Decision Support System for Selection of the Superior Mango Seeds Using Web-based Analytical Hierarchy Process (AHP) Hybrid Simple Additive Weighting (SAW) Method

— Indonesia is a horticultural country that agricultural production, one of which is mango production. Mango ( Mangifera indica L ) is one of the leading horticultural commodities in Indonesia. The use of high-quality seeds has made an impact influence on the productivity of farming, to increase the productivity of farming, it is very necessary to provide superior seeds for farmers so that farmers can increase yields and quality of production. With so many manga seeds available, a Decision Support System is needed or often called a Decision Support System (DSS). DSS is a model-based system consisting of procedures in processing and considerations to assist farmers (users) in making decisions on the selection of high-quality manga seeds. In this research, the method used is the Analytical Hierarchy Process (AHP) in searching for the weighting criteria and the Simple Additive Weighting (SAW) method in performing alternative rankings. The results of this study are to make it easier for farmers and the community in choosing superior manga seeds.


I. INTRODUCTION
Indonesia is a horticultural country that agricultural production, one of which is mango production, one of which is the production of mangoes.by use of superior seeds has a major effect on the productivity of farming, to increase the productivity of farming, it is very necessary to provide high-quality seeds for farmers and the community so that farmers can increase the yield and quality of production of superior mango seeds (Yahyan and Siregar 2019).
A Decision Support System (DSS) is a model-based system consisting of procedures in processing and considerations to assist farmers (users) in making decisions. In order to succeed in achieving its objectives, the system must be simple, robust, easy to control, fully adaptable to important matters, and easy to communicate with (Oktaputra, et al 2014). In this research, using a combination of two methods, namely AHP and SAW. The AHP method is used to determine the weight of importance between criteria (Sugianto, et al 2016). The SAW method is used to determine the value of alternative preferences based on criteria, so as to produce a ranking of each alternative.
Based on the description of the background of the problems mentioned earlier, the formulation of the problems proposed for this research One of the problems is that a large number of existing manga seeds can make it difficult for farmers to determine high-quality superior manga seeds. Therefore, special knowledge is needed about high-quality mango seeds so that harvest yields are more optimal, for that a decision support system application is needed that is able to provide information and recommendations to farmers about good quality mango seeds.
The purpose of this research is to design a computerbased decision support system to choose alternative superior mango seeds that can be used to help facilitate farmers who cultivate mango plants in choosing superior mango seeds.

A. Literature Study
Some of the literature that used as a guide and reference in this research include: Research conducted by Beni Irawan (2013) entitled "Decision Support System for Selection of Oil Palm Seeds Using the Simple Additive Weighting (SAW) Method". The system made for this decision is using the SAW (Simple Additive Weighting) method. The SAW method is to find the weighted sum of the performance ratings for each alternative on all attributes.
Research conducted by Ardhy (2018) entitled "Decision Support System for Corn Seed Selection Using the Analytical Hierarchy Process (AHP) Method at the Abadi Jaya Store, East Lampung". In this research, a decision support system can help users determine Corn Seeds according to the desired alternatives and criteria. The method used is Analytical Hierarchy Process (AHP).
Research Aripin, et al (2018) entitled "Decision Support System for Selection of the Best Mango Seeds Applying SAW and WASPAS Methods". This study also uses two comparison methods, namely the Simple Additive Weighting (SAW) method, and the Weighted Aggregated Sum Product Assessment (WASPAS) method. It will be able to select each attribute from the best alternative from several available alternatives.
Research conducted by Yahyan and Siregar (2019) entitled "Decision Support System for Selection of Web-Based Superior Rice Seeds using the Analytical Hierarchy Process (AHP) Method". This study reviews how to select superior rice seeds. If farmers can choose quality rice seeds, the harvest will be as their wishes, then a decision support system for selecting superior seeds is made using a web-based Analytical Hierarchy Process (AHP) method to facilitate farmers in obtaining information and assisting farmers in making decisions about seeds to be harvested.
Research (Didik Heriyantoro, et al (2020) entitled "Decision Support System for Determining Outstanding Teachers with AHP and SAW Methods at Markus High School in Tangerang". In this research, to build a decision support system application that provides recommendations for the selection or determination of outstanding teachers at Markus High School in Tangerang, accessed quickly, directly, and accurately in determining the results. The method used is the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods to provide an alternative assessment of outstanding teachers. The results of this study in determining the criteria at Markus High School in Tangerang using 5 (five) parameters, namely pedagogics, personality, social professionals, absences, and the sub-criteria used are illness, permission, and neglect. The results of this study can be concluded that the highest and best value using the SAW method falls on the Pracaya alternative with a value of 4.46 this highest value can be taken into consideration by the teacher to be selected for determining the desired outstanding teacher. Theoretical Foundation 1. Decision Support System A Decision Support System (DSS) is part of a computer-based information system including a knowledge-based system or knowledge management that is used to support decision making in an organization or company. It can also be said as a computer system that processes data into information for making decisions from specific semi-structured problems (B. Ali 2019). Artificial intelligence-based decision support systems can perform diagnoses in the form of knowledge, expert analysis, pattern recognition, and others in the scope of various cases (Muslimin B 2012).

Analytical Hierarchy Process (AHP)
Analytical Hierarchy Process (AHP) is a multicriteria decision method for solving complex or complicated problems, in an unstructured situation into parts (variables) which are then formed into functional or structural hierarchies to display the problems to be solved and then build a priority order for alternatives. Through pairwise comparisons based on the judgment of the decision-maker on the system. In this system, the AHP method is used in calculating the weight value of each criterion (Fatmawati, et al 2017). Troubleshooting hierarchy for AHP method can be seen in Picture 1. Have the same effect.

3
One element is slightly more important than the other.

5
One element is more important than the other.

7
One element is clearly more important than the other elements 9 One element is definitely more important than the other.
opposit e If activity i get one point compared to activity j, then j has the inverse value compared to i.

3) synthesis of priority
For each criterion and alternative, it is necessary to do pairwise comparisons. The weights or priorities are calculated by manipulating the matrix or by solving mathematical equations. The considerations for pairwise comparisons are synthesized to obtain overall priorities through the following steps: a) Square the matrix of pairwise comparisons. b) Count the number of values from each row, and then normalize the matrix. If the value is more than 10%, then the data judgment assessment must be corrected. However, if the consistency ratio (CI/IR) is ≤0.1. then the calculation results can be declared correct. List Index Random Consistency can be seen in table 2. The Simple Additive Weighting (SAW) method is often also known as the weighted addition method. The basic concept of SAW is to find the weighted sum of the performance ratings on each alternative on all attributes. The SAW method requires the process of normalizing the decision matrix (X) to a scale that can be compared with all existing alternative ratings. The SAW method must have several alternatives (A), criteria (C), and weight (Weight/W) which have the weight of provisions. SAW solution steps: a) Determine the alternative, namely Ai. b) Determine the criteria that will be used as a reference in making decisions, namely Cji. c) Provide the value of the suitability rating of each alternative on each criterion. d) Determine the weight of preference or level of importance (W) for each criterion (1) (1) e) Create a match rating table for each alternative on each criterion. f) Make a decision matrix X which is formed from the suitability rating table of each alternative on each criterion. The x value of each alternative (Ai) on each predetermined criterion (Cj), where, i=1,2,…m and j=1,2,…n (2) (2) g) Normalize the decision matrix by calculating the value of the normalized performance rating (rij) from the alternative Ai on the Cj criteria (Kusmandewi, 2006).
(3) Description of each criterion (3) : normalized performance rating value. : attribute value belonging from : greatest value of each criterion. : smallest value of each criterion. Benefit: if the biggest value is the best. i) The final result of the preference value (Vi) is obtained from the sum of the normalized matrix row elements (R) with the preference weights (W) corresponding to the matrix column elements (W).
The calculation results of a larger Vi value indicate that alternative Ai is the best alternative (Beni Irawan 2013).

Unified Model Language (UML)
In designing this system the author uses the Object-Oriented Analysis and Design method, with activities that focus on model development using the Unified Model Language as a system design tool consisting of use cases, activities, and class diagrams. According to Booch "UML is a standard language for creating software designs, UML is usually used to build documents from software-intensive systems". UML is a standard language that is often used to describe the process of analysing and designing object-oriented systems (Yusman 2013).

Hypertext Preprocessor (PHP)
PHP or Hypertext Preprocessor is a web-based programming language that can process dynamic data. PHP is said to be a server-side embedded script language, meaning that the syntax and commands that we provide will be fully executed by the server but included in ordinary HTML pages. Applications built by PHP, in general, will give results in a web browser but the whole process is run on the server, in principle, the server will work if there is a request from the client. In this case, the client uses PHP codes to send requests to the server (Elisa 2012).

My Structured Query Language (MySQL)
My Structured Query Language MySQL is a very popular type of database server. MySQL is a type of RDBMS (Relational Database Management System). MySQL supports the PH programming language, a structured query language because SQL has several rules that have been standardized by an association called ANSI. MySQL is an RDBMS (Relational Database Management System) server. RDBMS is a program that allows database users to create, manage, and use data in a relational model (Fahrozi and Harahap 2018).

A. Research Procedure
This research was conducted based on the research steps. The flow of application creation is shown in Picture 2. In this method flow describes a flow of the application of two combined (hybrid) methods where each method has different but related tasks. The first method is the AHP method to compare each criterion to produce a weighted value for each criterion. While the SAW method evaluates each alternative by normalizing each alternative to produce a ranking. The following is the flow of the research method, which can be seen in Picture 3.  Picture 3. Flow of the method C. Design system System design uses the next stage after system analysis, to get a clear picture of what will be done in system analysis then proceed with thinking about how to form the system. System design is a phase where design expertise is needed for the commuter elements that will use the system, namely the recovery of equipment and computer programs for the new system. Use case diagram for system can be seen in Picture 4.

Picture 4. Use Case Diagram
The explanation of the Use Case flow in Picture 4 can be seen in table 3.

Admin Criteria Analysis
The system analyzes the criteria and then generates a weight value for each criterion.

Admin Alternative Analysis
The system analyzes alternatives with data on each criterion so that it can generate the accumulated value of each alternative from the largest value to the smallest value.

Admin Ranking
Admin can see the ranking results of the mango seed selection assessment.

D. Case Manual Calculation
In this research, the AHP method is used to determine the weight of the mango seedling criteria. The criteria used were soil pH, soil texture, seedling age, stems, and pests. The criteria data used are data from interviews with Mr. Ali as a resource person/expert of manga seeds in Lobang Tiga Samarinda. The steps in using the AHP method are: 1. Defining the problem and determining the desired solution, then compiling a hierarchy of the problems encountered. The hierarchy of determining superior mango seeds can be seen in Picture 5. Picture 5. Mango Seed Hierarchy Structure 2. The comparison matrix from level two is the criteria by taking into account the relationship with level one. Comparison of Criteria Can be seen in Table 4. -81 -3. The result of comparison of criteria matrix with decimal conversion. Can be seen in Table 5. 4. Perform normalization in a way, the value of each cell of the column is divided by the number of each column. Then, the next step is to create a normalized matrix. Normalization matrix can be seen in Table 6.  6. Calculate the maximum Eigen by multiplying each first cell value with the priority weight, the value in the second cell column with the second priority, and so on. The maximum eigen table can be seen in Table 8.   Table can be seen in Table 9 Table 9 -82 -CR ≤ 0.1, the consistency ratio of the calculation can be accepted. Furthermore, the SAW method calculates to get the final score and handle alternative mango seeds according to the final value obtained. The steps of the SAW method are as follows: 1. Determine the criteria used as references in decision support. Can be seen in Table 10, 11, 12, 13, and 14 (M. Ali 2021). 5. Then normalize the matrix based on equations that are tailored to the type of attribute (benefit attributes and cost attributes) so that the Equal Matrix is obtained R. The results of the matrix that have been predicted after calculating using the benefit and cost formula.
6. The process of the circle is done by checking the C1 weight value with the first-row value in the first column of the results of the normalization of the matrix. Then the value of C2 weights with the second-row value in the second column and the set. The ranking table can be seen in Table  17.

IV. RESULTS AND DISCUSSION
The stage is the coding stage of the implementation that has been made into a programming language. The coding will produce an interface or display for the Decision Support System for Selection of Superior Mango Seeds Using the Analytical Hierarchy Process (AHP) Hybrid Simple Additive Weighting (SAW) method based on WEB.
Here are some of the views contained in the application: A. Criteria comparison page The Comparison Page Criteria can be accessed by the admin and user. However, the admin has advantages, where the admin can re-impair any criteria, while the user does not. This page also displays the calculation of the criteria for obtaining the criteria weights. The admin criteria and user calculation page can be seen in Picture 6. Picture 6. Criteria comparison page a. Criteria and Weights Page This page displays the results of the criteria weight values that have been compared with the criteria that have resulted in the weight values in the previous calculation. This page can be accessed by admin and user levels and the data on this page can only be viewed without being biased by the admin or user. The criteria weight page can be seen in Picture 7. Picture 7. Criteria and Weights Page

B. Alternative Page
The Alternative page contains alternative data, where the admin and user levels can access this page. In addition, the admin and user levels can add, edit and delete alternative data. Alternative pages can be seen in Picture 8. Picture 8. Alternative Page

C. Calculation results page
This page displays the results of the combined calculation of the AHP Hybrid SAW method and produces a preference value that determines the superior mango seeds. The greatest preference value of all available alternatives is the first rank of superior mango seed and is the best seed. The display of SAW calculation results can be seen in picture 9.
Picture 9. The Ranking Result Page V. CONCLUSION Decision Support System for Selection of Superior Mango Seeds designed with the Analytical Hierarchy Process (AHP) Hybrid Simple Additive Weighting (SAW) method can make it easier for users to choose the best seeds from mango plants, so users who are still difficult to determine superior mango seeds can easily choose mango seeds without having to be confused about which one is the best. -84 -By applying the Analytical Hierarchy Process (AHP) Hybrid Simple Additive Weighting (SAW) method on the Decision Support System, it was found that the calculation results for the selection of mango seeds were following the manual calculations that had been carried out which concluded that the application had worked well.