Journal of Information Technology and Computer Science Volume 7, Number 1, April 2022, pp. 47-59
Journal Homepage: www.jitecs.ub.ac.id
Recommendations for Selection of New Students at State Islamic High School Using the Analytical Hierarchy Process – Weighted Product
Muhammad Rizky Abdul Gofur*1, Ahmad Afif Supianto2, Nanang Yudi Setiawan3
1,2,3Faculty of Computer Science, Brawijaya University
1rizkyraka.mrag@student.ub.ac.id, 2afif.supianto@ub.ac.id, 3nanang@ub.ac.id
*Corresponding Author
Received 08 July 2021; accepted 30 September 2021
Abstract. State Islamic High School Sidoarjo is the only Islamic High School in Sidoarjo Regency under the Ministry of Religion. Many applicants always fill State Islamic High School Sidoarjo compared to the number of admission quotas, so it takes the suitable method to select new students. However, State Islamic High School Sidoarjo has not found the correct method in determining new students, and the school has not used the data of new students as best as possible.
In solving the problem, the methods used are AHP (Analytical Hierarchy Process) and Weighted Product. The AHP method is used in determining the weight of the criteria used, while the Weighted Product method is used to assess the quality of the recommendation data. The data used in this study is the admission data of new students in State Islamic High School Sidoarjo school year 2020/2021, with 875 data. The expected result is 267 prospective students who qualified, 40 candidates declared in reserve, and 568 did not qualify. The results conduct test agreement using the coefficient kappa generated value 0.837 (excellent). Data-limited visualizations are done with Google Data Studio in a dashboard of graphs and cards. Usability testing conducted using the System Usability Scale with a value of 81 shows the dashboard successfully deployed in the registration selection program of new students of State Islamic High School Sidoarjo.
Keywords: school registration, analytical hierarchy process, weighted product, dashboard, system usability scale.
1 Introduction
Education provides knowledge, skills, and habits performed by a group of people passed down from generation to generation through teaching, research, and even training. Education gets the best function in forming the character and dignity of a nation to make an intelligent nation life. In this era of globalization, many countries compete to support education to advance their education sector. For example, Indonesia has educational pathways starting from formal, non-formal, and informal education [1].
First, formal education is a structured and tiered academic pathway consisting of primary education, secondary education, and higher education. Non-formal education is an educational path outside the legal education path implemented in a structured and tiered manner. Still, we can look at informal education as a pathway to family and environmental education [2]. This educational pathway uses to develop the potential of learners following educational objectives.
Choosing a school is not underestimated because most parents send their children
48 JITeCS Volume 7, Number 1, April 2016, pp 47-59 to an excellent place to support their future education. With the rapid development of technology and the rapid change of globalization, choosing the right school is not easy.
In addition to the increasing number of schools available, each offers various options to prospective students. So does every prospective student who has the characteristics of their choice. Starting from the distance of the school from the residence, facilities, and infrastructure owned by the school, achievements that the previous school has achieved, and extracurricular activities in the school. Later, a selection was conducted by students and parents in choosing a school with a good predicate and wishes [3].
Indeed, prospective students and parents find difficulties determining the right school to be included in the chosen criteria. Students are inaccessible from the admissions system due to frequent server problems. Then there are obstacles for those who do not have much free time to conduct surveys due to government regulation on accepting new learners.
State Islamic High School is a faith-based school that is always in demand by prospective learners every new school year. It does not have an appropriate method in determining the weight of criteria used in rating the selection results of prospective new students and is supported by the measurement of test results that cannot say well.
Because there are still constraints on online tests that cannot conduct direct surveillance, it takes a method to measure the weight of the criteria used precisely and efficiently.
Then there are constraints on the results of the selection data obtained that the data has not been used to the maximum by the organizing committee. The information that can be gotten from the data can waste in vain. Because the data received was evaluated directly at the end of the school year that year. So it takes a way to overcome that.
Some research does previously using Analytical Hierarchy Process (AHP) method.
As in determining the choice of schools in Malang by using several other combinations of techniques. The AHP method combines with the Elimination Et Choix Tranduisant La Realite (ELECTRE) and Simple Additive Weighting (SAW) ways to be classified to be included in the appropriate group and perform a stamping [3]. Furthermore, accuracy testing obtained a score of 82.98%.
AHP is also used in addressing other problems as conducted in research related to positioning [4]. This research uses traditional AHP methods to obtain results by the decisions used in decision making. The criteria used in this study include obedience, work performance, responsibility, honesty, cooperation, and leadership, with three alternative options. Furthermore, it produces the most significant score on the criteria held by work performance of 6.95, and alternative C has the highest score of 21.65.
Other research on AHP and Weighted Product (WP) conducts to build a system of selecting the best employees during the COVID-19 pandemic [5]. In this research, a decision support system creates prototypes to solve problems. Then this study produced an accuracy rate of less than 10% with a subject of 5 people and a selection or assessment criteria of 5 categories. Moreover, after testing, the system has been successful and can be used as it should be.
Further research related to AHP is also conducted to optimize rough workers' selection in a company [6]. The AHP method is then combined with the Preference Ranking Organization Method for Enrichment Evaluation (Promethee) because it is considered the best alternative to the five types of preferences in the Promethee method.
The test was conducted using these five preference types and an enormous match value of the regular preference type and preference type of 80%. That indicates that the better the system's compatibility and expertise, the better the system is built.
Research related to the WP method is conducted in selecting a laptop to purchase
Muhammad Rizky et al. ,Recommendations for Selection of New Students: ... 49 [7]. That is for decision-making made following the specifications required by prospective buyers. They make it easier to make decisions built by a web user to do calculations using a system with 100% test results based on manual calculations and calculations.
A method is needed to solve the problems because the data consists of multi- attribute data used in Multi-Attribute Decision Making (MADM). The way to solve this problem is the analytical hierarchy process (AHP) used to determine the weight of the criteria used, then used the second method, namely Weighted Product (WP), which use to perform ratings for the selection of students with new standards. The use of the AHP method and also using the WP method get pretty good results from previous research [3][4][5][6][7]. Then, measure the consistency level of the weight result between the two raters calculated using the Cohen Kappa Coefficient.
Some studies use AHP and WP methods to perform the best employee selection reviewed as a decision support system. The resulting system is successful and worthy of use as a reference as a new reference. This study uses the same method but generates a new recommendation for decision-making.
To solve the problem in the evaluation, I created a dashboard. The dashboard facilitates stakeholders in making decisions and evaluating decision making later. After completing testing using the System Usability Scale (SUS), the user receives the dashboard created and the Guttman scale to measure the features used, whether by the needs of stakeholders or users. This paper is compiled in several ways: the methodology Proposed in this research is explained in Section 3, the results of this study in Section 4, and Section 5 contains the conclusions of this study.
2 Proposed Method
This part of the methodology explained how this research was conducted. This section explained how later prepared data that used in the recommendation process.
Then there also be a process used in the combined method between AHP – WP. The criteria consisting of 4 categories also have several alternative options explained further at the end of this section. It is explained how to conduct an evaluation related to the results and dashboard that has been made before.
2.1 Data Description
This stage is done because it relates to the stages of research that also continue the stage of data collection. The data used results from accepting new State Islamic High School students Sidoarjo in the 2021/2021 school year. The total of data that has been obtained is as much as 875 data. In addition to data from the Admission of New Learners, data retrieval uses interview techniques to obtain supporting information to determine how the Organizing Committee implemented the New Student Admissions system. The data is an Excel file that contains the variables shown in Table 1 below:
Table 1. Variables of Admission of New Students MAN Sidoarjo
Variable Data Type
No Number
Registration No. Text
Nisn Text
Name Text
Gender Text
Department Text
Iq Test Number
50 JITeCS Volume 7, Number 1, April 2016, pp 47-59
Variable Data Type
Subject Tests Number
Qur’an Test Number
Rating Score Number
Total Value Number
Status Text
Information Text
In table 1 is a reference so that later it can be used as one of the bases to be able to make comparisons and calculations in finding the value of the criteria used for calculations and also values in finding out whether the new prospective learners qualified in the selection of candidates who are considerations that can be submitted as a backup. These variables are used as the basis of previous references used by the organizing committee to determine the candidates who qualified who are expected to become students expected by the school.
2.2 Data Preprocessing
The data used amounted to 875 data coming from science majors and social majors.
Then it used all data that tested against the recommendations of selecting new students.
The data consists of declared qualified students, entered the reserve passes, and did not pass the new students MAN Sidoarjo. Then the variables used in the form of variables in the table data are alternative, gender, majors, IQ test scores, test scores of subjects, Quran test scores, report card scores, and descriptions. This description variable is explained whether the new learner belongs to the qualifying category, does not qualify, or enters into the reserve pass.
Then there also be changes to the value of the data derived from the overall test score. Data cleaning is intended to make later it more accessible in the visualization process on the dashboard. Moreover, it can also make evaluating the organizing committee easier. Each value converted to the same range for each category of its value.
2.3 Design of AHP – WP Method
Explanations related to flow charts start from determining criteria and a matrix of comparisons in pairs. After obtaining a paired comparison matrix, the next step is to sum the values of each criteria column. The following result was done to calculate the priority of the criteria of the paired comparison matrix. Determining the priority of the criteria of the next step is the determination of alternatives used as a determination in the recommendation selection of new students. Furthermore, testing the consistency ratio is used to measure how consistent the paired comparisons are, and lastly is to determine the priorities of the overall alternatives. Because it has obtained the value of the criteria weight used, it later is used in the Weighted Product method.
Further explanation related to flow chart Weighted Product method starts from determining the criteria so that weights are obtained for each of the required criteria.
Furthermore, improvements were made to the weight of each criterion so that the weight is equal to one. Then it did the calculation of the Si vector value and the value of the Vi vector. And the step that is born after knowing the value of each alternative derived from vector Vi is to do a rating that later is used as a result of recommendations from decision-making for selecting new students.
Analytical Hierarchy Process (AHP) is a method of functional hierarchy in decision making introduced by Thomas L. Saaty around the beginning of 1970. The
Muhammad Rizky et al. ,Recommendations for Selection of New Students: ... 51 usefulness of AHP covers the shortcomings of the previous method. In this method, it is possible to solve the problem of a component by measuring and adjusting the impact of an element that interacts with others [8]. The main factor obtained from the method is a functional hierarchy with a human assumption. So a striking comparison of the difference between AHP and other methods is in the type of input entered. In understanding this method to solve a problem, we must understand some basic principles that must understand.
In general, the usual procedures performed in the AHP method include:
1. Determining the type of criteria that are used as a requirement in decision making later.
2. Then next, prepare the criteria in the form of a comparison matrix in pairs.
3. Then perform the summation of the matrix columns.
4. After finding the number of columns of the matrix, the next step is to calculate the value by dividing each column element by the sum of the column matrix. Then perform a calculation of the priority criteria used by summing the matrix in step four and then dividing it by the sum of the criteria
5. The next step is to determine the alternatives used in decision-making. Then, after finding the choice used, arrange the option into a comparison matrix paired with each criterion.
6. Then next, do the summation of each matrix comparison paired as many as n matrix pieces that sum per column of the matrix.
7. Then do a calculation of the priority values of the comparison matrix paired with each alternative, Then perform the maximum Lambda calculation.
8. After doing the maximum lambda, a calculation is to perform the estimate of the value of the consistency index or commonly referred to as Consistency Index, by using the following Equation 1:
𝐶𝐼 = 𝜆𝑚𝑎𝑘𝑠− 𝑛
𝑛 − 1 (1)
9. Then perform consistency ratio calculation using the following Equation 2:
𝐶𝑅 = 𝐶𝐼
𝑅𝐼 (2)
If the value of CR < 0.1, then the comparison matrix pairs of criteria have a consistent weight. However, if the value of the CR > 0.1, then the value of the comparison matrix paired from the matrix is inconsistent. So later, if the value is unpredictable, repeated in filling the values in the comparison matrix paired for criteria and alternative elements.
The weighted product is one of the more efficient calculation methods because of the time used in performing calculations in a short period. Weight correction for
∑ Wj= 1 Equation 3 is used as follows:
𝑊𝑗= 𝑊
∑ 𝑊 (3)
Next is the determination of the criteria category used for decision-making. In selecting criteria based on interviews conducted with stakeholders of the organizing committee of new students MAN Sidoarjo. So that the criteria used in decision making consist of four categories of criteria, among others:
52 JITeCS Volume 7, Number 1, April 2016, pp 47-59 1. IQ Test Scores
2. Quran Test Scores 3. Subjects Test Scores 4. Academic Report
These criteria are variables that have value in determining the data used to determine prospective learners who deserve to be included in the list of prospective learners. And it has been approved by the organizing committee to be used as a reference in decision making. After we do the criteria determination, the next step is to compile a matrix of comparisons in pairs. In this step, the thing to do is to place the criteria that have been taken and put them into the table used to create a comparison matrix in pairs. Giving weight to each criterion can use values that vary between 1 to 9 that Saaty has set. Moreover, for the results of the comparison matrix paired from the selection criteria of new students, MAN Sidoarjo presented in Table 2 follows:
Table 2. Paired Comparison Matrix
Criteria IQ Test Quran Test Subject Test Academic Report
IQ Test 1 2 0.5 4
Quran Test 0.5 1 0.333333333 2
Subject Test 2 3 1 5
Academic Report 0.25 0.5 0.2 1
2.4 Evaluation Design
Evaluation is a way to discover the results of calculations using proposed methods to overcome a problem. In other words, the results result in an agreement later. The results obtained are included in the results that have been efficient or not. Then an evaluation of the features that have been made of a dashboard is by what is needed stakeholders likewise, the evaluation results of the dashboard implementation whether it can be received well by users or stakeholders. For performance measurement of the results will be used kappa coefficient while the measurement of features and implementation of the dashboard using the System Usability Scale and Guttman Scale.
Cohen's Kappa coefficient is a measurement technique invented by Cohen in 1960 to perform a measurement agreement between raters conducting a test [10]. Testing using Kappa Coefficients is using if there are not many raters or have fewer raters to do testing So that two raters can assess a subject. Then if the score is a category, there are usually only two categories, namely only the values 0 and 1. In the use of these coefficients, it is expected that the results obtained can produce a good value against both calculations taken from the implementer and the author to produce values that can be taken into decision making.
System Usability Scale (SUS) is a standard method used in collecting data derived from participants who have completed various tasks [12]. SUS is a form of testing an activity derived from a product interface. The method used in conducting the test contains ten questions in which respondents require to provide answers in the form of a scale of 1-5 based on questions containing the interface and tested features. In assessing results, and odd questions, multiplied by 2.5 so that the final score of the
Muhammad Rizky et al. ,Recommendations for Selection of New Students: ... 53 SUS assessment has a range of values from 0 until 100. Moreover, there is a standard produced in testing using system usability scales.
Guttman Scale is one of the scalogram methods used to perform scale analysis to gain a researcher's belief of a research object. Guttman's scale corrected a multiple- choice that aims to know a response from the respondent in measuring the attitude of a respondent of a product. The dimensional unity of a trait and attitude is judged well if measured using the Guttman scale. It is also called a universal attribute (universe attribute) or can also be called universal content (universe of content) [11].
4 Results
4.1 AHP – WP Results
After summing the values of the comparison table in pairs, the next thing to do is sum each of the criteria columns. The function of summing each column of criteria is as easy as doing calculations later. When the comparison matrix numbers are changed to decimal form, one way to find the maximum lambda value later. The results of the summation of each column of the four criteria. The next step is to calculate the elements of each criterion. This step is the same as normalizing the summing of the criteria columns.
Then next is to look for the average value of each row, commonly called relative weight, from the comparison matrix in pairs. The relative weight search aims to determine the priority scale of each existing criteria. The following method is commonly referred to as performing vector calculations of preferences from a paired comparison matrix. The result of the average calculation of each row is presented in Table 5. It can be seen sequentially with a value from high to low ranging from the subjects' test scores, IQ test scores, Quran test scores, and report card scores.
Table 4. The result of calculating the average value of each row
Criteria Result
IQ Test 0.288398487
Quran Test 0.154445145
Subject Test 0.475835435
Academic Report 0.081320933
To produce the value of the Consistency Ratio, the first thing to do is to determine the value of the weighted sum vector or Weighted Sum Vector and perform the calculation of the Consistency Index value. To produce the value of Weighted Sum Vector can be done by multiplying between the comparison matrix paired with the result of the average row value of each criterion and then summing it. The results of the calculation of vectors of weighted. Next is to look for the value of the consistency vector. The result of vector consistency calculation is presented in Table 5. The following is a calculation for the value of the consistency vector:
Next is to calculate the value of the maximum lambda (λmaks) before proceeding to the calculation stage of the value of consistency ratio. Then in doing the calculation of the maximum lambda used the following calculation:
54 JITeCS Volume 7, Number 1, April 2016, pp 47-59 λmaks = (4.024 + 4.0137 + 4.04041 + 4.0065) / 4 = 4.021127871
Table 5. Consistency Vector Results
Criteria Result
IQ Test 4.023912331
Quran Test 4.013710281
Subject Test 4.040414748
Academic Report 4.006474123
Since the paired comparison matrix has an order of 4, the values of the consistency index are as follows:
CI = 4.02112−4
4−1
CI = 0.00704
After we find the value of the consistency index, which is 0.00704, we can determine the consistency of the comparison matrix in pairs by doing a consistency ratio calculation. The following is the result of the calculation of consistency ratio value:
CR = 0.00704
0.9
CR = 0.007825
The value of the consistency ratio shows how much percentage of the consistency level is used in making decisions. Decisions are taken in a paired comparison. Later on, the final value is used as a benchmark for determining quality in a decision. Generally, suppose the value resulting from the consistency ratio equals 0.10 (uncertainty limit determined by Saaty) or has a smaller value. In that case, it can be sure that the paired comparison made as decision-making can have a consistent value [13].
The calculation then calculates the value of the 𝑆𝑖 Vector. The calculation is done by multiplying all existing criteria, further dividing with an alternative test result score with a positive rank with criteria that benefit and has a negative rank if it includes a cost. It can be seen that the selection of students on the test result score does not have criteria that are included in the cost criteria the results of vector calculations.
The calculation performed after performing the vector calculation 𝑆𝑖 is to calculate the value of the 𝑉𝑖 Vector. The result of vector calculation is the determination in weighting the results of existing alternatives. To generate a value from a vector 𝑉𝑖 by dividing the 𝑉𝑖 vector value by each existing alternative by the total overall value of the vector 𝑆𝑖 The results of the vector 𝑉𝑖. Next, do the weighting of vector calculations by sorting the results obtained from the most significant number to the smallest of each major. The results obtained then be categorized as qualifying, qualifying reserves, and not qualifying. The weighting results can be seen in Table 10 for 5 data that fall into the qualifying category.
Muhammad Rizky et al. ,Recommendations for Selection of New Students: ... 55
Table 10. Weighting Results
Ranking Alternative Result Information
1 1 0.001289 Qualified
2 2 0.001285 Qualified
3 3 0.001285 Qualified
4 6 0.001284 Qualified
5 7 0.001284 Qualified
… . … . … . … .
It can be seen that the results obtained from the final calculation with the highest value are at the value of 0.001289. This value is the highest result by proving that the average value goes into an average of 90. But the order 4 and 5 is not the same alternative because the results of alternative calculations 6 and 7 have an average value that is more than alternatives 4 and 5.
4.2 Recommendations consistency using Cohen Kappa Koefisien
The Kappa coefficient is used to measure the agreement between two raters. The purpose of doing this is to find out the results of the calculations have been consistent or not. Furthermore, several previous studies use kappa coefficients in decision-making using the AHP method and produce good results. [14]. Kappa test results are used to determine how much consistency two experts produce. Kappa calculation results using SPSS software is an analysis software owned by IBM [15]. By entering all the results of the actual data and recommendation data obtained.
Table 11. Calculation Results of Kappa Coefficient
Value
Measure of Agreement Kappa 0.837
N of Valid Cases 875
The calculation of Coefficient Kappa produces a value of 0.837 in Table 11. The result indicates that the Interpretation owned by the Coefficient kappa falls into the excellent category because it has a value of coefficient Kappa of x > 0.75 [16]. Thus, it can be ascertained that the new criteria factors can be considered valid and reliable for decision-making. The new criteria used as decision making can be used in making decisions on new students of State Islamic High School Sidoarjo in the following year.
They must be carried out by the organizing committee of the admission activities of new students to achieve success in implementing the selection of new students in the following years.
4.3 Dashboard Implementation
The results of the recommendations were visualized into a dashboard created using Google Data Studio. Google Data Studio is one of the tools used to process data owned by Google into a dashboard used as informative reporting [17]. The recommendations become the basis for the organizing committee for the admission of new students of Madrasah Aliyah Negeri Sidoarjo in determining priorities and references to students
56 JITeCS Volume 7, Number 1, April 2016, pp 47-59 who are declared qualified to enter the selection path and evaluating the admission activities of new learners MAN Sidoarjo.
The main page in Figure 4 contains the new student data distribution values in Iq test score data, Mapel test, Qur'an test, and Report card. Then also contains the results of the percentage data of male and female learners of each major and the percentage data that performs verification. Then on the dashboard in Figure 5 contains the comparison of actual data and recommendation data. On the page, make the results of the average test score and the percentage of learners based on their category. The page also contains recommendations based on actual data and recommendation result data.
Furthermore, both pages are equipped with filters to make it easier to select in search of the required data.
Fig 4. Main Dashboard Page
Fig 5. Recommendations Dashboard Page
4.4 Dashboard Usability using System Usability Scale
Usability analysis is used in the final stages of research to determine how well the quality resulting from a dashboard has been created. As a result, to display the research that has been done. Later used as a tool in this testing stage is the system usability scale, which has advantages in using samples [18]. Later, the calculation is done using
Muhammad Rizky et al. ,Recommendations for Selection of New Students: ... 57 weighting with a value range of 1 to 5. The test was conducted by the chairman of the New Admissions Committee of MAN Sidoarjo, and 9 ranks were conducted as stakeholders to assess the dashboard that has been made.
Based on the calculation of SUS questionnaire scores obtained from respondents of the Chief Executive of PPDB MAN Sidoarjo school year 2020/2021 and nine of the committees, it was concluded that the score was 81. So it can be said that the dashboard created falls into acceptable categories; moreover, the dashboard can be said to be well received by the user. The results can be seen in Table 12.
Table 12. SUS Dashboard Results
Respondent Result
Respondent 1 87.5
Respondent 2 77.5
Respondent 3 82.5
Respondent 4 80
Respondent 5 82.5
Respondent 6 87.5
Respondent 7 72.5
Respondent 8 77.5
Respondent 9 82.5
Respondent 10 80
Average SUS Results 81
4.5 Guttman Scale
The Guttman scale was used to perform the required answers from respondents with the "Yes" and "No" options. The answer is appropriate and, depending on the researcher's problem, the respondent. Following this case, the problem is found in the features contained in the dashboard that has been created. Some of the features contained in the dashboard are the total number of prospective students based on filters, the percentage of student verification results, the gender comparison of each major, the average score on the test, up to the maximum value, and the minimum score as well.
Furthermore, based on the results of the Guttman scale by the chief executive of New Student Admissions MAN Sidoarjo school year 2020/2021 obtained results with a percentage of 100%, which can be said that all features contained on the dashboard have met the needs needed by respondents.
Conclusion
Determination of the results of decision making using the Method Analytical Hierarchy Process - Weighted Product produces results in the form of producing a weighting order of admission of new learners using the criteria that have been determined by the organizing committee also with the weight of the criteria that have been determined. Based on the results obtained, 875 names of prospective students based on the recommendation results are the same as the actual data results. Therefore,
58 JITeCS Volume 7, Number 1, April 2016, pp 47-59 the new recommendations can be used as a reference for the organizing committee to select new students by paying attention to the proper criteria by criteria needed beforehand.
The agreement between the two raters using the coefficient kappa showed a result of 0.837, which falls into the category of excellent. The results carried out analysis using the AHP - WP method can make new decisions.
The usability test results on the dashboard showed a score of 81. It can be said that the dashboard can be accepted by the organizing committee of new students, man Sidoarjo. The calculation of recommendations is then carried out in visualization into Google Data Studio with a simple and attractive look. The dashboard consists of two pages to make it easier to read the data and results that have been obtained. The dashboard view that becomes two pages can make it easier to evaluate for the committee of implementation of new learners and make decisions in determining new learners.
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