GIS-based landslide susceptibility mapping using analytic hierarchy process and artificial neural network in Jeju (Korea)

Groundwater resources are essential for drinking water, irrigation, and the economy mainly in semiarid environments where rainfall is limited. Currently, unpredictable rainfall due to climate change and pollution on the Earth’s surface directly affects groundwater resources. In this area, most people depend on groundwater resources for irrigation and drinking purposes, and every summer, most of the area depends on groundwater in a semiarid environment. Hence, we selected two popular methods, the analytical hierarchy process (AHP) and multiple influence factor (MIF) methods, which can be applied to map groundwater potential zones. Nine thematic layers, such as land use and land cover (LULC), geomorphology, soil, drainage density, slope, lineament density, elevation, groundwater level, and geology maps, were selected for this study using remote sensing and geographic information system (GIS) techniques. These layers are integrated in ArcGIS 10.5 software with the help of the AHP and MIF methods. The map of the groundwater potential zones in the study area revealed four classes, i.e., poor, moderate, good, and very good, based on the AHP and MF methods. The groundwater potential zone area is 241.50 (ha) Poor, 285.64 (ha) moderate, 408.31 (ha) good, and 92.75 (ha) very good using the AHP method. Similarly, the MIF method revealed that the groundwater potential classes were divided into four classes: 351.29 (ha) poor, 511.18 (ha), moderate, 123.95 (ha) good, and 41.78 (ha) very good. The results were compared to determine which methods are best for planning water and land resource development in specific areas that have basaltic rock and drought conditions. Both groundwater potential zone maps were validated with water yield data. The receiver operating characteristic (ROC) curve and area under the curve (AUC) model results are found to be 0.80 (good) and 0.93 (excellent) using the MIF and AHP methods, respectively; hence, the AHP method is best for delineation of groundwater potential zone maps and groundwater resource planning. The present study’s framework and the results will be valuable for improving the efficiency of irrigation, conserving rainwater and maintaining the ecosystem in India.

Proper site selection for solid waste disposal is a significant issue in the management of solid waste. The present study has been carried out in Debark town, Amhara region, Northwestern Ethiopia, with an analytical hierarchy process (AHP) method and geographic information system (GIS) tools to locate the suitable solid waste disposal sites. In the present study, the following eleven thematic layers such as groundwater level, lithology, land use/land cover, precipitation, soil types, elevation, and slope, distance from the (drainages, springs, lineaments, and roads), and their sub-criteria have been used for the selection of suitable solid waste disposal sites. The above-mentioned thematic factors and their sub-criteria standardized weights and consistency ratios have been calculated and checked using the AHP method. The outcome of this study shows (2 km2 area) 2.50%, (3 km2 area) 3%, and (77 km2 area) 94.5% of the area is highly, moderately, and unsuitable, respectively, for the siting the solid waste disposal site in the present study area. The current study results show the effectiveness of GIS tools and the AHP method in solid waste disposal site selection analysis.

In this study, it is aimed to examine the studies based on the AHP (Analytic Hierarchy Process) method in the field of education and to present the researcher's perspective on how to use the AHP method in the field of education. Within the scope of this aim, firstly the AHP method was introduced with a sample application and then the results were interpreted. The other aim of the research; studies which based on the AHP methods in the field of education in the last five years have been examined through content analysis. AHP; is one of the “Multiple Criteria Decision Making (MCDC)” methods that can determine the priority or weights among the criteria and alternatives based on comparative judgments. The content analysis conducted within the scope of the research was carried out in the context of eight criteria determined by the researchers. According to the results of the analysis; the AHP method has shown an increasing tendency compared to the years, and usually is used for determining and prioritizing teaching priorities. Especially in Asia Pacific countries, the AHP method is used much more intensive. Another result is that the AHP method is used to make group decisions rather than individual decisions. It has been seen that the research has been done especially with undergraduate students. In addition to these, there are lots of studies with academicians and experts.

With the rapid development of science and technology, new technology is starting to be used in various fields including education. Education has a very important progress in a nation, because it can optimize individual potential. The educational process in higher education has a big influence on a student's future. However, there are many students who experience difficulties in choosing a college major after graduating from vocational high school (SMK) or senior high school (SMA), because of the complexity in identifying the suitability between interests and study programs. Decision making is a problem that everyone faces, especially in choosing an appropriate college major. There are many factors to consider, and with many options available, the decision-making process can be difficult. To overcome this problem, this research aims to create a decision support system (DSS) using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique For Order By Similarity To Ideal Solution) methods. The AHP method is used to solve complex problems by structuring a hierarchy of criteria and developing weights or priorities. However, when the AHP method is used with many criteria and alternatives, other methods are needed for more effective results. Therefore, a combined method of AHP and TOPSIS was chosen, where AHP focuses on pairwise comparison matrices and consistency analysis, while TOPSIS can measure relative performance and alternative decision making simply and efficiently. The results of research on decision support systems for selecting majors using the AHP and TOPSIS methods show that the application of the combined AHP-TOPSIS method can be used to determine the best alternative in selecting majors by comparing alternatives based on predetermined criteria. In addition, system testing results show that the system functions as expected and meets user needs. With a decision support system for selecting college majors implemented on the website, it can simplify the decision-making process for students and BK teachers in choosing college majors. The results of the calculation of the percentage of system feasibility in blackbox testing show a value of 95.71%, which indicates that this major selection decision support system website can be used.

Remote sensing (RS) and Geographic Information System (GIS) are potential tools for competent planning and administration of essential groundwater resources. In this study, a typical methodology is proposed to delineate groundwater target zones using integrated RS, GIS and Analytical Hierarchy Process (AHP) method. The developed methodology is confirmed by a case study in Karur district of Tamil Nadu, Southern India. Seven thematic layers, viz., Lithology, Lineament Density, Geomorphology, Slope, Post– Monsoon Water Level, Drainage Density and Landuse/Land cover were considered in this study. Selected seven thematic layers and their features were assigned suitable weights on the Saaty’s scale according to their virtual significance in groundwater incidence. The assigned weights of the thematic layers and their features were then normalized by using AHP. Finally, the selected seven thematic maps were incorporated by weighted linear combination method in a GIS environment to produce a groundwater targeting map. Thus, five groundwater targeting zones were identified and demarcated in the study area, viz., ‘very good’, ‘good’, ‘moderate’, ‘poor’ and ‘very poor’. The groundwater targeting map was finally verified using the well discharge data and the result was found acceptable. The ultimate result depicts the favorable groundwater targeting zones in the study area and can be helpful in better planning and managing of groundwater resources particularly in hard rock terrains.

The purpose of this study was to develop landslide susceptibility analysis techniques using artificial neural networks and to apply the resulting techniques to the study area of Boun in Korea. Landslide locations were identified in the study area from interpretation of aerial photographs and field survey data. A spatial database of the topography, soil type, timber cover, geology, and land cover was constructed and the landslide-related factors were extracted from the spatial database. Using these factors, the susceptibility to landslides was analyzed by artificial neural network methods. The results of the landslide susceptibility maps were compared and verified using known landslide locations at another area, Yongin, in Korea. A Geographic Information System (GIS) was used to analyze efficiently the vast amount of data and an artificial neural network turned out to be an effective tool to analyze the landslide susceptibility.

Detecting the different blends of diesel and biodiesel fuels using electronic nose machine coupled ANN and RSM methods


 Strategies to buy a house, consumers often experience problems in determining the house to be purchased, because each house has different characteristics. These characteristics will be used as reference considerations in determining which house to buy. In this study, the AHP (Analytical Hierarchy Process) method was used to weight the criteria and test the level of consistency with the pairwise comparison matrix. If the matrix has been consistent, then it can be continued to rank to determine the chosen alternative by using input weighting criteria obtained from the AHP method. To overcome the above problems, it is necessary to build a decision support system by implementing a ranking that can make it easier to determine House Selection using the AHP (Analytical Hierarchy Process) method. Of the 9 sample houses in the Cepu area, the highest was the Housing of Zam Zam Cepu Type 38/78 with a total value of 2,84564719.

This study aims to provide recommendations for gaming laptops using the AHP method with criteria for Hardware used, Graphics Card, Design, Cooling System, Reliability, Connectivity, Price, so that it becomes a solution for gamers in choosing the right laptop for gaming. The decision support system for gaming laptop selection recommendations developed is implemented using the Analytical Hierarchy Process (AHP) method. Where the AHP method can describe complex multi-factor or multi-criteria problems into a hierarchy, then the importance of each variable is given a subjective numerical value to be compared with other variables through a paired comparison matrix. Based on the assessment results using the AHP method, a recommendation for choosing the first gaming laptop by Dell Gaming G15 with a value of 0.806, the second model recommendation was obtained by Acer Nitro with a value of 0.5745, the third model recommendation was obtained by MSI Bravo 15 B5DD with a value of 0.524.

Scheduling is one of the important things in teaching and learning process. The Analytical Hierarchy Process (AHP) method is a system analysis method that can be used to connect unstructured situation into a spesific part that used to make an effective decisions. The application of AHP based on the decomposition of objectives, evaluates values through pairwise comparisons in stages and able to choose the best alternative from some alternatives. The purpose of this study is to prove whether the AHP method can be used to determine scoring for the election of lecturer schedules and to knowing the result of AHP’s scoring The data in this study are: criteria of the subjects, lecturers, SKS, lecturer status, space, time to determine the score and alternative, namely in the form of even semester teachers. As for producing departmental recommendations, input is needed in the form of score resulting from the AHP calculation and calculating the space that shows the floor, day and course. This study uses comparative data and the same alternative from previous studies,that is scheduling data for the Even Semester of Mechanical Engineering Study Department that certain on scheduling for regular lectures. The final results of this study include several names that can be used for scheduling first. Judging from the previous research using the DS / AHP method, 17 lecturers got the order from 29 lecturers, but in this study, the whole can be sorted.

Pharmacy staff is a health service that needs to improve the quality of its service to answering customer expectations and demands. AHP (Analytical Hierarchy Process) and Rating Scale are powerful instruments as evaluation tools in management because they can assess the performance of the Hospital Pharmacy Installation. This study aims to analyze the performance of pharmacy officers in drug distribution using the AHP (Analytical Hierarchy Process) method and the Rating Scale at Bhayangkara Hospital Medan in 2020. This type of research is quantitative research. The research design uses a correlation study with a retrospective approach equipped with a sheet. Observations are in the form of a table list. The sample in this research is all officers involved in the distribution of drugs in the inpatient room of the Bhayangkara Hospital Medan who receive drug distribution from the pharmacy. The sampling technique in this study used a total sampling technique, namely taking a sample of the entire population in the study. Based on the sampling technique, the total sample was 57 people. The results of the cross table between the performance of pharmacy officers in drug distribution using the Rating Scale method in the Bhayangkara Hospital Installation in Medan in 2020, which shows the p-value for each variable, namely the quality p-value = 0.000, the quantity value p = 0.006, the use time value p = 0.000, the cooperation value p = 0.000. This study concludes that there is an influence between the performance of pharmacy officers in drug distribution using the AHP method and the Rating Scale at the Bhayangkara Hospital Installation in Medan in 2020. It is recommended that pharmaceutical officers further improve health services, especially paying attention to drug distribution for each installation in the hospital. Keywords: Performance, AHP, Rating Scale, Pharmacy Officers.

Tabbinjai Village is susceptible to landslides due to high rainfall, steep topography, and human activities. This study aims to determine the zone of landslide vulnerability using geophysical data and satellite imagery to generate a level of landslide vulnerability map in Tabbinjai Village. The AHP (Analytical Hierarchy Process) method is used to determine the weight composition of satellite imagery data, and Seismic vulnerability and slip plane identification are geophysical methods that include the HVSR (horizontal-to-vertical spectral ratio) method and the Wenner-Schlumberger configuration, respectively. Based on the AHP method, landslide susceptibility is classified into low (60.67%), moderate (37.89%), and high (1.44%) susceptibility zones. These spatial findings are supported by the in situ seismic vulnerability index (Kg) and geoelectrical resistivity profiles, confirming the strong likelihood of slope failure in critical areas. Therefore, integrated satellite imagery and geophysical data provide a reliable reference for regional spatial planning and disaster mitigation strategies.

This study applies the Gaussian Analytical Hierarchy Process (Gaussian AHP) to landslide susceptibility mapping and demonstrates its superior methodological rigor and predictive performance relative to the traditional AHP method. Susceptibility maps produced by Gaussian AHP allocated 26.31% of the study area to the very high susceptibility class, outperforming the traditional AHP’s estimated share (23.52%), and achieved a more balanced distribution across all five classes. Validation against a high resolution inventory of 97,742 landslide samples collected during the February 2023 São Sebastião event—divided into 70% training and 30% validation subsets—yielded improved metrics: ROC area under the curve of 0.6360 versus 0.6220; overall accuracy of 0.6364 versus 0.6229, balanced accuracy of 0.6356 versus 0.6221; and sensitivity of 0.3585 versus 0.3116, for the Gaussian and traditional AHP methods respectively. An uncertainty analysis quantified a 56.16% disagreement between the two methods, revealing that Gaussian AHP reduced classification ambiguity in critical classes. A complementary density-based assessment, comparing observed landslide crown points and scar polygons against susceptibility class areas, showed that Gaussian AHP produced a gradual, coherent increase in normalized landslide density from very low to very high susceptibility, whereas traditional AHP displayed sharp breaks in intermediate classes. These findings confirm that Gaussian AHP enhances objectivity, spatial coherence, and operational reliability, better aligning high density landslide clusters with the highest susceptibility zones. By leveraging statistical weighting, Gaussian AHP streamlines data preprocessing and reduces the need for expert calibration, making it well suited for assessments in data rich environments. The statistical weighting procedure facilitates the integration of diverse geospatial datasets and supports robust, reproducible multicriteria decision analysis. Its integration with accurate machine learning-derived land use/land cover data and refined climate data is recommended to further improve predictive accuracy and support proactive landslide risk management strategies. The proposed approach can additionally meet operational purposes, provided that near real-time climate data, updated geospatial databases, and massive computing resources are available.

Landslide susceptibility zonation using geospatial technique and analytical hierarchy process in Sikkim Himalaya

There is a need to increase the effectiveness and efficiency with which the operational fund budget is managed at RSUD Brigjend H. Hasan Basry Kandangan. Declining revenue projections and limited resources mean that hospitals must determine budget priorities in an objective and measurable way. This research aims to analyse the application of the Analytical Hierarchy Process (AHP) method to determine operational fund budget priorities, providing recommendations to support more effective decision-making in a hospital environment. A qualitative approach was used, involving data collection through interviews and documentation, and analysis using the AHP method with the assistance of Expert Choice 11 software to compare criteria and service alternatives. The results showed that the main criteria for determining budget priorities are potential income, market demand, operational costs and limited resources. The analysis prioritised home care services due to their high revenue potential and market demand. The application of AHP has also been proven to increase the efficiency, transparency and accountability of budget decision-making processes. This study concludes that the AHP method can be an effective tool for BLUD Hospital's operational budget prioritisation process. It is recommended that the method be integrated into all work units and supported by training for optimal application.