DESICION SUPPORT SYSTEM OF LAND SUITABILITY FOR CORN SEED VARIETIES

Determining the suitability of plantation land is a crucial factor in enhancing productivity and sustainability in the agricultural sector. However, existing studies often lack comprehensive approaches that integrate both the prioritization of criteria and precise evaluation of land suitability. This study addresses this gap by developing a decision support system (DSS) for plantation land suitability using a combination of the Profile Matching and Analytic Hierarchy Process (AHP) methods. The AHP method is employed to assign weights to various criteria based on their relative importance, while the Profile Matching method evaluates land suitability based on the generated profiles. The results indicate that this integrated approach provides accurate and detailed land suitability recommendations. Specifically, Buket Rata land is suitable for Clove (preference score: 3.821), Oil Palm, and Tea (3.596); Reulet land is suitable for Cocoa (3.22) and Coconut (3.16); Geulanggang Kulam land is suitable for Clove (3.41), Cocoa (3.35), and Oil Palm (3.29); Sawang land is suitable for Clove (3.41), Oil Palm (3.17), and Cocoa (2.99); and Pesisir Laut land is suitable for Sugarcane (3.353) and Clove (3.173). This DSS not only aids decision-makers in optimizing land use and managing sustainable plantations but also contributes to the broader field of agricultural decision-making by demonstrating the effectiveness of combining AHP and Profile Matching methods.

With the increasing diversity of transportation needs, selecting the most suitable automatic motorcycle (matic) has become a challenge for consumers due to the wide range of available options. This study aims to develop a Decision Support System (DSS) to assist consumers in choosing the best matic motorcycle using the Weighted Product (WP) and Profile Matching (PM) methods. Data were collected through interviews with local motorcycle dealers and official manufacturer websites. The decision-making process focuses on five key criteria: price, engine capacity, safety level, year of release, and the number of available color options. The WP method calculates the preference value of each alternative by multiplying the normalized values with their respective weights. Meanwhile, the PM method compares actual data with an ideal profile and evaluates the resulting gaps. The system was developed using PHP and tested through both manual calculations and application-based validation. Results show that both WP and PM methods consistently recommended the Vario 160 ABS as the top choice. However, the PM method also placed NMAX Neo in an equivalent top position. These findings demonstrate that combining WP and PM methods provides complementary insights. WP offers clearer ranking distinctions, while PM emphasizes alignment with ideal profiles.

This study presents the design and implementation of a Decision Support System (DSS) aimed at facilitating the selection of potential banking stocks by novice investors. The system integrates two well-established decision-making methodologies: the Analytical Hierarchy Process (AHP) and Profile Matching. The objective is to provide a structured, data-driven approach that assists users in making informed and objective investment decisions based on critical financial performance indicators. These indicators include Price to Earnings Ratio (PER), Price to Book Value (PBV), Return on Assets (ROA), Return on Equity (ROE), Earnings Per Share (EPS), Book Value Per Share (BVPS), Debt Ratio (DR), and Dividend Yield (DY). In this system, AHP is employed to calculate the relative weight or importance of each financial criterion through pairwise comparisons, incorporating users judgment in the weighting process. Once the weights are determined, the Profile Matching method is used to assess and rank the alternative banking stocks based on how closely they align with the ideal profile defined by the criteria. The results of the analysis identified Bank Mandiri (BMRI) as the top-ranked stock, followed by Bank Rakyat Indonesia (BBRI) and Bank Central Asia (BBCA), indicating their strong fundamental performance according to the selected indicators. To validate the system's functionality, black-box testing was conducted on 21 different modules, all of which yielded valid outcomes. This confirms that the application operates correctly and reliably. Overall, the study concludes that the DSS is effective, user-friendly, and valuable as a decision support tool, especially for beginner investors targeting the banking sub-sector.

The hybrid method is a combination of the Analytical Hierarchy Process (AHP) method, the Profile Matching method, and the Composite Performance Index (CPI) method, which is used as a process in a decision support system (DSS) to select the best performing lecturers. The selection process requires a systematic mechanism to ensure consistency and transparency in making decisions. So this study used a hybrid method with the criteria listed in the teaching and learning scorecard and the results of student evaluations for selecting the best-performing lecturers. This research aims to provide knowledge about the computed value of the priority level and consistency ratio of criteria from the AHP method, as well as the competence GAP value from profile matching and the ranking value for each alternative using the CPI method. Results showed that the hybrid method succeeded in calculating the weight value of the level of importance and the criteria consistency ratio of 0.049 and was able to determine the best-performing lecturer from 46 alternatives as a candidate with the highest ranking score of 141.12.

PT. Prima Grafika is a digital printing company that is looking for the best prospective employees. Based on research and observations that have been made, the company only uses administrative data in selecting prospective employees. Processing a lot of data and documents with the same applicant's name slowing down the data processing and exceeding the time limit has been determined to get the best employees. The solution to this problem is by making a web-based system in recruitment, a decision support system combined with Analytic Hierarchy Process (AHP) method as a weighting to conduct priority criteria analysis by pairwise comparisons between two criterion so that all criteria are covered, and the Profile Matching (PM) method as a ranking. This study uses three methods of testing, namely, Black Box Testing system tested by 60 respondents who can be accepted by the company; User Acceptance Testing (UAT) obtained from 10 respondents with an ideal score of 900 produced an actual score of 779 or 86.1%, in total this whole system is acceptable; and Delone and McLean Model Test Results obtained from 10 respondents with an ideal score of 850 produced an actual score of 726 or 85.7% which is very good. With the results of ranking: A001 - Cantika Dewi = 4.12, A004-Arif Yulkianto = 3.98, A002 Eprriadi = 3,913, A003-Rika Novriani = 3,467.

Computers have become one of the technological tools that play a crucial role in enhancing society's productivity. Therefore, many desktop computer users assemble their own computers to achieve computer performance according to their preferences or needs. However, some people lack information about the variations, specifications, and capabilities of each computer component to be assembled. This research offers a recommendation system that is part of a decision support system (DSS) to assist users in providing recommendations for computer components that are being sought and needed based on brand, price, and specifications using the Analytic Hierarchy Process (AHP) and Profile Matching methods. Parameters are based on the processor, motherboard, graphics card (VGA), storage, RAM, power supply, and casing with priority categories based on specifications, price, and brand. Data weighting is done using the Analytic Hierarchy Process (AHP) method, while the Profile Matching method is used for ranking the weighting results. The research results show an accuracy rate of 60% using the Profile Matching method, while the AHP method achieves an accuracy rate of 57%.

Assessment of PNPM-MPd’s proposal not run quickly and objectively. The purpose of this research is to create software to help the verification team in conducting an objective assessment of the proposals using the profile matching method and the analytic hierarchy process (AHP). Profile matching method is used to provide an assessment, determination of the gap, and the weighting criteria. While the AHP method is used to calculate the pairwise comparison matrices, eigenvalues​​, priorities, maximum eigenvalues​​, consistency index (CI) and consistency ratio (CR). CR values ​​are used to determine the order in which proposals will be funded by BLM. The final result of this research is decision support system software for assessment of PNPM-MPd’s proposal that can determine the rank of the highest value to lowest. Keywords : Assessment; Profile matching; Analytic Hierarchy Process (AHP)

PT Vizta Pratama Bengkulu is a branch of a franchise company engaged in family karaoke entertainment services, founded by a well-known dangdut singer, Inul Daratista and starting its first operation in 2005 in Kelapa Gading area. PT. Vizta Pratama Bengkulu has not used the Decision Support System Application. The decision to determine the recipient of the annual bonus is only to calculate the total value based on 3 criteria, namely responsibility, discipline, honesty without using a decision support method, therefore sometimes it is felt that the giving of employee annual bonuses is not right on target. Decision support system for giving annual bonus at PT. Vizta pratama using the analytical hierarchy process (AHP) method is a desktop-based application that has implemented the AHP (Analytical Hierarchy Process) method, this application runs on a Windows operating system created using the Visual Basic .NET programming language and SQL Server 2008r2. This application can be used to assist in the assessment process in determining the annual bonus at PT. Vizta Pratama Bengkulu where this application uses 4 predetermined criteria and then processed using the AHP (Analytical Hierarchy Process) method so as to produce values that will be ranked. Based on the results of the Blackbox testing that has been carried out, it can be concluded that the decision support system for providing annual bonuses at PT. Viztapratama by using the analytical hierarchy process (AHP) method is able to run well and can overcome data input errors by users and the SPK application with the Analytical Hierarchy Process method has provided effective results in accordance with the results of calculations using paired comparisons of 4 criteria where the comparison of pairs of criteria must produce consistent weighting criteria.

A decision support system is a solution to help provide decision recommendations in determining which options to choose as a solution, in this decision support system research, namely analyzing and comparing the Matching Profile method and the SAW (Simple Additive Weighting) method in providing the best choice solution in the case of determining teaching staff acceptance. Determination of Admission, The selected teaching staff, are teaching staff who are in accordance with the criteria and quality. In an educational institution, namely TPQ Anbata, it is a very important issue to get elected teaching staff. One way to get teaching staff who is in accordance with the cafeteria is determined by selecting or determining prospective teaching staff by paying attention to various assessment criteria so that the selected teaching staff is feasible. From the tests that have been carried out, the results obtained include all test cases, and the testing is appropriate. The results of the system calculation accuracy test show that the calculation of Matching Profile and SAW (Simple Additive Weighting Method carried out by the system with manual calculations is correct and the feasibility test. Appropriate to use in making decisions determining the recruitment of teachers than the profile matching method in Anbata TPQ. The difference is in the highest value in each method. In the profile matching method, the highest value is Salman Al Fariz with a value of 4.70 while in the SAW method the highest value is Ali Gufron with a value of 8,778., it can be concluded that the most appropriate method in determining the recruitment of teaching staff at TPQ Anbata is the Profile Matching Method.

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.

PT. LSP (Langkat Sawit Hijau Pratama) is a palm oil factory, where palm fruit or palm kernels are processed into palm oil (unfinished crude oil) which can be further processed into cooking oil, industrial oil or fuel. To get the best crude oil, superior and quality palm oil is needed, so a Decision Support System is needed in choosing suppliers to maintain good quality palm oil. A decision support system (DSS) in selecting suppliers is important because the right supplier can have a positive impact on company performance. Using a Decision Support System (DSS) with the Analytical Hierarchy Process (AHP) method in selecting suppliers can increase efficiency and effectiveness in decision making, as well as help companies choose the right suppliers and have the potential to have a positive impact on company performance. This research aims to determine the performance of the Analytical Hierarchy Process (AHP) in the Supplier selection Decision Support System and utilize the Decision Support System using the Analytical Hierarchy Process (AHP) method in making decisions as part of the consideration in choosing the right supplier. The results of this research show that by comparing decisions with the Saaty theory, priority weightings for each criterion and sub-criteria are obtained consistently or CR < 0.1. Price Criteria (0.0699), Capacity Criteria (0.2289), Quality Criteria (0.5081), Arrival Criteria (0.1932). Having obtained the final score, the best supplier has been determined using the Analytical Hierarchy Processes method, namely the BEST supplier with a total of 0.5870, and the last position is the TANI9 supplier with a total of 0.0958.

Selection of optimal coconut varieties for coconut milk production is a crucial step in the food industry, considering that the quality and quantity of coconut milk are greatly influenced by the type of coconut used. This study aims to determine the best coconut varieties for coconut milk production by integrating two multicriteria decision-making methods, namely the Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW). The AHP method is used to determine the weight of each influential criterion, such as oil content, taste, price, and availability. Meanwhile, the SAW method is applied to rank various coconut varieties based on the weight of the criteria that have been obtained. The data used in this study were collected from various sources, including scientific literature, as well as field observation data. The results of the analysis indicate that certain coconut varieties have significant advantages in terms of quality and efficiency of coconut milk production. The coconut varieties selected through the combined AHP and SAW methods are expected to provide practical guidance for coconut milk producers in selecting optimal coconut varieties, so that they can improve the quality of the coconut milk produced. Thus, this study provides an important contribution in the field of agribusiness, especially in the selection of coconut varieties for coconut milk production, as well as implementing the use of AHP and SAW methods in complex and multi-criteria decision making.

Selecting a landfill site is a difficult task because the process depends on many factors and restrictions. Landfill is an optimal solution for the disposal of solid waste in Al-Musayiab Qadhaa, which is located in the northern part of Babylon Governorate. At the moment, there is no landfill site in that area that follows the scientific selection site criteria. For this reason, in this research, fifteen variables were considered (groundwater depth, rivers, soil types; agriculture lands use, land use, elevation, slope, gas pipelines, oil pipelines, power lines, roads, railways, urban centers, villages and archeological sites) using geographic information system (GIS) to find out the best suitable landfill site. In addition, two methods of multi-criteria decision-making were used to derive weights for criterion’s maps on GIS to obtain potential landfill sites. The first method is analytical hierarchy process (AHP) which was used to identify the weight for each criterion from the matrix of pairwise comparisons. The second method was the simple additive weighting (SAW) which is a simple method to solve the problem of the selection landfill sites. After comparison of the results obtained based on combining two final maps resulted from methods of AHP and SAW using GIS environment to determine the pixels percentage of matching and non-matching for two maps, two suitable candidate landfill sites were identified that satisfy the requirements with an area of 7.965–5.952 km2. Area of these sites can accommodate the solid waste generated from the Qadhaa up to 2030.

Decision support systems can be used to help determine a decision. One of the methods used is the AHP (Analytical Hierarchy Process) method which is considered a flexible method and suitable for decision making. The purpose of this research is to see the use of the Analytical Hierarchy Process (AHP) method in a decision support system to assist a decision. This research method is literature study. The results of this research are that the AHP method in decision support systems can be used as a method of choice that can help determine decisions in various sectors of life.

In the field of services, customer satisfaction is a very important factor and determine the success of an enterprise. In the field of outsourcing, customer satisfaction indicator is the labor required delivery in a timely manner and has a level of quality in accordance with the terms proposed by the customer. To provide the best talent to customers, team recruitment and selection must perform a series of tests with a variety of methods to match the criteria of office given by the user with the criteria owned candidates and in order to support growth in graduation rates force a partner at the stage of user approval. For this purpose, the authors conducted a study with the method of observation, interviews, document reviews the candidate recruitment process, so as to provide recommendations for candidates with the highest quality delivery to the user at the stage of approval. The author put forward a model of decision support that is supported by the method of profile matching and Analytical Hierarchy Process (AHP) in problem solving. The final results of this study can be used to support a decision in order to improve the effectiveness of the delivery of quality candidates, increase customer satisfaction, lower costs and improve gross operational margin of the company.