Improved-Node-Probability Method for Decision Making in Priority Determination of Village Development Proposed Program

This research proposes a new method, the probability of nodes (NP) and the cumulative frequency of indicators within the framework of Bayesian networks to calculate the weight of participation. This method uses the PLS-PM approach to examine the relationship structure of participatory factors and estimate latent variables. Data were collected using questionnaires involving participants offering proposals, the village residents themselves. The participation factors identified in this research were divided into two categories, namely, internal factors (abilities) and external factors (motivation). The internal factors included gender, age, education, occupation, and income, while the external factors included motivation relating to economic, political, socio-cultural, norm-related, and knowledge-related issues. Moreover, there are three factors directly affecting the level of participation, they are: the level of attendance in meetings, participation in giving suggestions, and involvement in decision making. The test results showed that the application of participation weight in decision making priority of proposal of village development program give change of final rank of decision with test result as: recall 50%, precision 80% and accuracy 50%.

@article{Trisnawarman2017,
  title     = {Improved-Node-Probability Method for Decision Making in Priority Determination of Village Development Proposed Program},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {11},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Dedi Trisnawarman and Sri Hartati and Edi Winarko and Purwo Santoso},
  doi       = {10.14569/IJACSA.2017.081108},
  url       = {https://doi.org/10.14569/IJACSA.2017.081108}
}