The Government program in tackling the economic crisis that has occurred so far is by providing direct assistance to very poor families (KSM) in every village throughout Indonesia. The Family Hope Program (PKH) is one of the government's conditional aid programs as a form of compensation from the fuel price increase, which certainly affects the lives of the wider community, including the poor. In order for the expected results to be more accurate and the system designed is arranged systematically, the authors decided to use Analytical Hierarcy Process (AHP). This decision support model will describe the problem of multi-factor or multi-criteria into a form of hierarchy, From the results of the test the shrill and weight of PKH assistance is the type of work of the head of the family is not fixed in the first rank with 4.9 shrill. With the results of the output is feasible or not prospective recipient in PKH, obtained from the comparison of the lamda weight of the rating category with the weight value of the predetermined ratio.
In: Journal of risk research: the official journal of the Society for Risk Analysis Europe and the Society for Risk Analysis Japan, Band 17, Heft 3, S. 337-352
In: Proceedings of the 17th International Multidisciplinary Scientific Geoconference (Vol. 17, Issue 23, pp.377-384) on Informatics, Geoinformatics and Remote Sensing, DOI: 10.5593/sgem2017/23/S11.046
A comparative study of perceptions concerning the environmental quality of residential real estate in Switzerland based on empirical data collected in three different linguistic regions is presented. Responses by homeowners in the Geneva, Zurich and Lugano areas to questionnaires involving pairwise preference criteria are analysed in the framework of the analytic hierarchy process (AHP). Eight different environmental quality criteria are used and responses are categorised in terms of indicators concerning the personal situation of the homeowner. The results show that environmental preference levels across the three cities are in the 7‐18 per cent range. It appears that perceptions are similar for four of the eight criteria, whereas notable differences exist for the other criteria. Some possible interpretations of these results are given. Finally, possible extensions to this study are discussed, in particular how the approach could be integrated in a more detailed spatial analysis of socio‐economic data in the framework of geographic information systems.
In: Proceedings of International Conference on Sustainable Computing in Science, Technology and Management (SUSCOM), Amity University Rajasthan, Jaipur - India, February 26-28, 2019
This study aims to describe the management of the allocation of village funds in physical development in the village of Siborna, Panei Subdistrict, Simalungun Regency and to identify inhibiting factors and supporting factors in managing village fund allocation. The focus of this research is the management of village fund allocations which include: planning, implementation. The determination of the allocation of village funds will later use the Analytical Hierarchy Process (AHP) method with 4 criteria including: villagers, rural poor, village area and Village Geographical Difficulty Index. Alternative Samples in this study were 4 villages, including the villages of Sosor Hamlet, Simpang Bahbirong Hamlet, Hutabagasan Hamlet and Kebun Sayur Hamlet. The results of this study using the AHP method obtained by the Village of Vegetable Farm Village is an alternative with the highest value that is eligible to get a village fund allocation from the government with a value of 3,0000
Purpose Despite being a low-tech industry, woodwork manufacturing industry that includes furniture and cabinet making, witnessed technological leaps in production technologies due to technical developments in computer numerical control (CNC) machining processes. The managers of this industry have attached high importance to the selection of efficient machines as their decisions directly affect the quality and performance of products produced by the firms. Improper selection process can result in a significant decrease in productivity and flexibility. Therefore, a systematic decision-making procedure is needed to prevent inaccurate investments on machines. The purpose of this paper is to purpose a hesitant fuzzy analytic hierarchy process (HFAHP) based multi-criteria decision making (MCDM) system for CNC router selection in small- and medium-sized enterprises (SMEs) in woodwork manufacturing.
Design/methodology/approach The study proposes a hierarchical model consisting of 4 main criteria and 11sub-criteria for woodwork manufacturing. Technical, personnel, economic and vendor aspects constitute the main criteria. Because of the hierarchical structure of the model, HFAHP is utilized to define the importance weights of the criteria, and to select the most appropriate CNC alternative for a manufacturing company under focus. In a selection procedure, the judgments of decision makers may have vagueness to specify the importance of criteria affecting the decision process. In the literature, the fuzzy set theory has been utilized to deal with such uncertainties. However, when the ideas of the managers have high potential to fall into contradiction in pairwise comparisons, a novel approach is needed to overcome the obstacles. HFAHP allows the membership degree having a set of possible values. It is specifically useful in compromised decisions where experts cannot agree on a single value and prefer to come up with an interval of linguistic variables.
Findings It is revealed that for SMEs in woodwork manufacturing, the most important criterion in selecting the CNC routers is the technical aspects. It may seem counter intuitive that they do not refrain finding the technical criteria superior to the economic aspects, even though they have limited budgets compared to large-scale firms. This demonstrates that in current competitive environment, SMEs understand the need for high-quality production strategy. The weights of the remaining two criteria (personnel and vendor aspects) are relatively low because they expect that they can easily overcome the problem of adapting the workers by training, and all vendors have quality standard qualifications so they can offer a satisfactory service and supplementary systems.
Practical implications The ready-to-use model proposed is specialized for SMEs in woodwork manufacturing. However, to make it an easily adaptable model for every company in the woodwork industry regardless of its size, the calculation process of the priority weights is illustrated in detail with a numerical example. Any company can follow the process using their own preferences to end up with a specific model that will perfectly reflect their own specific priorities. For demonstrating the application of the model, a case study is conducted in a woodwork manufacturing SME to select the best CNC router among three alternatives.
Originality/value The originality and value of the paper is twofold. First, to the best of our knowledge, this is the first study that proposes a woodworking-specific CNC router selection for SMEs. Second, to handle the high uncertainty in the judgements, and to facilitate consensus among the experts during face to face meetings to develop compromised matrices, a very recently developed method, HFAHP is used.
In order to sustain or improve a position, higher education institutions have to realize that service quality is a critical condition for survival and growth in the education market. Therefore, the purpose of the research presented in this paper is to emphasize quality as a source of competitive advantage of higher education institutions, as well as to identify opportunities for improving service quality. The main objective of the research is to evaluate whether service quality determines students' satisfaction. The data provided by empirical research, conducted at universities in Serbia, have been subject to model that is usually used for service quality assessment and evaluation (SERVQUAL model). This model is valuable, but certainly not sufficient for creating an improvement map. Therefore, for identification of improvement priorities, in addition to SERVQUAL model, AHP method, pared t-test, ANOVA and regression analysis have been used. The results of the analysis indicate a gap between service quality that students expect and perceive. In addition, based on quantitative analysis, priorities for improvement of service quality are identified.
The sustainable management of river basins is a comprehensive problem involving not only environmental quality but also socio-economic aspects. The primary objective of the study is to propose a sustainable management model of a river basin based on a clear identification of the good water quality in the river basin applicable for any river basin. The proposal is based on a monitoring of the quality of surface water in the basin, a quantitative and qualitative analysis of pollution, a questionnaire survey on the sewer systems and wastewater treatment in the basin and the diffuse sources of water pollution. For a better outline, a case study of Hornád river basin, Slovakia, was carried out. Two methodologies were applied: SWOT analysis for identification of indicators and the priorities and AHP analysis for a prioritization of the decisions. These analyses can be carried out for any activity based on identification of indicators and the priorities of the defined indicators to promote sustainable development. Based on the findings and the results of the analyses the model for managing the development of surface water quality in the basin was proposed. Generally applicable principles of sustainable development, accepting legislation in the field of water management, considering the quality of surface water in the basin, the impacts of wastewater discharges into the recipient, the identification and evaluation of positive and negative aspects of surface water quality, and the implementation of the proposed measures and post-implementation monitoring of qualitative development were covered in and by the proposed model.