PAIRWISE COMPARISON METHOD FOR DETERMINING GEOGRAPHIC DIFFICULTY LEVEL (CASE STUDY: BANDUNG BARAT REGENCY)

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1 PAIRWISE COMPARISON METHOD FOR DETERMINING GEOGRAPHIC DIFFICULTY LEVEL (CASE STUDY: BANDUNG BARAT REGENCY) Nur Ainiyah 1, Albertus Deliar 1, Riantini Virtriana 1 1 Remote Sensing and Geographic Information Science Research Division Institute of Technology Bandung (ITB) nur.ainiyah0108@gmail.com, albertus.deliar@gmail.com, riantini.virtriana@gmail.com KEY WORDS: Geographic Difficulty Level, Geographic Information System, weighting, pairwise comparison. ABSTRACT: Geographic Difficulty Level (GDL) is a picture of human limitations in conducting activities in the earth s space as an impact of physical topography of the earth. Roads and slopes are one of geospatial parameter that can be used to determine GDL. Spatial decision making process in determining the level of interest between parameters in GDL s determination is quite difficult if field measurement and parameter s checking are conducted directly. Therefore, the utilization of Geographic Information System (GIS) application on determination activity of GDL to process both spatial and non-spatial data, are expected to facilitate the work and provide the optimal results in terms of time, cost, and effort. Data processing in GDL s determination can be obtained through weighting techniques by using pairwise comparison (PC) method. PC is one of method to process the decision making scientifically and rationally in providing solution to problems of using the complex parameters in various alternatives. The whole results of application concepts and methods in data processing indicate that model can provide the GDL s information of a region. Furthermore, the decision making can be carried out to determine the areas with relatively have more difficult GDL and or relatively low compared to another areas. 1. INTRODUCTION Definition of Geographic Difficulty Level (GDL) can be derived from definition of geographic and difficulty level. Geographic is a physical characteristics of the earth and human activities in it as an impact of physical topography of the earth (Pidwirny, 2006). Difficulty level is a picture that shows the ease or difficulty from a case (Arikunto, 1999: 207). So that GDL is a picture of human limitations in conducting activities in the earth s space as an impact of physical topography of the earth. Roads and slopes are one of geospatial parameter that can be used to determine GDL. Assessment of the road is given to every class of road based road s function according to PP (regulation of government in Indonesia) 2006 no. 34 section 9 to 20 about the road and based the Department of Public Works (PW) including: artery, collector, local, environmental, and walkways. As well as considered the viewpoint based on Minimum Service Standards (MSS) in the field of road, covering are: aspects of accessibility, mobility, and the physical condition of the road. While an assessment of slope is given based on class divisions slope refers to the Guidelines for Preparation of Pattern of Land Rehabilitation and Soil Conservation (1986) including: flat, slightly, rather steep, steep, and very steep. 2. METHOD A method used is weighting. The weight is given to determining level of interest between the parameters. As for a weight in this study using one of methods from weighting is Pairwise Comparison (PC). PC method developed by Saaty (1980) for purposes of the Analytic Hierarchy Process (AHP). AHP is one of the method can be used in the decision making system to take into account the perceptions, preferences, experience and intuition which combines subjective assessment into one logical way. Several steps in the procedure using PC method can be described in Figure 2.1: Start Setting goals Determining a parameter Making pairwise comparison matrix Calculating the Weighted Value Parameter Making scenarios priority weight parameter Calculating weight class for each parameter Consistency test Yes No Weighting finish Figure 2.1 Steps procedure of weighting

2 1) Arranging A Hierarchy of Problems Setting a goal as target system what purpose research. The next level consists of criteria or parameters to assess or consider alternatives. Each criterion can have sub-criteria below and also can have intensity values respectively. 2) Determining The Priority of Each Element in Phases: 2.1 Making Pairwise Comparisons Matrix Comparing elements in pairs according to a criteria given. For pairwise comparisons used form of a matrix. Arrangement of element in matrix describe in Table 2.1. Table 2.1 Pairwise comparison matrix C A 1 A 2 A n A I a 11 a 22 a 1n A 2 a 21 a 22 a 2n... A n a n1 a n2 a nn 2.2 Filling A Matrix Filling a pairwise comparisons matrix is using a value of the preference scale which scale ratio of 1 to 9 which has been established by Saaty (Table 2.2). If an element in the matrix compared to itself, then rated = 1. If i than j get a certain value, then j than i is the opposite value. 2.3 Synthesis Table 2.2 Pairwise comparison matrix Value Definition 1 Equally important 3 Slightly more important 5 More important 7 Strongly more important 9 Absolutely more important 2, 4, 6, and 8 Worth between two adjacent consideration Consideration of pairwise comparisons to obtain overall priority synthesized by step: i. Summing values of each column in a matrix. ii. Dividing each value of column with total corresponding column to obtain a normalization matrix. iii. Summing values of each matrix and dividing by number of element to obtain an average value. iv. Measuring of consistency. In making decision important to know how well consistency is there. This is done because they do not want decisions based on consideration with a low consistency. Low consistency indicated that consideration would appear to be something random and inaccurate. Consistency is important to obtain valid results in real world. Therefore, validation test of assessment pairwise comparison conducted by test Consistency Ratio (CR). Step to calculate a ratio of value consistency: i. Multiplying value of first column with relative priority of first element, the value in second column with relative priority of second element, and so on. ii. Summing each rows. iii. Result of summation rows divided with relative priority element concerned. iv. Dividing above results with many existing elements, this result is called eigenvalues (λ). v. Calculating Consistency Index (CI) using formula :

3 CI λ n = Consistency Index, ratio of consistency deviation = Eigenvalues of order n matrix, average consistency = Order of matrix, compare number of parameter vi. Calculating a ratio consistency to claim limit inconsistency using formula: CR RI = Consistency Ratio = Random Index CR value of pairwise comparison matrix will produce two possibilities are: (1) CR < 0.1 (10%), indicates a level of consistency that is quite rational in giving judgment on pairwise comparison matrix. (2) CR > 0,1 (10%), indicates there has been a judgment inconsistent which affect assessment needs to be repeated again, especially in determining a level of importance from two parameters were compared. Random Index is an index of consistency for each pairwise comparison matrix at random. RI value depends on n as in Table 2.3. Table 2.3 Value of Random Index (RI) n RI n RI RESULT AND ANALYSIS Purpose to be achieved in this research is to create a model which based GIS for determining the GDL can provide information about GDL in an area. Then from the models can be done making to determining difficulty level from each area, which in this case the village area. In a simple hierarchical decomposition of problem can be described in Figure 3.1 Determining the Difficulty of Geography Level Street Slope Environm Rather Artery Collector Local Walkways Flat Slightly Steep ent steep Very Steep Figure 3.1 Hierarchy in determining priority After decomposition problem, the next step is determining a weight of class parameters by forming pairwise comparison matrix for each class of each parameter that has been selected. Giving value to each element of class parameters that can be seen from viewpoint of class which has the relative values more important than others. Assessment of each class parameter can be described in Table 3.1 and Table 3.2.

4 Table 3.1 Pairwise comparison matrix for class of road parameter Table 3.2 Pairwise comparison matrix for class of slope parameter Reading or comparing way is of rows to columns (left to right). For each parameter that is compared with itself will have a value = 1, as in row 1 column 1 (artery compared with artery), row 2 column 2 (collector compared with collector), and so on as in assessment in Table 3.1 and Table 3.2 above. On Table 3.1 when class of collector compared with class of walkway, then collector is very important rather than walkway with a value judgment is 7 on row 2 and column 5. Therefore row 5 and column 2 is filled with the value inverse from 7 is 1/ 7, and so on for charging pairwise comparison matrix in each element. That means as illustrate by Figure 3.2 below: Collector compared walkway Collectors are very important than walkway Walkway relative very difficult than collector Figure 3.2 Examples of assessment the road class parameters (collector compared with walkway) To obtain final result will be determined priority level of interests, then relative weights of classes on each of parameters that have been multiplied by the value, after then summed by each parameter. The equation is as follows: Class Parameter of Road Class Parameter of Slope Where: KJ & KL = Weighted values of road/ street parameters and slope parameter. = The relative weight of class street including: artery, collector, local, environment (others) and walkways. = The relative weight of class slope including: flat, slightly, rather steep, steep, and very steep. = Long of road class are: artery, collector, local, environment (other), and walkways. = Area of slope are: flat, slightly, rather steep, steep, and very steep. If all calculations have been done, yet can be done related to decision-making where the overall area of measuring parameters, GDL has a relatively higher or relatively lower than other areas. That is because there are multivalued of parameter in each village.

5 Thereby make several models of scenarios final weighted through scoring method for each parameter. The aim is to obtain a single value, so it can be taken a decision or policy. The equation of assigned final weights as follows: Result can be described as Figure 3.3 below: 1 st Model (KJ *50%) + (KL*50%) = DECISION 2 nd Model (KJ *75%) + (KL*25%) = DECISION 3 rd Model (KJ *25%) + (KL*75%) = DECISION (a) (b) (c) Figure 3.3 Graphic of Comparison parameters to the model 1 st (a), 2 nd (b), and 3 rd (c) scenario When all result of calculations have been completed, the next step is to build a data base on data attributes of each parameter of spatial data using ArcGIS software. The data required are: street/ roads (shape file format), slope (shape file format) and village administration (shape file format). Database management performed on data attributes of village administration which previously had to design a data base on all attributes of existing data. The finally result calculation and data processing was done using integration between PC method and GIS, shaped visualization is a modeling in form of a map as Figure 3.4.

6 Figure 3.4 Examples of geographic difficulty level modeling with 1 st scenario model From the graph results of weighting using PC method and scoring parameters to three models (Figure 3.3), obtained weight s value is proportional with priority value. The smaller weight values of interest level, then smaller priority value. The smaller priority value indicates the higher of GDL. Reason for choosing street and slope as an object parameter determining GDL, because in this study only examines the utilization of geospatial information obtained from extraction of spatial and non-spatial data (attributes). And assumed only street and slopes that may affect to model, whereas non-factor other geospatial data mostly from Central Bureau of Statistics (CBS) assumed not to affect outcome. This is because, data obtained from CBS still very low accuracy, highly subjective and depends on charger questionnaire without any consistency test and other statistical tests, so not confidence limits of existing data. Method to get weight s values basically there 4 (four) are: ranking, rating, pairwise comparison, and analysis of trade-offs (Malczewski, 1999). While in this study using PC method, because only PC method equipped with a technique be able to perform a validation test of the consistency in the assessment given. While for the other weighting method has been no technique to perform a validation test of weighting given to existing parameters. Application of PC method in assessment process is comparing between classes on any parameter (class of streets and slopes). Then compare between parameters by giving weight in scoring through the creation of multiple modeling scenarios. From results usage PC method can found analysis that despite validation test has been carried out on assessment process, but method is simply a mathematical method without any statistical testing. It causes not confidence limits of truth that form modeling results. The dependence of model generated a perception that involve subjectivity assessors, also causes a model becomes meaningless if it gives an incorrect assessment. Selection of two parameters in determining GDL in this study causes PC method can only be applied to assess parameters of interest between classes. Therefore assessment given to class with parameter based on preference assessment can be carried out a validation test (the truth). Validation test in PC method only performed to maintain the consistency of results assessment given in pairwise comparison matrix, not final results. Results of test series consistency that has been done, found that assessment given to parameter class has proved to be consistent. However at the level of inter-parameter cannot to validation test on weighting. In a hierarchy (level) parameter determining of GDL, created three scenarios using a weighted scoring models. This is done because PC method can only be applied to use amounted to more than two parameters, which it can be seen from table preference RI. Parameter (n) amounted to one or two with RI value = 0 (zero). The RI value will affect calculation to get value of CR, where CR = CI / RI. CR value shows how much consistency of assessment given. Therefore if two parameters are used (RI = 0), causing value CR becomes "infinite" or inconsistent and many possibilities that will be generated.

7 At this research established three weights of scenarios model to both parameters using scoring methods. Formation of variation through three scenario models because ignorance by giving weight to level of interest among street parameter and slope parameter. Therefore, variation of weight will be known pattern modeling. Weight value is formed, which is split into ½ (half) equal parts between interests of both parameters (50% street: 50% slope), split into ¾ (three fourths) are combined with ¼ (quarter) other sections to produce a sum value equal to one (75% of street: 25% slope), and reverse a judgment on second model to be (25% street: 75% slope). Based on results of three scenarios modeling established as such, proved capable of providing an overview of level of interest among a parameters with other parameters. However, an assessment is still influenced by subjectivity giver importance weight and absence of a method that can be used to test correctness of assessment results. Therefore an application of scoring methods for other issues related to determination of level of interest among constituent parameters of decision function can be done by setting a standard by giving authority to achieve the desired results or objectives based on special considerations. 4. CONCLUSION AND FUTURE PROSPECT Implementation of GIS technology in modeling using weighting method of PC used in providing an assessment of road and slope parameters for determining an area GDL, has proven its consistency able to assist in decision making process regarding the determination of GDL in rural areas. GIS-based modeling produced by simply utilizing geospatial information such as roads and slope, was quite capable of visually provide relevant information GDL areas that have relatively higher or lower than other regions. Of modeling in this study, it was found that the village is a village in Nyenang region in Bandung Barat Regency which have relative most difficult GDL (higher) than other village. While the village that has lowest relative GDL (not difficult) through first and third modeling is Cikahuripan village, as well as the results of modeling is Village of Mount Masigit. However, it should be noted, that modeling is generated using only two parameters derived from extraction of geospatial data sources BIG Thus, changes in object or detail information on modeling results are still low and the lack of validation of test results, causing no limit accuracy or confidence in modeling results obtained. For the other data sourced from CBS as compiled as a component in determination of GDL is also not included, so it is still very possible for modeling the resulting change and priority level of village GDL also changing positions. However, this modeling can at least contribute in providing input or an example of modeling in calculation determining GDL an area. Of overall data processing and discussion that has been done, then with humility researchers said that there is still a shortage in this thesis. Therefore, if there are some suggestions that can be submitted by the author, with the aim to enhance and improve further research into a better direction. As for future prospect that can be delivered include: 1) Adding a parameter to determine or measure geographic difficulty level on region, in addition to roads and slope-related data such as the availability of basic services, infrastructure conditions, and access to transportation. The hope to obtain a comprehensive picture of more thorough and related areas that have priority geographic difficulty with seeing objects and resources they have, so we get more accurate results for optimal utilization of information. 2) It would be nice to do ground check to determine complete picture of each a geographic conditions in village at Bandung Barat Regency, and is also done to determine and calculate the accuracy of results interpretation through field inspections and results of data processing. 3) Need for comparison and or merging with other methods in addition to weighting method using PC or scoring. The hope a results provided more accurate and more detailed, also can compare the most appropriate method in assisting decision-making process on priority setting GDL region.

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