JURNAL RISET INFORMATIKA Vol. 5, No. 3. June 2023 P-ISSN: 2656-1743 |E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i3.454 Accredited rank 4 (SINTA 4), excerpts from the decision of the DITJEN DIKTIRISTEK No. 230/E/KPT/2023 295 THE BEST EMPLOYEE DECISION SUPPORT SYSTEM USING THE ANALYTICAL HIERARCHY PROCESS METHOD AT PT ASDP INDONESIA FERRY (PERSERO) Deny Novianti-1, Anggi Oktaviani-2, Dahlia Sarkawi-3, Aldyanto-4, Ahmad Faren Syahidan-5 Sistem Informasi / Administrasi Perkantoran Universitas Bina Sarana Informatika Jakarta, Indonesia denynov.dov@bsi.ac.id, dahlia.dls@bsi.ac.id Informatika / Teknologi Informasi Universitas Nusamandiri Jakarta, Indonesia aldyanto1709@gmail.com, farensyahidan@gmail.com, anggi.aov@nusamandiri.ac.id (*) Corresponding Author Abstract Selecting the best employees aims to spur employee morale by improving performance and dedication. The selection of the best employees is selected based on company criteria. PT ASDP Indonesia Ferry (PERSERO) The best employee criteria applied by the company are Work Quantity, Work Quality, Attendance, Teamwork, and Initiative. Employee assessment is carried out every month by the assessment team (Vic e President (VP) and Manager). The problem faced is determining the best employees with criteria and alternatives that are calculated manually. This system is a Decision Support System (DSS) built using the Analytical Hierarchy Process (AHP) method. Previously, the evaluation process for selecting the best employees had never been done. Some of the problems encountered were the absence of an employee performance appraisal process, there was no appropriate selection method, and a Decision Support System (DSS) was not available that could make it easier to assess the selection of the best employees. Keywords: Best employees, Decision Support System, Analytical Hierarchy Process (AHP) Abstrak Pemilihan karyawan terbaik bertujuan untuk memacu semangat kerja karyawan dalam meningkatkan kinerja karyawan dan dedikasi di perusahaan tersebut. Pemilihan karyawan terbaik dipilih berdasarkan kriteria perusahaan. PT ASDP Indonesia Ferry (PERSERO) kriteria-kriteria karyawan terbaik yang diterapkan perusahaan adalah Kuantitas Kerja, Kualitas Kerja, Kehadiran, Kerjasama Tim, Inisiatif. Penilaian karyawan dilakukan pada setiap bulan oleh tim penilai yaitu Vice President (VP) dan Manager. Masalah yang dihadapi adalah bagaimana menentukan karyawan terbaik dengan kriteria dan alternatif yang dihitung secara manual. Sistem ini merupakan Sistem Pendukung Keputusan (SPK) yang dibangun dengan menggunakan metode Analitycal Hierarchi Process (AHP). Dimana sebelumnya proses evaluasi pemilihan karyawan terbaik belum pernah dilakukan. Beberapa permasalahan yang ditemui adalah tidak adanya proses penilaian kinerja karyawan, belum ada metode pemilihan yang tepat, dan belum tersedia Sistem Pendukung Keputusan (SPK) yang dapat mempermudah dalam menilai pemilihan karyawan terbaik. Kata kunci: Karyawan Terbaik, Sistem Pendukung Keputusan (SPK), Analytical Hierarchi Process (AHP) INTRODUCTION The presence of valuable human resources will likely be a significant supporting component in an organization's progress. With quality human resources, a company can do its job, proliferate and become famous. For this reason, it is essential to supervise human resources in a company by determining the best employees to increase employee determination in further developing their implementation, commitments, and tasks so that they become better and develop. To trigger employee performance, a company can choose the best workers every year by mailto:denynov.dov@bsi.ac.id mailto:dahlia.dls@bsi.ac.id mailto:aldyanto1709@gmail.com, mailto:aldyanto1709@gmail.com, mailto:anggi.aov@nusamandiri.ac.id P-ISSN: 2656-1743 | E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i3.454 JURNAL RISET INFORMATIKA Vol. 5, No. 3 June 2023 Accredited rank 4 (SINTA 4), excerpts from the decision of the DITJEN DIKTIRISTEK No. 230/E/KPT/2023 296 giving awards, prizes, and job promotions to selected workers. According to Mondy and Noe, employee performance appraisal includes behavior or attitudes, skills, discipline, attendance, knowledge, and goal achievement. For this situation, the author provides a new normalization or criteria for selecting the best employees: quantity of work, quality of work, teamwork, attendance, and initiative. Inappropriate dynamics will cause the selected workers not to match the actual reality, while the better-weighted workers are sometimes not selected. An agency needs to conduct an employee performance assessment to determine the success or non-success in carrying out its duties (Saefudin & Wahyuningsih, 2017). The determination of who becomes The Best Telesales has gone through various stages of the process from within the Telesales Team respectively and passed the assessment stage from the Management based on specific criteria set by (Septiani et al., 2019). The application created can be used by decision-makers while still based on a more effective decision support system in selecting the best customer (Taufik Kurnialensya & Rohmad Abidin, 2020). Decision Support System using Analytical Hierarchy Process (AHP) is a decision-making method for prioritizing various alternatives (Nur Ajny, 2020). Based on the system, not based on someone's choice with the system, will help the company determine the best manager so that it does not take sides with one of the parties and make the wrong choice (Aisyah & Putra, 2022). To help related parties more effectively select the communities in need and those affected so that they are right on target as expected by all communities in Sundawenang Village by accurate and relevant data (Sembiring et al., 2020). The concept of a decision support system can be applied as a tool to determine the ideal internet service provider as a wireless network in the home environment. One method that is relevant and has a calculation of consistency values in determining the priority level of criteria is the Analytical Hierarchy Process (AHP) method (M. I. H. Saputra & Nugraha, 2020). It is hoped that by using one of the methods in the decision support system, the calculation process by determining the predetermined criteria can provide output in the form of recommendations from the head of the PPA Kanit using the Sumarno1 Weight Product method (Sumarno & Harahap, 2020). Decision Support System (SPK) is a system aimed at supporting decision management and a computer-based system capable of solving unstructured problems. AHP is the most widely used method in solving multicriteria problems (R. H. Saputra et al., 2019). A decision support system (SPK) is an electoral system commonly used to determine choices according to predetermined criteria and alternatives (Fatullah et al., 2022). The decision-making of a problem, be it a simple or complex problem, requires thorough and accurate information, the ability to analyze and process information and the correct solution method (Djamain, 2015). The decision support system (SPK) is a system that can provide alternative solutions to these problems. The decision support system is currently developing with various methods, including the AHP (Analytical Hierarchy Process) method helping to make decisions (Hartanto & Prasetiyowati, 2012). The AHP method is a method used to assess actions that are associated with a comparison of the weight of importance between factors as well as a comparison of several alternative options. This method will provide weighting results of each choice according to many established criteria, namely price, location, and type. The choice with the most significant weight is a choice that is a recommendation to be chosen by consumers (Ardiyanto et al., 2013). Employee performance appraisals carried out by companies are generally only for assessing work performance, namely how work can be done well, achieve the targets set and achieve the desired end goal (hard skills). Assessments related to employees' soft skills have not been carried out much. Companies apply several criteria in conducting soft skill competency assessments, but the criteria still vary (Umar et al., 2018). Employee performance appraisal is essential to support the smooth running of the business. Selection of the best employees will increase the motivation of employee performance. Decision Support System (SPK) can make assessing the selection of the best employees easier, so an SPK application is needed to assess the best employee selection. The methods that can be used are the AHP method, the AHP Method produces alternative priorities and the weight of criteria in determining the best employees objectively based on the criteria given by the store owner as a decision maker who will provide bonus rewards for the best employees, the goal is to motivate employees in improving their performance (Fu’adi & Diana, 2022). PT ASDP Indonesia Ferry (Persero) It is one of the state-owned enterprises in Indonesia that participates in the operation of ferry transportation services and administration of the ferry port for passengers, vehicles, and merchandise. The primary capability of this JURNAL RISET INFORMATIKA Vol. 5, No. 3. June 2023 P-ISSN: 2656-1743 |E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i3.454 Accredited rank 4 (SINTA 4), excerpts from the decision of the DITJEN DIKTIRISTEK No. 230/E/KPT/2023 297 company is to provide public transportation permits between adjoining regions and unite the big islands while simultaneously providing public transportation access to areas that do not yet have crossings to accelerate development (pioneer crossings). To develop employee performance, you have to choose the best workers so that they can compete with each other to be on top. Some companies give grants to the best workers with the best capacities among different workers. Therefore, the researcher wants to create a framework that recognizes the best PT ASDP Indonesia Ferry (PERSERO) workers who will be awarded later. This is expected to increase the spirit of representatives in their work, especially in providing the best assistance to consumers. The framework that will be built is a decision support network, or DSS, using the Analytical Hierarchy Process (AHP) method. One of the techniques in decision support is the Analytical Hierarchy Process (AHP) technique, which is a strategy to determine the demand for work needs. Several studies on decision support systems (DSS) developed using the Analytical Hierarchy Process (AHP) method include applying the AHP and SAW methods for determining employee promotions. The criteria for selecting decision-making tools are skill, teamwork, discipline, and loyalty. Judging from each focus above, the importance of choosing a network that supports decisions in choosing the best talent for workers at PT. ASDP INDONESIA FERRY (PERSERO) and its impact can further develop employee performance and morale and influence organizations and associations. This affects the efficiency and improvement of workers. However, it is difficult for the higher-ups to decide just like that. Several considerations need further consideration before selecting the best worker. Whether it's a non-complex problem or a complex problem, concluding a problem requires accurate and precise data so that it can have much insight that is suitable to be the primary concern. With the advancement of information technology innovation, including equipment and programming, different effects have been traced on various aspects of human life. One of them is the emergence of a dynamic model called decision-making. The Decision Support System (DSS) can dash effectively and successfully. The data that is monitored by the system must provide accurate, fast, coordinated and precise data through computerized data processing. On this basis, the researcher sets the title. RESEARCH METHODS This research will be implemented in the Analytical Hierarchy Process (AHP) method as the Best Employee Decision Support System at PT ASDP Indonesia Ferry (PERSERO). Figure 1. Flowchart AHP Procedure or steps in the AHP method (Tonni et al., 2020): 1. Defining problems, determining solutions, and compiling a hierarchy of problems encountered. Figure 2 Problem Definition Example 2. Determine the priority by creating a pairwise comparison matrix and representing the relative importance of the elements. Table 1 Criteria Comparison Format Kriteria 1 Kriteria 2 Kriteria 3 Kriteria 4 Kriteria 1 K11 K12 K13 K1n Kriteria 2 K21 K22 K23 K2n Kriteria 3 K31 K32 K33 K3n Kriteria 4 Kn1 Kn2 Kn3 Knn P-ISSN: 2656-1743 | E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i3.454 JURNAL RISET INFORMATIKA Vol. 5, No. 3 June 2023 Accredited rank 4 (SINTA 4), excerpts from the decision of the DITJEN DIKTIRISTEK No. 230/E/KPT/2023 298 3. Synthesis, which considers comparing pairs to obtaining priority, is done: Divide each value from the column by the corresponding column total to obtain a normalized matrix. Add up the values of each row and divide by the number of elements to get the average value. 4. Determine consistency. In making decisions, the level of consistency is essential to note because we do not want decisions based on considerations with low consistency, with a maximum value of consistency ratio (CR) of = 0.1 or 10%. The things that are done in this step are: Multiply each value in the first column by the relative priority of the first element, the value in the second element by the relative priority of the second element, and so on. Total each row. The result of the row sum is divided by the corresponding relative priority element. Add up the quotient above with the number of elements whose result is called I max. 5. Calculating the consistency ratio (CR) with the formula CR = CI/IR, where CR = Consistency Ratio, CI = Consistency Index, IR = Random Consistency Index. 6. The consistency index (CI) is calculated using the formula. 𝐶𝐼 = 𝜆𝑚𝑎𝑥−𝑛 𝑛−1 ................................................................. (1) where n is the number of elements. 7. Examining Table 3's Random Consistency Index. Table 3 The Random Consistency Index n 1 2 3 4 5 6 7 8 9 10 IR 0 0 0,6 0,9 1,1 1,2 1,3 1,4 1,4 1,5 n 11 12 13 14 15 16 17 18 19 20 IR 1,5 1,5 1,6 1,6 1,6 1,6 1,6 1,6 1,6 1,6 Time and Place of Research This research was conducted at the head office of PT ASDP Indonesia Ferry (PERSERO). Gedung Kelapa Gading Trade Center, Jl. Boulevard Bar. Raya, RT.2/RW.9, Klp. Gading Bar, Kec. Klp. Gading, Kota Jkt Utara, Daerah Khusus Ibukota Jakarta 14240. The time of data collection and research used by researchers starts in May 2022. Sum the values of each column in the matrix. Research Target or Subject The objectives of this research are as follows: It is developing criteria for the Analytical Hierarchy Process (AHP) method of selecting the best employees for awards. Provide optimal and precise results in determining the best employees at PT. ASDP Indonesia Ferry (PERSERO) with the Analytical Hierarchy Process (AHP) method in a decision support system. Make it easier for PT. ASDP Indonesia Ferry (PERSERO) to find the best employees by using the Analytical Hierarchy Process (AHP) method in a decision support system. RESULTS AND DISCUSSION Recommended System Analysis The datasets needed in this study are primary and secondary data. The primary data used is data or information about employees at PT ASDP Indonesia Ferry (PERSERO), or flow data regarding selecting the best employees and data relating to the selection process for selecting the best employees. While secondary data is data obtained from books, journals, and the internet that supports research. At this stage, the analysis of the proposed system aims to produce a computerized employee selection system. The proposed system is to change the manual system into a computerized system in processing data to display new employees with the highest and lowest scores. The proposed system analysis includes UML: The use case diagram, Activity diagram, and Class diagram. Selecting the Best Employee An overview before the decision-making system for selecting the best employees was carried out by DBD was that every activity of selecting the best employees was still conducted manually, and there was still an element of subjectivity from one party only so that all data on the best prospective employees did not have a fixed weight. Mistakes often occurred, so prospective employees who did not meet the standards passed the selection process for selecting the best employees. Likewise, the data storage place for the best prospective employees is not automatically stored in the system; it is still manual, so that it can pose a significant risk regarding personal data or information related to prospective employees. Overview of the Proposed System The general picture is that the user, as DHF, will choose and enter a weight value for each criterion according to the user's level of interest. The criteria are discipline, teamwork, skills, loyalty, JURNAL RISET INFORMATIKA Vol. 5, No. 3. June 2023 P-ISSN: 2656-1743 |E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i3.454 Accredited rank 4 (SINTA 4), excerpts from the decision of the DITJEN DIKTIRISTEK No. 230/E/KPT/2023 299 and tenure. After the user enters the weight value and presses the process button, the system will calculate it using the Analytical Hierarchy Process (AHP) method. The system will display the alternative with the highest value that dominates the other values. Analytical Hierarchy Process (AHP) I compared data between criteria and alternatives in a paired matrix using the AHP importance intensity scale. This process is carried out to determine the value of the consistency ratio comparison (also known as the consistency ratio or CR). The consistency requirement must be less than 10% or CR<0.1. Before comparing paired matrices between criteria and alternatives, determine the intensity of interest for each criterion and alternative. Determining the intensity of importance of each criterion and alternative is to avoid CR > 0.1 or inconsistency. The weakness of a manager when inputting comparison values between criteria into a paired matrix is that the input comparison values are often inconsistent. Therefore, the intensity of the importance of each criterion and alternative is determined— the value of the intensity of interest given by the manager of PT. ASDP Indonesia Ferry (PERSERO) for each criterion and alternative is in the range of values from 1 to 9. The range of values from 1 to 9 is related to the comparison value developed by Saaty. Hierarchical Structure Representation After input (criteria data and alternatives), the representation is carried out in a hierarchical structure. The problems that must be formulated in building a hierarchical structure are identifying goals (goals), criteria, and alternatives (employees) that are assessed. The hierarchical structure of the best employee problem formulation can be seen in the image below. Figure 3 A Hierarchical Structure For Selecting The Best Employees Identification of goals becomes the most critical decision in a case. The goal to be achieved in this thesis is the selection of the best employees. Identifying the best employee selection criteria can be initialized with the symbol K. The best employee criteria are summarized in Table 4 below. Table 4 Criteria For Selecting The Best Employees No. Criteria Initials Criteria Name 1 K1 Working Quantity 2 K2 Work Quality 3 K3 Teamwork 4 K4 Presence 5 K5 initiative The alternative identification stage is to identify the employee as the object of assessment who is chosen to be the best employee. This thesis research takes an alternative sample of three employees, as shown in Table 5 below. Table 5 Best Employee Candidate No. Alternative Alternatif Name 1. A1 Diah 2. A2 Ayu 3. A3 Viona Comparison of Criteria in the Analytical Hierarchy Process (AHP) Method This method has weights and several criteria needed to determine the best employees. The specified criteria are Working quantity, Quality of work, Teamwork, Presence, and Initiative. The above criteria are initialized with the symbol K, as seen in Table 4. From each of these criteria, the weight of each criterion will be determined to determine the intensity of interest in each criterion. The function of determining the intensity of importance of each criterion is to avoid CR > 0.1 or inconsistency. The value of the intensity of interest given by the manager or lead team project member for each criterion ranges from 1 to 9. The range of values from 1 to 9 relates to the comparison value developed by Saaty. Based on the assessment obtained from the questionnaire that we submitted to the project manager or lead team member regarding the weighting of the intensity of interest of each criterion or comparison of criteria, it can be seen in Table 6 below. P-ISSN: 2656-1743 | E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i3.454 JURNAL RISET INFORMATIKA Vol. 5, No. 3 June 2023 Accredited rank 4 (SINTA 4), excerpts from the decision of the DITJEN DIKTIRISTEK No. 230/E/KPT/2023 300 Table 6 Assessment Obtained From The Questionnaire No. Comparison of Criteria Value 1. Working Quantity Quality of work √ 5 2. Working Quantity Teamwork √ 9 3. Work Quantity Presence √ 3 4. Work Quantity Initiative √ 9 5. Quality of work √ Teamwork 6 6. Quality of work √ Presence 5 7. Work Quality Initiative √ 4 8. Teamwork Presence √ 3 9. Teamwork √ initiative 5 10. Presence Initiative √ 3 The existence of the value of the intensity of the importance of the criteria (table 6) can be directly concluded from the AHP pairwise comparison matrix between each criterion. So, managers no longer need to compare one by one the value of the intensity of interest between criteria. The comparison of the paired matrix of the AHP criteria can be seen in Table 7 below. Table 7 AHP Criteria Pairwise Comparison Matrix Criteria K1 K2 K3 K4 K5 K1 1 1/5 1/9 1/3 1/9 K2 5 1 6 5 ¼ K3 9 1/6 1 1/3 5 K4 3 1/5 3 1 1/3 K5 9 4 0,2 3 1 Information: : Lower triangular matrix comparison value : The comparison value of the upper triangular matrix (a mirror or reciprocal of the lower triangle value) The results in Table 7 that the comparison value for himself (K1 to K1, K2 to K2, K3 to K3, and K4 to K4, K5 to K5) is 1, which means the intensity of interest is the same. The comparison of K1 with K2 is worth it. It can be explained that K2 is more important than K1. The comparison of K1 with K3 with a value of 9 can be explained by the fact that K3 is an absolute element rather than a K1 element. The comparison of K1 with K4 with a value of 3 can be explained by the fact that K4 is slightly more critical than K1. The comparison of K1 with K5 is worthwhile. It can be explained that K5 is an absolute element more than K1. Comparison of Alternatives on Quantity of Work The value of the intensity of interest given by the manager or lead team project member to each alternative is in the range of values from 1 to 9 relates to the comparison value developed by Saaty. Based on the assessment obtained from the questionnaire that we submitted to the project manager or lead team member regarding the weighting of the intensity of interest of each alternative or the comparison of alternatives, it can be seen in Table 10. Table 10 Alternative Comparison Value On Criteria No. Alternative comparison => Working Quantity Value 1 Mrs. A √ Mrs.B 2 2 Mrs. A √ Mrs. C 3 3 Mrs. B √ Mrs. C 2 The existence of alternative interest intensity values (table 10) can be directly concluded with AHP pairwise comparison alternatives between each alternative so that managers no longer need to compare the interest intensity values between alternatives individually. In Table 11, the AHP alternative paired matrix comparison can be seen. Table 11 Alternative Work Quantity Comparison Matrix Working Quantity A1 A2 A3 A1 1 2 3 A2 0,5 1 2 A3 0,3333333333 0,5 1 The results in Table 11 that the comparison value for itself (A1 to A1, A2 to A2, A3 to A3) is 1, which means the intensity of importance is the same. A1 is worth nearly the same as A2 but cannot be considered better than A2. The comparison of A1 with A3 with a value of 3 can be explained by A3 being better than A1. A comparison of A2 with A3 is worth 2 points, almost the same as A3, but cannot be considered better than A2. Before calculating the priority weight value, the comparison value in each column cell is shown in Table 12 below. Table 12 The Sum Of Each Column Of Comparison Values Working Quantity A1 A2 A3 A1 1 2 3 A2 0,5 1 2 A3 0,3333333333 0,5 1 Jumlah 1,833333333 3,5 6 JURNAL RISET INFORMATIKA Vol. 5, No. 3. June 2023 P-ISSN: 2656-1743 |E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i3.454 Accredited rank 4 (SINTA 4), excerpts from the decision of the DITJEN DIKTIRISTEK No. 230/E/KPT/2023 301 Calculating the priority weight value is dividing each cell by the number in its column. Column K1 =0.545 Column K2 = 0.571, and so on After the results of the division of each column are obtained, the eigenvector value or priority weight can be calculated (seen in Table 13). The priority weight value is the average value by adding up the values from each row and dividing them by the many criteria elements, and if they are added up, they will be worth one. Table 13 Priority Weight Value Alternative Eigen Value Sum Average 0,5454545 0,5714286 0,5 1,6168831 0,538961 0,2727273 0,2857143 0,3333333 0,8917749 0,2972583 0,1818182 0,1428571 0,1666667 0,491342 0,1637807 Sum 1 After obtaining the alternative priority weights, the maximum land value (λmax), or eigenvalue, is calculated, the sum of multiplying the priority weights with the number of columns. CR = 0.0015/0.58 = 0.0025 (consistent because it meets the requirements of CR 0.1) And so on, until the initiative's alternatives are compared. System Implementation Based on the analysis and system design results, the best employee selection system is implemented by applying the Analytical Hierarchy Process method. Results Analysis This web-based system is designed specifically for users to provide recommendations for the best employment decisions based on the criteria applied at PT. ASDP Indonesia Ferry (PERSERO). The system has a main menu equipped with the AHP method to assist the calculation process and produce recommendations for the best employee decisions. a. Attendance Pairwise Comparison Matrix Figure 7 Attendance Pairwise Comparison Matrix Figure 7 displays the pairwise comparison matrix: Mrs. A is 4.33333, Mrs. B is 1.53333, and Mrs. C is 9. Produces a Matrix Criteria value including 1) Principle Eigen Vector (max) of 3.05536, Consistency index of 0.02768, and Consistency Ratio of 4.77% b. Calculation Results and Ranking The system will display the best employee calculation menu, which displays calculations according to the desired month and year. If the month and year have been selected, the system will display the AHP ranking menu, as shown in Figure 10 below. Figure 10 Menu Display Of AHP Calculation Results and Ranking The AHP ranking menu display has several menu tabs that detail the AHP process on criteria, alternatives, and decision results in the form of a ranking. On the ranking menu tab, a list of the best employee recommendations is displayed that can be used as a consideration for managers in determining the best employee decisions. CONCLUSIONS AND SUGGESTIONS Conclusion By making a decision support system for the best employees, it can assist leaders in making decisions to determine the best employees according to the existing criteria and using the Analytical Hierarchy Process (AHP) method, namely: The Management has determined the criteria used in the decision support system for selecting the best employees: work quantity, work quality, teamwork, attendance, and initiative. The decision weight of the best employee using the AHP method is close to the weight of the manual calculation decision used at PT. ASDP Indonesia Ferry (PERSERO). There is an intensity value for each criterion and alternative from the company. The manager does not have to input the value of the paired matrix comparison because the system will operate automatically so that the comparison value is consistent (CR 0.1). P-ISSN: 2656-1743 | E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i3.454 JURNAL RISET INFORMATIKA Vol. 5, No. 3 June 2023 Accredited rank 4 (SINTA 4), excerpts from the decision of the DITJEN DIKTIRISTEK No. 230/E/KPT/2023 302 Suggestion From the research conducted, valuable suggestions can be generated for system development, such as adding other methods to complement the shortcomings of AHP. REFERENCES Aisyah, N., & Putra, A. S. (2022). Sistem Pendukung Keputusan Rekomendasi Pemilihan Manajer Terbaik Menggunakan Metode AHP (Analytic Hierarchy Process). Jurnal Esensi Infokom : Jurnal Esensi Sistem Informasi Dan Sistem Komputer, 5(2), 7–13. https://doi.org/10.55886/infokom.v5i2.275 Ardiyanto, H., Sasongko, P. S., & Adhy, S. (2013). Sistem Pendukung Keputusan Pemilihan Perumahan Menggunakan Metode Ahp Berbasis Web (Studi Kasus CV. Wisma Anungkriya Demak). JOINT, 2(3), 50–58. Djamain, Y. (2015). Berbasis Web Untuk Menentukan Penjurusan Pada Sma X Dengan Menggunakan Metode Ahp ( Analytical Hierarchy Process ). Jurnal PETIR, 8(2), 197. Fatullah, R., Hasanah, H., & Rizky, D. (2022). Sistem Pendukung Keputusan Pemilihan Jurusan Kuliah dengan Metode Analytical Hierarchy Process (AHP) Berbasis Web pada SMAN 1 Kramatwatu. Smart Comp: Jurnalnya Orang Pintar Komputer, 11(1), 37–43. https://doi.org/10.30591/smartcomp.v11i1. 3096 Fu’adi, M. I., & Diana, A. (2022). Sistem Pendukung Keputusan Menggunakan Metode Analytical Hierarchy Process (Ahp) Untuk Pemilihan Karyawan Terbaik Pada Toko Sepatu Saman Shoes. RADIAL : Jurnal Peradaban Sains, Rekayasa Dan Teknologi, 9(2), 265–280. https://doi.org/10.37971/radial.v9i2.243 Hartanto, T., & Prasetiyowati, M. I. (2012). Sistem Pendukung Keputusan Pemilihan Laptop Berbasis Web dengan Metode Analytical Hierarchy Process. Jurnal ULTIMATICS, 4(2), 7–15. https://doi.org/10.31937/ti.v4i2.314 Nur Ajny, A. (2020). Sistem Pendukung Keputusan Pemilihan Lipstik Dengan Analytical Hierracy Process. Jurnal Riset Sistem Informasi Dan Teknologi Informasi (JURSISTEKNI), 2(3), 1– 13. https://doi.org/10.52005/jursistekni.v2i3.5 9 Saefudin, S., & Wahyuningsih, S. (2017). Sistem Pendukung Keputusan Untuk Penilaian Kinerja Pegawai Menggunakan Metode Analytical Hierarchy Process (Ahp) Pada RSUD Serang. JSiI (Jurnal Sistem Informasi), 1(1), 33–37. https://doi.org/10.30656/jsii.v1i0.78 Saputra, M. I. H., & Nugraha, N. (2020). Sistem Pendukung Keputusan Dengan Metode Analytical Hierarchy Process (Ahp) (Studi Kasus: Penentuan Internet Service Provider Di Lingkungan Jaringan Rumah). Jurnal Ilmiah Teknologi Dan Rekayasa, 25(3), 199–212. https://doi.org/10.35760/tr.2020.v25i3.342 2 Saputra, R. H., Novitasari, D., Waziana, W., & Kridianto, R. (2019). Sistem Pendukung Keputusan Pemilihan Guru Terbaik Berbasis WEB Menggunakan Metode AHP Pada SMK Negeri 1 TALANGPADANG. Jurnal Ilmiah Nasional Riset Aplikasi Dan Teknik Informatika, 01(02), 39–46. https://naratif.sttbandung.ac.id/index.php/n aratif/article/view/67 Sembiring, F., Fauzi, M. T., Khalifah, S., Khotimah, A. K., & Rubiati, Y. (2020). Sistem Pendukung Keputusan Penerima Bantuan Covid 19 menggunakan Metode Simple Additive Weighting (SAW) (Studi Kasus : Desa Sundawenang). Explore:Jurnal Sistem Informasi Dan Telematika, 11(2), 97. https://doi.org/10.36448/jsit.v11i2.1563 Septiani, M., Afni, N., & Andharsaputri, R. L. (2019). Perancangan Sistem Informasi Penyewaan Alat Berat. JUSIM (Jurnal Sistem Informasi Musirawas), 4(02), 127–135. https://doi.org/10.32767/jusim.v4i02.639 Sumarno, S. M., & Harahap, J. M. (2020). Sistem Pendukung Keputusan Dalam Menentukan Pemilihan Posisi Kepala Unit (Kanit) Ppa Dengan Metode Weight Product. JUST IT : Jurnal Sistem Informasi, Teknologi Informasi Dan Komputer, 11(1), 37. https://doi.org/10.24853/justit.11.1.37-44 Taufik Kurnialensya, & Rohmad Abidin. (2020). 135-Article Text-311-1-10-20200609. Sistem Pendukung Keputusan Pelangganterbaik Dan Pemberian Diskon Menggunakanmetode Saw & Topsis, 13(1), 18–33. Umar, R., Fadlil, A., & Yuminah, Y. (2018). Sistem Pendukung Keputusan dengan Metode AHP untuk Penilaian Kompetensi Soft Skill Karyawan. Khazanah Informatika : Jurnal Ilmu Komputer Dan Informatika, 4(1), 27–34. https://doi.org/10.23917/khif.v4i1.5978