Pub Date : 2022-06-30DOI: 10.31315/telematika.v19i2.6534
Soni Adiyono, Romy Aziz Risaldi, A. P. Widodo, E. Sediyono
Purpose: This study aims to determine the efforts to minimize the occurrence of risks in enterprise systems and how far the framework is applied to an organization, as well as what steps must be applied in anticipation of it.Design/methodology/approach: This study uses a systematic review research method of literature published by international journals in the period 2016 to 2021 which is subscribed to by Diponegoro University.Findings/result: Most of the selected journals stated that in an effort to secure enterprise systems in an organization, they really consider several aspects in it, especially in terms of cost which is one of the biggest considerations in it, besides that support from policy makers must be needed to make guidelines in implementing framework (framework) regarding the limitations of Authentication access and interaction on a system.Originality/value/state of the art: the method applied will focus on discussing the realm of enterprise systems, specifically discussing framework management in an effort to minimize risks to enterprise systems.
{"title":"Framework Management to Minimize Risk in Protecting Enterprise Systems: Systematic Literature Review","authors":"Soni Adiyono, Romy Aziz Risaldi, A. P. Widodo, E. Sediyono","doi":"10.31315/telematika.v19i2.6534","DOIUrl":"https://doi.org/10.31315/telematika.v19i2.6534","url":null,"abstract":"Purpose: This study aims to determine the efforts to minimize the occurrence of risks in enterprise systems and how far the framework is applied to an organization, as well as what steps must be applied in anticipation of it.Design/methodology/approach: This study uses a systematic review research method of literature published by international journals in the period 2016 to 2021 which is subscribed to by Diponegoro University.Findings/result: Most of the selected journals stated that in an effort to secure enterprise systems in an organization, they really consider several aspects in it, especially in terms of cost which is one of the biggest considerations in it, besides that support from policy makers must be needed to make guidelines in implementing framework (framework) regarding the limitations of Authentication access and interaction on a system.Originality/value/state of the art: the method applied will focus on discussing the realm of enterprise systems, specifically discussing framework management in an effort to minimize risks to enterprise systems. ","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77519185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-28DOI: 10.35671/telematika.v15i1.1222
R. Kosasih
Traffic surveillance was initially carried out directly using CCTV, but this kind of surveillance was not possible for a full day by the security forces. In addition, with the increasing growth of vehicles in Indonesia, a method is needed that can be used to assist security forces in monitoring traffic such as detecting and automatically counting the number of vehicles. Therefore, in our research, we propose a method that can detect vehicles, and count the number of vehicles from video recordings on the Bintara Bekasi toll road using background substraction methods such as gaussian mixture models and morphological operations. The results showed that the vehicle detection accuracy rate was 86.3636%, the precision was 89.0625%, and the recall was 96.6101%. In this study, vehicle classification was also carried out based on the detection results into two types of vehicles, namely cars and trucks. From the results of the research, the classification accuracy rate was obtained at 85.9649%.
{"title":"Detection and Classification of Vehicles on the Bekasi Toll Road Using the Gaussian Mixture Models Method and Morphological Operations","authors":"R. Kosasih","doi":"10.35671/telematika.v15i1.1222","DOIUrl":"https://doi.org/10.35671/telematika.v15i1.1222","url":null,"abstract":"Traffic surveillance was initially carried out directly using CCTV, but this kind of surveillance was not possible for a full day by the security forces. In addition, with the increasing growth of vehicles in Indonesia, a method is needed that can be used to assist security forces in monitoring traffic such as detecting and automatically counting the number of vehicles. Therefore, in our research, we propose a method that can detect vehicles, and count the number of vehicles from video recordings on the Bintara Bekasi toll road using background substraction methods such as gaussian mixture models and morphological operations. The results showed that the vehicle detection accuracy rate was 86.3636%, the precision was 89.0625%, and the recall was 96.6101%. In this study, vehicle classification was also carried out based on the detection results into two types of vehicles, namely cars and trucks. From the results of the research, the classification accuracy rate was obtained at 85.9649%.","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80899799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-28DOI: 10.35671/telematika.v15i1.1307
O. Somantri
This research proposes a method to optimize the accuracy of the Naïve Bayes (NB) model by optimizing weight using a genetic algorithm (GA). The process of giving optimal weight is carried out when the data will be input into the analysis process using NB. The research stages were conducted by preprocessing the data, searching for the classic naïve Bayes model, optimizing the weight, applying the hybrid model, and as the final stage, evaluating the model. The results showed an increase in the accuracy of the proposed model, where the naïve Bayes classical model produced accuracy rate of 87.69% and increased to 88.65% after optimization using GA. The results of the study conclude that the proposed optimization model can increase the accuracy of the classification of early detection of diabetes.
{"title":"An Optimize Weights Naïve Bayes Model for Early Detection of Diabetes","authors":"O. Somantri","doi":"10.35671/telematika.v15i1.1307","DOIUrl":"https://doi.org/10.35671/telematika.v15i1.1307","url":null,"abstract":"This research proposes a method to optimize the accuracy of the Naïve Bayes (NB) model by optimizing weight using a genetic algorithm (GA). The process of giving optimal weight is carried out when the data will be input into the analysis process using NB. The research stages were conducted by preprocessing the data, searching for the classic naïve Bayes model, optimizing the weight, applying the hybrid model, and as the final stage, evaluating the model. The results showed an increase in the accuracy of the proposed model, where the naïve Bayes classical model produced accuracy rate of 87.69% and increased to 88.65% after optimization using GA. The results of the study conclude that the proposed optimization model can increase the accuracy of the classification of early detection of diabetes.","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73313959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-28DOI: 10.31315/telematika.v19i1.6415
Atin Triwahyuni, E. Hartati, Hera Setiawan, Riska Triani
Purpose: The focus of this research is to create a Consumer Service Questionnaire Dashboard application that can perform questionnaire data processing, service satisfaction analysis and reporting the results of service improvement recommendations at STMIK PalComTech.Design/methodology/approach: This study uses the Prototype method, where this method can interact with the user during user creation. This method consists of five stages, namely communication, planning quickly, modeling the design quickly, making prototypes, and submitting the system or software to the user or users to be tested using the black box testing method.Findings/result: The results of this study resulted in an application for processing customer service questionnaires from STMIK PalComTech, to simplify and shorten UPT-PM staff in preparing reports on the results of the questionnaire recap, reporting and distributing the results of the questionnaire recap of the Head of UPT-PM.Originality/value/state of the art: The system testing technique used in this study is black box testing, this testing technique focuses on the functional specifications of the software, this test is also used to find errors in the system, for example interface errors, performance errors, incorrect or missing functions.
{"title":"STMIK PalComTech Customer Service Questionnaire Processing Application Design","authors":"Atin Triwahyuni, E. Hartati, Hera Setiawan, Riska Triani","doi":"10.31315/telematika.v19i1.6415","DOIUrl":"https://doi.org/10.31315/telematika.v19i1.6415","url":null,"abstract":"Purpose: The focus of this research is to create a Consumer Service Questionnaire Dashboard application that can perform questionnaire data processing, service satisfaction analysis and reporting the results of service improvement recommendations at STMIK PalComTech.Design/methodology/approach: This study uses the Prototype method, where this method can interact with the user during user creation. This method consists of five stages, namely communication, planning quickly, modeling the design quickly, making prototypes, and submitting the system or software to the user or users to be tested using the black box testing method.Findings/result: The results of this study resulted in an application for processing customer service questionnaires from STMIK PalComTech, to simplify and shorten UPT-PM staff in preparing reports on the results of the questionnaire recap, reporting and distributing the results of the questionnaire recap of the Head of UPT-PM.Originality/value/state of the art: The system testing technique used in this study is black box testing, this testing technique focuses on the functional specifications of the software, this test is also used to find errors in the system, for example interface errors, performance errors, incorrect or missing functions.","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86269420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-28DOI: 10.31315/telematika.v19i1.7165
Dona Aryanti, O. S. Simanjuntak, Juwairiah Juwairiah
Purpose: This study aims to measure success and determine the factors that support or hinder the success of the e-learning SPADA Wimaya.Method: This study adapts the development of the DeLone and McLean Model 2003. The data used are primary data obtained from the answers of 387 users of the e-learning SPADA Wimaya Pembangunan Nasional “Veteran” Yogyakarta University as respondents in the distributed questionnaire. The results of the questionnaire were processed using SPSS to test descriptive of the data. After that, the data is processed using Structural Equation Modeling (SEM) for testing the inner model and outer model which includes hypothesis testing through SmartPLS software.Result: Of the nine proposed hypotheses, six were accepted and the other three were rejected. Because not all variables affect each other significantly, the e-learning SPADA Wimaya is declared to have not been successful. The factors that hinder the success of the e-learning SPADA Wimaya are the security indicator on the system quality variable, responsive indicator on the service quality variable and communication effectiveness on the net benefit variable.
{"title":"Success Measurement of E-Learning Spada Wimaya at Universitas Pembangunan Nasional “Veteran” Yogyakarta Using Delone and Mclean Model Approach","authors":"Dona Aryanti, O. S. Simanjuntak, Juwairiah Juwairiah","doi":"10.31315/telematika.v19i1.7165","DOIUrl":"https://doi.org/10.31315/telematika.v19i1.7165","url":null,"abstract":"Purpose: This study aims to measure success and determine the factors that support or hinder the success of the e-learning SPADA Wimaya.Method: This study adapts the development of the DeLone and McLean Model 2003. The data used are primary data obtained from the answers of 387 users of the e-learning SPADA Wimaya Pembangunan Nasional “Veteran” Yogyakarta University as respondents in the distributed questionnaire. The results of the questionnaire were processed using SPSS to test descriptive of the data. After that, the data is processed using Structural Equation Modeling (SEM) for testing the inner model and outer model which includes hypothesis testing through SmartPLS software.Result: Of the nine proposed hypotheses, six were accepted and the other three were rejected. Because not all variables affect each other significantly, the e-learning SPADA Wimaya is declared to have not been successful. The factors that hinder the success of the e-learning SPADA Wimaya are the security indicator on the system quality variable, responsive indicator on the service quality variable and communication effectiveness on the net benefit variable.","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89737164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tujuan: Mengetahui seberapa akurat penggunaan perbaikan kata metode Levenshtein Distance terhadap analisis sentimen vaksin Covid-19 menggunakan metode Naïve Bayes.Perancangan/metode/pendekatan: Menerapkan perbaikan kata Levenshtein Distance untuk preprocessing dan algoritma Naïve Bayes dalam melakukan analisis sentimen komentar masyarakat tentang vaksin Covid-19.Hasil: Dengan diterapkannya perbaikan kata pada dataset yang digunakan dapat meningkatkan akurasi dari model Naïve Bayes yang dibangun. Akurasi pengujian menggunakan data uji lama yang berjumlah 479 data meningkat dari 61% menjadi 71% dan pengujian dengan data uji baru yang berjumlah 100 data akurasi meningkat dari 59% menjadi 66%. Namun untuk klasifikasi data testing baru memperoleh akurasi yang cukup rendah walaupun data yang dites hanya berjumlah 100 data, hal ini disebabkan oleh sistem yang kurang mampu dalam melakukan klasifikasi data baru yang belum pernah dilakukan training sebelumnya.Keaslian/ state of the art: Penelitian ini menggunakan data dengan jumlah 2394 data yang berasal dari komentar akun Instagram Kemenkes RI. Untuk preprocessing dilakukan perbaikan kata dengan algoritma Levenshtein Distance dan untuk analisis komentar menggunakan algoritma Naïve Bayes dengan ekstraksi fitur TF-IDF.
{"title":"Analisis Sentimen Vaksin Covid-19 Menggunakan Algoritma Naive Bayes dan Perbaikan Kata Levenshtein Distance","authors":"Fahmi Reza Prasastio, Heriyanto Heriyanto, Wilis Kaswidjanti","doi":"10.31315/telematika.v19i1.6577","DOIUrl":"https://doi.org/10.31315/telematika.v19i1.6577","url":null,"abstract":"Tujuan: Mengetahui seberapa akurat penggunaan perbaikan kata metode Levenshtein Distance terhadap analisis sentimen vaksin Covid-19 menggunakan metode Naïve Bayes.Perancangan/metode/pendekatan: Menerapkan perbaikan kata Levenshtein Distance untuk preprocessing dan algoritma Naïve Bayes dalam melakukan analisis sentimen komentar masyarakat tentang vaksin Covid-19.Hasil: Dengan diterapkannya perbaikan kata pada dataset yang digunakan dapat meningkatkan akurasi dari model Naïve Bayes yang dibangun. Akurasi pengujian menggunakan data uji lama yang berjumlah 479 data meningkat dari 61% menjadi 71% dan pengujian dengan data uji baru yang berjumlah 100 data akurasi meningkat dari 59% menjadi 66%. Namun untuk klasifikasi data testing baru memperoleh akurasi yang cukup rendah walaupun data yang dites hanya berjumlah 100 data, hal ini disebabkan oleh sistem yang kurang mampu dalam melakukan klasifikasi data baru yang belum pernah dilakukan training sebelumnya.Keaslian/ state of the art: Penelitian ini menggunakan data dengan jumlah 2394 data yang berasal dari komentar akun Instagram Kemenkes RI. Untuk preprocessing dilakukan perbaikan kata dengan algoritma Levenshtein Distance dan untuk analisis komentar menggunakan algoritma Naïve Bayes dengan ekstraksi fitur TF-IDF.","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81848495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-28DOI: 10.31315/telematika.v19i1.6450
A. Murdiyanto, A. Himawan
Purpose: To identify keywords that can be chosen to increase CTR on the website so that the potential revenue of targeted prospects through search engines is higher.Design/methodology/approach: This study applies the weighted product method based on the criteria that will be determined to find the best keyword list.Findings/result: The results of identification by ranking using the weighted product method based on the criteria C1, C2, and C3 resulted in an average increase in CTR of 16.18% to 22.92%. With this increase, business owners can be more efficient in the online advertising process.Originality/value/state of the art: The identification of keywords that can be chosen to increase CTR on a website by ranking using the weighted product method has never been done by previous researchers.
{"title":"Identification Of Keywords That Impact Of Increasing The Click Through Rate Of Online Advertising On Search Engines","authors":"A. Murdiyanto, A. Himawan","doi":"10.31315/telematika.v19i1.6450","DOIUrl":"https://doi.org/10.31315/telematika.v19i1.6450","url":null,"abstract":"Purpose: To identify keywords that can be chosen to increase CTR on the website so that the potential revenue of targeted prospects through search engines is higher.Design/methodology/approach: This study applies the weighted product method based on the criteria that will be determined to find the best keyword list.Findings/result: The results of identification by ranking using the weighted product method based on the criteria C1, C2, and C3 resulted in an average increase in CTR of 16.18% to 22.92%. With this increase, business owners can be more efficient in the online advertising process.Originality/value/state of the art: The identification of keywords that can be chosen to increase CTR on a website by ranking using the weighted product method has never been done by previous researchers. ","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83582609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-28DOI: 10.31315/telematika.v19i1.7174
I. A. T. Putra, Ketut Sepdyana Kartini, N. Putri
Tujuan: PT. Arta Jaya Elektrik memiliki karyawan yang setiap bulan diberikan gaji dan setiap 6 bulan diberikan bonus gaji. Dalam proses penentuan bonus karyawan masih menggunakan Microsoft Excel sehingga terkadang terjadi kesalahan dalam proses penginputan data yang akan digunakan untuk penilaian karyawan. Selain itu, dikarenakan harus membuat rekapan data penunjang pemberian bonus karyawan.Perancangan/metode/pendekatan: Perancangan sistem dibuat untuk dapat mengelola data karyawan, data kriteria, data sub-kriteria, data penilaian, data perhitungan, dan data hasil akhir. Pendekatan Metode MAUT dan MABAC digunakan karena ingin melakukan perbandingan untuk memilih metode yang paling tepat dan mudah dalam menentukan bonus gaji karyawan. Hasil: Pengujian perhitungan menggunakan MAUT dan MABAC menghasilkan urutan hasil peringkat yang sama. Namun hasil total perhitungan menunjukan jumlah yang berbeda. Keaslian/ state of the art: Berdasarkan penelitian terdahulu, dalam penelitian ini menggunakan kriteria absensi, keterlambatan, lembur, dan kinerja karyawan dalam melakukan perhitungan metode MAUT dan MABAC untuk mencari hasil akhir perangkingan alternatif.
{"title":"COMPARISON OF MAUT METHOD WITH MABAC IN GIVING EMPLOYEES SALARY BONUS AT PT. ARTA JAYA ELECTRIC","authors":"I. A. T. Putra, Ketut Sepdyana Kartini, N. Putri","doi":"10.31315/telematika.v19i1.7174","DOIUrl":"https://doi.org/10.31315/telematika.v19i1.7174","url":null,"abstract":"Tujuan: PT. Arta Jaya Elektrik memiliki karyawan yang setiap bulan diberikan gaji dan setiap 6 bulan diberikan bonus gaji. Dalam proses penentuan bonus karyawan masih menggunakan Microsoft Excel sehingga terkadang terjadi kesalahan dalam proses penginputan data yang akan digunakan untuk penilaian karyawan. Selain itu, dikarenakan harus membuat rekapan data penunjang pemberian bonus karyawan.Perancangan/metode/pendekatan: Perancangan sistem dibuat untuk dapat mengelola data karyawan, data kriteria, data sub-kriteria, data penilaian, data perhitungan, dan data hasil akhir. Pendekatan Metode MAUT dan MABAC digunakan karena ingin melakukan perbandingan untuk memilih metode yang paling tepat dan mudah dalam menentukan bonus gaji karyawan. Hasil: Pengujian perhitungan menggunakan MAUT dan MABAC menghasilkan urutan hasil peringkat yang sama. Namun hasil total perhitungan menunjukan jumlah yang berbeda. Keaslian/ state of the art: Berdasarkan penelitian terdahulu, dalam penelitian ini menggunakan kriteria absensi, keterlambatan, lembur, dan kinerja karyawan dalam melakukan perhitungan metode MAUT dan MABAC untuk mencari hasil akhir perangkingan alternatif.","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87105514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-28DOI: 10.31315/telematika.v19i1.6878
Komang Gde Hendra Kusuma Putra, I. Candiasa, G. Indrawan
Purpose: This study aims to analyze and determine the effectiveness of the combination of decision-making methods in the selection of outstanding students using the Analytical Hierarchy Process (AHP) and Weighted Product (WP) methods.Design/methodology/approach: A quantitative approach is used to analyze the combination of AHP and WP methods in determining outstanding students. The ranking results were analyzed using Mean Absolute Percentage Error (MAPE).Findings/result: This research produces a combination analysis of the AHP and WP decision-making methods, so that it can be used for implementation into information systems.Originality/value/state of the art: The difference between this study and previous studies is the combination of methods used in this study. An analysis of the effect of several variables in increasing accuracy is also produced.
{"title":"Analysis of the AHP-WP Method in the Decision Support System for the Assessment of Outstanding Students at ITEKES Bali","authors":"Komang Gde Hendra Kusuma Putra, I. Candiasa, G. Indrawan","doi":"10.31315/telematika.v19i1.6878","DOIUrl":"https://doi.org/10.31315/telematika.v19i1.6878","url":null,"abstract":"Purpose: This study aims to analyze and determine the effectiveness of the combination of decision-making methods in the selection of outstanding students using the Analytical Hierarchy Process (AHP) and Weighted Product (WP) methods.Design/methodology/approach: A quantitative approach is used to analyze the combination of AHP and WP methods in determining outstanding students. The ranking results were analyzed using Mean Absolute Percentage Error (MAPE).Findings/result: This research produces a combination analysis of the AHP and WP decision-making methods, so that it can be used for implementation into information systems.Originality/value/state of the art: The difference between this study and previous studies is the combination of methods used in this study. An analysis of the effect of several variables in increasing accuracy is also produced.","PeriodicalId":31716,"journal":{"name":"Telematika","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83547380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-28DOI: 10.31315/telematika.v19i1.7181
Devin Waas, Made Dona Wahyu Arsitana, I. P. H. Permana, I. K. Wiratama, I. Sudipa
Purpose: Adjust the Group Decision Support System (GDSS) model in completing case studies of selecting the best alternative candidate pairs for the OSIS core board with many decision-makers and problems in the differences in the preferences of decision-makers as well as modeling in decision making with multi-criteria and multi-attributes and combining preferences decision-makers to choose the best alternative partner candidate.Design/methodology/approach: The Group Decision Support System (GDSS) model combines the SMART method for modeling multi-criteria and multi-attribute assessments and the Copeland Score model for aggregating the judgments of five decision-makers against the selected pair of OSIS core board candidates using a voting mechanism.Findings/result: The comparison test for the manual calculation of the SMART- Copeland Score Model method with the results of the system calculation is the same. From the ten alternative data in the first stage of the test through the SMART method calculation, it then passes into four alternatives divided into two alternative candidate pairs, namely alternative candidate pairs (A1, A3) and alternative candidate pairs (A2, A4). The second stage test uses calculations Copeland Score voting, which produces the best alternative candidate pair, namely alternative (A1, A3) with a final point score = 4.Originality/value/state of the art: Based on a review of previous research, this study uses line-up criteria, written tests, and interview tests with the SMART method to calculate alternative scores on each criteria, and the Copeland Score model to aggregate decision makers' preferences to produce the best alternative candidate pairs. In calculating the final value of the alternative ranking.
目的:调整群体决策支持系统(Group Decision Support System, GDSS)模型，完成多决策者的OSIS核心板最佳备选人选对选择的案例研究和决策者偏好差异问题，以及多标准多属性决策建模，结合偏好决策者选择最佳备选搭档人选。设计/方法/方法:群体决策支持系统(GDSS)模型结合了SMART方法，用于建模多标准和多属性评估，以及Copeland评分模型，用于通过投票机制汇总五个决策者对选定的sis核心董事会候选人的判断。发现/结果:人工计算SMART- Copeland评分模型方法与系统计算结果的对比检验相同。从第一阶段测试的10个备选数据通过SMART方法计算，然后传递到4个备选数据，分为两个备选备选数据对，即备选备选数据对(A1, A3)和备选备选数据对(A2, A4)。第二阶段测试使用计算Copeland得分投票，产生最佳备选候选人对，即最终得分= 4的备选(A1, A3)。原创性/价值/技术水平:在回顾以往研究的基础上，本研究使用阵容标准、笔试和面试测试，采用SMART方法计算每个标准的备选分数，并使用Copeland评分模型汇总决策者的偏好，以产生最佳备选候选人对。在计算备选排名的最终值时。
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