia Countries Based on Time Series Data of Total Trade

Afrimayani¹,

Ahmad²,

Yozza³

et al. 2019

The International Conference on ASEAN 2019

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ASEAN total trade is an instrument to provide a brief description of the development of trade in each ASEAN country. In order to realize a cohesive and integrated ASEAN economy through the free flow of goods trade in 2025.The hierarchical cluster method for times series data of total trade is used to grouping ASEAN countries into three groups with strong similarities and characteristics to the annual total trade in goods from 2008-2017 from the ASEAN Statistical Yearbook 2018. The cluster analysis by distance corresponding to time series data is performed. The first cluster consist of Brunei Darussalam, Indonesia, Singapore, Malaysia, and Thailand which had a high enough total trade among other ASEAN countries. The second cluster consists of the Philippines. Furthermore, the third cluster consists of Cambodia, Vietnam, Laos, and Myanmar. The second cluster has medium total trade and the third cluster has a fairly low total trade compared to other ASEAN countries. The performance total trade clustering in ASEAN countries is expected to be able to see the situation of the development of goods trade in ASEAN countries, this situation must be considered by ASEAN policies in increasing trade in goods.

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“…This agglomerative algorithm is done with a bottom-up approach. The clustering procedure with the divisive method is the opposite of the agglomerative method [7].…”

Section: Plus Minus Products Made By a Countrymentioning

confidence: 99%

The Clustering of Southeast Asia Countries Based on Time Series Data of Total Trade

Afrimayani¹,

Ahmad²,

Yozza³

et al. 2019

The International Conference on ASEAN 2019

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“…In financial case, to choose the optimal portfolio for stocks also can be modeled as explained in [2]. While the financial performance of Islamic Rural Banks can be applied by using clustering analysis as described in [3]. In other financial cases, time series of rainfall predicted by using Markov Autoregressive as in [4].…”

Section: Introductionmentioning

confidence: 99%

Hybrid Model of Seasonal ARIMA-ANN to Forecast Tourist Arrivals through Minangkabau International Airport

Yollanda¹,

Devianto²

2020

Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bog

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The number of tourist arrivals forecasting is required for the future development of tourism industry to improve the economic growth. The number tourist arrivals data can be analyzed by building a model so that it will help to find out the number of tourist arrivals in the next period which is through Minangkabau International Airport. The linear model that is used is Seasonal Autoregressive Integrated Moving Average (SARIMA) used and continued to build a nonlinear model of the residual SARIMA model using Artificial Neural Network (ANN). In this research, SARIMA model which obtained is SARIMA (1, 0, 1) (1, 1, 0) 12. But, residual of SARIMA model has not been fulfilled an autocorrelation assumption so that it isproposed a new model of SARIMA-ANN. The residual model of SARIMA is built using the ANN model architecture with 2-2-2-1 network topology. The performance rate of time series model of tourist arrivals which is the data started on January 2012 until March 2019 is measured using Mean Absolute Percentage Error (MAPE). Based on the MAPE value of 17.1770% indicates that the model obtained having good performance to forecast the number of tourist arrivals through Minangkabau International Airport in the future.

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“…Banks have an important role in the economy of a country, one of them as intermediary institutions which channeling public funds into investment asset productive that will boost the real sector productivity, capital accumulation, and aggregate growth. Moreover, the bank's main function is collecting funds from excessive sector and lending it to poor sectors [1] Banks are divided into two type based on it business scale of payment traffic, commercial banks and small business banks. The commercial banks carry out business activities in conventional and sharia principles which in their activities provide services in payment traffic, while small business banks do not provide services in payment traffic.…”

Section: Introductionmentioning

confidence: 99%

“…One type of small business bank is sharia small business bank. Sharia small business bank runs its business activities which do not provide services in payment traffic with sharia principle [1]. Sharia small business bank is an alternative for people who run small and medium businesses and want banks that apply Islamic principles, sharia and its traditions in financial transactions.…”

Section: Introductionmentioning

confidence: 99%

Determining Factors That Affecting Financial Performance of Sharia Small Business Bank by Using Ordinal Logistic Regression with Bootstrap Estimation

Ridho¹,

Devianto²

2020

Proceedings of the Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bog

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The aim of this study is to find out the financial performance's affecting factors of sharia small business bank in Indonesia. Financial performance is the response variable which grouped into three categories, they are bad, medium, and good. Predictor variables involved in this study consisted of 11 numerical data and 1 categorical data. The numerical data are financial capital, productive assets, credit, third party funds, income, capital adequacy ratio, return on assets, return on equity, financing deposit ratio, non performing financing, and operational efficiency. Whereas the categorical data is the location of sharia small business bank (1 if it is in rural areas, 2 if it is in the business center, and 3 if it is in a business and urban center). Ordinal logistic regression with a bootstrap estimation is performed to determine the predictor variable that affects the response variable. This study found that two predictor variables affected the response variable significantly, namely return on assets and return on equity with a hit ratio of 96.41%. So that it can be concluded that the model obtained has been able to determine the level of performance of sharia small business bank in Indonesia.

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On the Clustering of Islamic Rural Banks Based on Financial Performance

Cited by 11 publications

References 8 publications

The Clustering of Southeast Asia Countries Based on Time Series Data of Total Trade

The Clustering of Southeast Asia Countries Based on Time Series Data of Total Trade

Hybrid Model of Seasonal ARIMA-ANN to Forecast Tourist Arrivals through Minangkabau International Airport

Determining Factors That Affecting Financial Performance of Sharia Small Business Bank by Using Ordinal Logistic Regression with Bootstrap Estimation

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