JURNAL RISET INFORMATIKA Vol. 5, No. 1. December 2022 P-ISSN: 2656-1743 |E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i1.472 Accredited rank 3 (SINTA 3), excerpts from the decision of the Minister of RISTEK-BRIN No. 200/M/KPT/2020 507 THE IMPLEMENTATION OF MOORA METHODS TO SUPPORT REFINEMENT DECISION PRIORITY SYSTEM IN INFORMATION TECHNOLOGY Fanni Rahmah Tsani-1*), Umi Chotijah-2 Teknik Informatika Universitas Muhammadiyah Gresik Kabupaten Gresik, Indonesia https://umg.ac.id/ fanirahmatsani039@gmail.com-1*), umi.chotijah@umg.ac.id-2 (*) Corresponding Author Abstract Maintenance of information and communications technology scoped on the Lamongan Regency Government is the responsibility of the Lamongan Regency Communications and Information Department. The application of information technology is closely related to the problems that appear, such as Communication Network Interruption/Damage. In this case, the report is provided by the user via WhatsApp message, and no single point of contact is used for delivery, retard the refinement process and making it difficult for technicians to prioritize refinement. In this study, the authors built a decision- supporting in order to assist technicians in making priority refinement. The Multi-Objective Optimization Based Ratio Analysis (MOORA) method is the appropriate method to apply for this study as it allows us to perform the ranking process based on different weighting attributes. The calculation process of the MOORA method is based on specified criteria and weightings. Criteria are the type of damage, risk of a complaint, duration of the claim, and type of service. In one day, the three regional apparatuses with the highest scores are selected and recommendations for prioritized refinement are provided. In this study, we found that samples with high criterion weights and high criterion scores tended to be prioritized over other samples. The results MOORA calculated show the library service to be the best alternative with a value of 0.396 on ten regional apparatus tested. Keywords: Decision Support System; Repair Priority; Multi-Objective Optimization based on Ratio Analysis (MOORA); Information Technology Abstrak Pemeliharaan teknologi informasi dan komunikasi dilingkup Pemerintahan Kabupaten Lamongan merupakan tanggung jawab Dinas Komunikasi dan Informatika Kabupaten Lamongan. Penerapan teknologi informasi tidak terlepas dari permasalahan yang timbul seperti adanya gangguan/kerusakan jaringan komunikasi. Dalam hal ini teknisi kesulitan dalam menentukan prioritas perbaikan dikarenakan pelaporan yang diberikan pengguna melalui pesan whattsapp dan tidak digunakan kontak tunggal dalam penyampaiannya, sehingga memperlambat proses penyelesaian perbaikan. Pada penelitian ini, penulis membangun suatu sistem pendukung keputusan yang bertujuan untuk membantu teknisi dalam menghasilkan suatu keputusan prioritas perbaikan. Metode Multi-Objective Optimization Based Ratio Analysis (MOORA) adalah metode yang tepat diterapkan pada penelitian ini karena mampu melakukan proses perangkingan berdasarkan atribut bobot yang berbeda. Proses perhitungan metode MOORA berdasakan kriteria dan bobot yang telah ditentukan. Kriteria penilaian yang digunakan adalah jenis kerusakan, resiko komplain, lama permintaan, dan jenis pelayanan. Dalam satu hari akan dipilih tiga perangkat daerah dengan nilai tertinggi untuk dilakukan rekomendasi prioritas perbaikan. Dalam penelitian ini ditemukan bahwa sample dengan nilai kriteria yang tinggi dengan bobot kriteria yang tinggi cenderung mendapatkan prioritas yang lebih dibandingkan sample yang lain. Hasil perhitungan MOORA menunjukkan Dinas Perpustakaan sebagai alternative tertinggi dengan nilai 0,396 pada sepuluh perangkat daerah yang diuji coba. Kata kunci: Sistem Pendukung Keputusan; Prioritas Perbaikan; Multi-Objective Optimization based on Ratio Analysis (MOORA); Teknologi Informasi P-ISSN: 2656-1743 | E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i1.472 JURNAL RISET INFORMATIKA Vol. 5, No. 1. December 2022 Accredited rank 3 (SINTA 3), excerpts from the decision of the Minister of RISTEK-BRIN No. 200/M/KPT/2020 508 INTRODUCTION Communication and Informatics Department of Lamongan Regency, is the regional apparatus which responsible for the maintenance of information and communication technology device for all regional apparatus that use communication networks and data exchange in carrying out their duties. The application of information technology cannot be separated from the problems that arise from disruption to information technology service resulting in service interruptions that could be affecting the performance of Lamongan Regency Government. When performing their duties, technicians have faced problems in determining the priority of each issue in regional apparatus. furthermore, repair requests are not handled by a single contact person. Therefore, it makes the data collection unorganized and slowing down response time (Santoso, Wijaya, & Nugraha, 2019). to fulfill that needs, a decision support system is recommended to assist decision maker for prioritizing requests from the regional apparatus. A decision support system is defined as a computerized system that used to facilitate decision making (Risykiyana, Rosyid, Chotijah, & Marโ€™i, 2022). Using a decision support system helps user make decisions (Yunus & Senung, 2021). Currently, the Lamongan Department Communications and Information Department needs an effective and efficient decision support system to expedite repairs. This study uses one of the Multi-Criteria Decision Making (MCDM) methods, namely the Multi-Objective Optimization based on Ratio Analysis (MOORA) with the consideration of being able to carry out the process simultaneously optimizing two or more conflicting attributes (Maharrani & Somantri, 2020) Where the attributes can be profitable (benefit) or unprofitable (cost) (Fadli & Imtihan, 2019) and can provide a better alternative assessment than other methods and carry out an easy and fast ranking process (Pane & Erwansyah, 2020). Several studies applying the MOORA method were conducted in PT. Indonesia Comnets Plus SBU Regional Sumbagsel that determining the level of urgency to improve the damaged towers is still being done manually. to determine the severe damage using MOORA (Abdurrasyid, Nugroho, Dakhlan, Arman, & Mahayana, 2022), the same thing is applied to the priority of selecting tower construction areas because the high cost of building a tower is the reason for providers to be selective and right on target in determining the location of tower construction using the AHP method and MOORA (Pane & Erwansyah, 2020). From several studies that have been carried out, the data used is data that no longer has been updated, so the data cannot experience re-versioning of the running time series. This research provides objective, fast, and transparent input or recommendations in determining priorities for improving information technology so that the decisions to be taken will be effective and appropriate (Pane & Erwansyah, 2020). RESEARCH METHODS Types of research This research belongs to qualitative research. Time and Place of Research This research was carried out from March 2022 to April 2022. The research was carried out at the Lamongan Regency Communication and Informatics Department in the Informatics Application Field, which is located on Jalan KH. Ahmad Dahlan, Lamongan Regency. Research Target / Subject This research targeted the efficiency of decision priority making. Procedure 1. Identification of Problem Often technicians have difficulty in determining refinement priorities due to the reporting that users provide via WhatsApp messages and not using a single contact in their delivery, thus slowing down the refinement completion process. In this study, the authors built a decision support system that aims to assist technicians in making a priority refinement decision. The Multi- Objective Optimization based on Ratio Analysis (MOORA) method is the right method to be applied to this study because it is able to carry out a ranking process based on different weight attributes so that the improvement priority results obtained are optimally and appropriate. 2. Data, Instruments, and Data Collection Techniques This study used repair submission data from regional apparatus at the Lamongan District Communication and Information Department. In one day, 3 local officials will be selected for repairs. Priority improvement activities need to be carried JURNAL RISET INFORMATIKA Vol. 5, No. 1. December 2022 P-ISSN: 2656-1743 |E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i1.472 Accredited rank 3 (SINTA 3), excerpts from the decision of the Minister of RISTEK-BRIN No. 200/M/KPT/2020 509 out within regional apparatus so that decisions to be taken are more effective and optimal. The criteria used in carrying out priority repairs are the type of damage, the risk of complaints, the length of request, and the type of service. The followings are the techniques used for data collection: a) Field Research The research was carried out by direct observation of the problem to be studied and taking the data needed for research at the Lamongan Regency Communication and Information Service. b) Literature Research Previous research related to journal topics and used as a reference source. Research conducted by (Abdurrasyid et al., 2022) at PT. Indonesia Comnets Plus SBU Regional Sumbagsel determines the level of urgency of repairs in towers using the MOORA method with 100% accuracy results, the same is also applied (Pane & Erwansyah, 2020) by applying the AHP and MOORA methods as determining the weight of the criteria and the best alternative to be selected in the selection of tower construction sites that have a level of accuracy at the seven locations tested. Other research was also conducted by (Akmaludin, Sihombing, Dewi, Rinawati, & Arisawati, 2021) testing conducted with the MOORA method in collaboration with the Price-Quality Ratio approach, the results obtained were the selection of object- based software applications. which can be done optimally and provide efficiency in the benefits and costs incurred. From the many studies used as reference sources, no decision support system has been found using versioning-type data. 3. Data Processing From filling out the repair form, the following sample data is obtained: Table 1. the repair data Regional apparatus Type of damage The risk of complain Demand Hour Type of services Kec. Maduran Local network Level 2 1 day Public services Kec. Sekaran Local network Level2 10 minute Public services Gedung PKK Internet network Level 5 >24 our Management Kec. Pucuk Software Level 2 2 our Public services Kec. Brondong Hardware Level 2 1,5 our Public services Bakesbangpol Internet network Level 4 24 our Management Gedung DPRD Internet network Level 3 1 our Management Dinas perpustakaan Local network Level 1 12 our Public services Dispora Internet network Level 3 1 our Management Inspektorat PC Level 3 4 our Management 4. Data Analysis The Multi-Objective Optimization method based on Ratio Analysis (MOORA) is an algorithm that optimizes two or more conflicting attributes simultaneously (Sunardi, Fadlil, & Fitrian Pahlevi, 2021) as well as a method used to optimize the ranking of a number of alternatives with several stages based on ratio analysis (Akmaludin, Sihombing, Dewi, Rinawati, & Arisawati, 2021). The first algorithm is to input the value of the criteria where the value of the criteria in an alternative is the value that will later be processed and the result becomes a decision. The criteria values are then converted into a decision matrix that defines the rows of data. The form of the matrix in question can be seen in equation 1. ๐‘‹ = ๐‘ฅ๐‘–๐‘— = [ ๐‘ฅ๐‘–๐‘— โ‹ฏ ๐‘ฅ๐‘–๐‘› โ‹ฎ โ‹ฎ โ‹ฎ ๐‘ฅ๐‘š1 โ‹ฏ ๐‘ฅ๐‘š๐‘› ] ............................................... (1) In this equation, the data takes the form of rows and columns. In equation (1) 'i' represents the number of rows and 'j' represents the number of columns. 'm' is the alternative and the 'n' is the number of attributes. The next process is normalization in the MOORA algorithm to unite each element of the matrix so that the elements on the matrix have a uniform value. Normalization of the matrix can be seen in equation 2. ๐‘‹๐‘–๐‘— โˆ— = ๐‘ฅ โˆšโˆ‘ ๐‘ฅ๐‘–๐‘— 2โˆ— ๐‘–=1 ...................................................................... (2) P-ISSN: 2656-1743 | E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i1.472 JURNAL RISET INFORMATIKA Vol. 5, No. 1. December 2022 Accredited rank 3 (SINTA 3), excerpts from the decision of the Minister of RISTEK-BRIN No. 200/M/KPT/2020 510 Equation (2) is obtained by dividing alternative values by square roots and alternate quadratic quantities The normalization that has been carried out is then continued by reducing the values of max and min-max to indicate that an attribute is more important multiplied by the corresponding weight, as depicted in equation 3. ๐‘Œ๐‘– โˆ— = โˆ‘ ๐‘ค๐‘—๐‘‹๐‘–๐‘— โˆ—๐‘” ๐‘—=1 โˆ’โˆ‘ ๐‘ค๐‘—๐‘‹๐‘–๐‘— โˆ—๐‘› ๐‘—=๐‘”+1 .................................. (3) Equation (3) aims the summary of benefit attribute 'j' to 'g' and then reduces the cost attribute iteratively 'g+1' until 'n' for each alternative 'i'. Yi is the preference value and W is the weight. The final value of the calculation uses equation 3 to determine the ranking of the MOORA calculation results with the highest ranking value being the highest preference value. RESULTS AND DISCUSSION In determining the selection of priorities for information technology improvements, a method was needed to assist in the determination of the regional apparatus whose damage was repaired, a decision support system was needed to find out which regional apparatus was prioritized for repairs. The method used in the improvement priority is the Multi-Objective Optimization based on Ratio Analysis (MOORA) method. The algorithm to be used in the process of prioritizing information technology improvements can be seen in Figure 1. Figure 1. Pseudocode calculation MOORA The process of calculating the MOORA method began by giving weight to each criterion, then a suitability rating was generated to form a decision matrix and carried out normalization of the decision matrix. After normalization, attribute optimization was performed by including weights. Benefit optimization value (max) minus cost optimization value (min). The biggest optimization result showed that the alternative was prioritized. In the MOORA method, there were criteria as an assessment process to determine priority improvements. The criteria used in the repair priority were the type of damage (C1), the risk of complaints (C2), the time of request (C3), and the type of service (C4). The alternative selection is shown in table 2. JURNAL RISET INFORMATIKA Vol. 5, No. 1. December 2022 P-ISSN: 2656-1743 |E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i1.472 Accredited rank 3 (SINTA 3), excerpts from the decision of the Minister of RISTEK-BRIN No. 200/M/KPT/2020 511 Table 2. Alternative selection Alternative Criteria C1 C2 C3 C4 Kec. Maduran Local network Level 2 1 day Public services Kec. Sekaran Local network Level2 10 minute Public services Alternative Criteria C1 C2 C3 C4 Gedung PKK Internet network Level 5 >24 our Management Kec. Pucuk Software Level 2 2 our Public services Kec. Brondong Hardware Level 2 1,5 our Public services Bakesbangpol Internet network Level 4 24 our Management Gedung DPRD Internet network Level 3 1 our Management Dinas perpustakaan Local network Level 1 12 our Public services Dispora Internet network Level 3 1 our Management Inspektorat PC Level 3 4 our Management Furthermore, the determination of criteria and weights in accordance with predetermined qualifications is indicated in Table 3. Table 3. criteria and quality Criteria Description Quality Type C1 Type of damage 0,14 Benefit C2 The risk of complain 0,29 Benefit C3 Demand Hour 0,21 Benefit C4 Type of services 0,36 Benefit After knowing the alternative determination, then determine the quantitative value of the criteria on each alternative. The weight of the criteria uses the proposed approach (Annisaa, Anugrah, & Devi, 2022). The criteria used are as follows ; The type of malfunction (C1) is data sourced from the request. With the type of criteria that are of the benefit type, where if the vulnerability or damage is higher, it has a high level of assessment. The rating is in table 4. Table 4. Value of the risk of damage Type of damage Description Value Internet network very high 5 Local network High 4 Hardware Enough 3 PC Low 2 Software very low 1 The risk of complaint (C2) is the risk of complaints coming from the user. The criteria are of the benefit type, where if the risk of the complaint is high, it has a high level of assessment. The rating is in table 5. Table 5. The value of risk complain The risk of complaint Description Value Level 1 very high 5 Level 2 High 4 Level 3 Enough 3 Level 4 Low 2 Level 5 very low 1 The request hour (C3) in this case is the time it takes to make repairs. The criteria are of the benefit type, where if the time required is a lot, the assessment given is high. The rating is in table 6. Table 6. The value of demand hour Demand hour Description Value >24 hour very high 5 10 - 24 hour High 4 3-10 hour Enough 3 30 minutes โ€“ 3 hours Low 2 0 โ€“ 30 minutes very low 1 Type of service (C4) is a service contained in the regional apparatus with the type of benefit criteria, where if the type of public service there is damaged, the value provided is high from management services. The rating is in table 7. Table 7. Type of service value Demand hour Description Value Public service High 2 Management Moderate 1 If the value of each criterion has been determined, then create a matching rating table as in table 8. P-ISSN: 2656-1743 | E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i1.472 JURNAL RISET INFORMATIKA Vol. 5, No. 1. December 2022 Accredited rank 3 (SINTA 3), excerpts from the decision of the Minister of RISTEK-BRIN No. 200/M/KPT/2020 512 Table 8. The Alternate match rating Alternative Criteria C1 C2 C3 C4 Kec. Maduran 4 4 5 2 Kec. Sekaran 4 4 1 2 Gedung PKK 5 1 5 1 Kec. Pucuk 1 4 2 2 Kec. Brondong 3 4 1 2 Bakesbangpol 5 2 4 1 Gedung DPRD 5 3 2 1 Dinas perpustakaan 4 5 4 2 Dispora 5 3 2 1 Inspektorat 2 3 3 1 Furthermore, the application of the MOORA method was carried out in selecting improvement priorities so as to produce the best alternative that could be chosen and recommended (Hendrayana & Mahendra, 2019) to prioritize the improvement. After the results of the suitability rating in table 8 are transformed into the X matrix as follows: ๐— = ( ๐Ÿ’ ๐Ÿ’ ๐Ÿ’ ๐Ÿ’ ๐Ÿ“ ๐Ÿ ๐Ÿ ๐Ÿ’ ๐Ÿ‘ ๐Ÿ’ ๐Ÿ“ ๐Ÿ ๐Ÿ“ ๐Ÿ‘ ๐Ÿ’ ๐Ÿ“ ๐Ÿ“ ๐Ÿ ๐Ÿ‘ ๐Ÿ‘ ๐Ÿ“ ๐Ÿ ๐Ÿ ๐Ÿ ๐Ÿ“ ๐Ÿ ๐Ÿ ๐Ÿ ๐Ÿ ๐Ÿ ๐Ÿ’ ๐Ÿ ๐Ÿ ๐Ÿ ๐Ÿ’ ๐Ÿ ๐Ÿ ๐Ÿ‘ ๐Ÿ ๐Ÿ) the approach taken to the MOORA method in the matrix normalization process is obtained from the denominator, the best choice is the square root of the sum of the squares and each alternative per attribute (Agustina & Sutinah, 2022), Matrix normalization is used to calculate the number of alternatives and the number of criteria (Wardani, Parlina, & Revi, 2018). The calculation of normalization is by dividing each alternative by the root value of the sum of the alternative values for each criterion that has been raised to the first power. The following is an example of calculating matrix normalization: ๐ด11 = 4 โˆš42 + 42 + 52 +12 + 32 + 52 +52 + 42 + 52 +22 = 0,314 ๐ด21 = 4 โˆš42 + 42 + 52 +12 + 32 + 52 +52 + 42 + 52 +22 = 0,314 In the same way, do it for all alternative C1 and other criteria so that the results are obtained as in Table 9. Table 9. normalization results Alternative Criteria C1 C2 C3 C4 Kec. Maduran 0,314 0,364 0,488 0,400 Kec. Sekaran 0,314 0,364 0,098 0,400 Gedung PKK 0,393 0,091 0,488 0,200 Alternative Criteria C1 C2 C3 C4 Kec. Pucuk 0,079 0,364 0,195 0,400 Kec. Brondong 0,236 0,364 0,098 0,400 Bakesbangpol 0,393 0,182 0,390 0,200 Gedung DPRD 0,393 0,273 0,195 0,200 Dinas perpustakaan 0,314 0,455 0,390 0,400 Dispora 0,393 0,273 0,195 0,200 Inspektorat 0,157 0,273 0,293 0,200 Optimizing the criteria for each alternative is given an importance value, provided that the maximum criteria type weight value is greater than the minimum criteria quality (Ferdian & Chotijah, 2022). To get the results of the optimization calculations, it was done by means of the results of the matrix normalization multiplied by the weights that had been determined for each criterion (Siregar, Poningsih, & Safii, 2018). The results of optimization calculations can be seen in Table 10. Table 10. The result of optimization Alternative Criteria C1 C2 C3 C4 Kec. Maduran 0,044 0,105 0,102 0,144 Kec. Sekaran 0,044 0,105 0,020 0,144 Gedung PKK 0,055 0,026 0,102 0,072 Kec. Pucuk 0,011 0,105 0,041 0,144 Kec. Brondong 0,033 0,105 0,020 0,144 Bakesbangpol 0,055 0,053 0,082 0,072 Gedung DPRD 0,055 0,079 0,041 0,072 Dinas perpustakaan 0,044 0,132 0,082 0,144 Dispora 0,055 0,079 0,041 0,072 Inspektorat 0,022 0,079 0,061 0,072 JURNAL RISET INFORMATIKA Vol. 5, No. 1. December 2022 P-ISSN: 2656-1743 |E-ISSN: 2656-1735 DOI: https://doi.org/10.34288/jri.v5i1.472 Accredited rank 3 (SINTA 3), excerpts from the decision of the Minister of RISTEK-BRIN No. 200/M/KPT/2020 513 The preference value is obtained by calculating the maximum and minimum values, namely by adding up the value of the benefit and cost criteria. Max is the criterion for the type of benefit and min is the criterion for the type of cost (Alisia, Ginting, & Syari, 2021). In this study there are only types of benefit criteria, the calculation results can be seen in Table 11. Table 11. Rankings Alternative Max Min Yi Kec. Maduran 0,396 0 0,396 Kec. Sekaran 0,314 0 0,314 Gedung PKK 0,256 0 0,256 Alternative Max Min Yi Kec. Pucuk 0,301 0 0,301 Kec. Brondong 0,303 0 0,303 Bakesbangpol 0,262 0 0,262 Gedung DPRD 0,247 0 0,247 Dinas perpustakaan 0,402 0 0,402 Dispora 0,247 0 0,247 Inspektorat 0,235 0 0,235 After calculating the preference value, the result of the highest preference value is the best alternative. The results of the ranking can be seen in Table 12. Tabel 12. Rankings Alternative Result Ranking Dinas Perpustakaan 0,396 1 Kecamatan Maduran 0,314 2 Kecamatan Sekaran 0,256 3 Kecamatan Brondong 0,301 4 Kecamatan Pucuk 0,303 5 Bakesangpol 0,262 6 Gedung PKK 0,247 7 Gedung DPRD 0,402 8 Dispora 0,247 9 Inspektorat 0,235 10 Based on the analysis that has been carried out using the MOORA method, the highest value calculation results are shown in Table 12, rank 1 is obtained at the library service alternative with the type of damage to the internet network, the level of damage is 1, with a request time of 12 hours, and the type of service is public service. 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