Issue handling of inadvertence situations in the decision-making process of recruiting new employees at PT. Warta Media Nusantara that use criteria value of interviews, field test, a psychological test and medical check-up requires Multi Attribute Decision Making (MADM) as an auxiliary method of decision-making on the prospective eligible employee to be accepted in the company. There are various MADM methods, such as Simple Additive Weighting (SAW) method and Weighted Product (WP) method. Both of these methods are known as the most common method used in handling MADM issues, so in this study both methods are applied to the DSS and analyzed the differences in terms of obtained results and the execution time required for each method. The results of the study of the application of SAW and WP methods in the recruitment of new employees DSS there are some differences in the results of the candidates rank order and the differences in execution time of each method. The differences in rank order of these methods are due to the effects of alternative values, weighting criteria, and the calculation method. WP method is able to provide more rigorous result than SAW method, while the difference in execution time of SAW and WP methods explains that the execution time of SAW method relatively quick because SAW calculation method has a simpler process than the process of WP calculation methods.
Technological development is growing rapidly among with the increasing of human needs especially in mobile technology where the technology that often be used is android. The existence of this android facilitates the user in access of information. This android can be used for healthy needs, for example is detecting dental disease. One of the branches of computer science that can help society in detecting dental disease is expert system. In this research, making expert system to diagnosis dental disease by using certainty factor method. Dental disease diagnosis application can diagnose the patient based on griping of the patient about dental disease so it can be obtained diseases possibility of the patient itself. This application is an expert system application that operates on android platform. Furthermore, in the measurement accuracy of the system test performed by 20 patients, there were 19 cases of corresponding and 1 cases that do not fit. So, from system testing performed by 20 patients resulted in a 95% accuracy rate.
This research develops a decision support system for the selection of outstanding students by combining AHP and TOPSIS methods. AHP method was used because it could be implemented to this data and do the priority ranking process for each criterion based on pairwise comparison matrix. The TOPSIS method was used because the concept of the chosen alternative does not only have the shortest distance from the positive ideal solution, but also has the longest distance from the negative ideal solution. The purpose of this study was finding out the workings of the TOPSIS method and the AHP-TOPSIS combination method, as well as to find out the comparison of the best methods between TOPSIS and the combination method of AHP-TOPSIS in the selection of outstanding students. The concept of TOPSIS is simple and easy to understand and has the ability to measure decision alternatives while AHP is not chosen because the AHP method is widely used in the case of criteria weighting and priority determination of each criterion. However, if the two methods were combined the results will be better because in AHP there is an eigenvector concept which is used to do the priority ranking process for each criterion based on pairwise comparison matrix, then the results of the weighting criteria are processed by the TOPSIS method for ranking process. The application of the TOPSIS method on the selection of outstanding students can be analyzed with the results of the presentation using Hamming Distance incompatibility is 93%. Meanwhile, the application of the AHP-TOPSIS combination method gets the presentation results using Hamming Distance incompatibility is 91%. Based on these results in this study it can be concluded that the AHP-TOPSIS combination method is better than the TOPSIS method.
ThispaperdescribedtheuseofGeoGebrasoftwaretohelpstudentsinunderstanding Calculus material and its applications. GeoGebra is already used by more than 100 million students around the world. GeoGebra has the ability to minimize the difficulties of students who get Calculus subjects, especially students majoring in Natural Sciences and Engineering because this subject becomes a compulsory subject and a fundamental foundation in mathematics and its application across multidisciplinary fields such as medical, social sciences, psychology, and economics. Usually, the calculus course is given to first-year university students as the foundation for next course requirement. However, the manual calculation in Calculus sometimes takes a long time as it requires mathematics skills to solve the problem. Therefore, the advantagesofusingGeoGebraare(a)helpingtoconveytheCalculusconceptmaterial to be more interesting, especially for the delivery of material concepts of functions, limits, derivatives, and integrals, (b) providing a more realistic image, especially for more complex calculus material, and (c) providing a faster and accurate solution.
System backup can’t be a good solution without planning. Secure data backup planning will prevent more data loss. The Comprehensive Exam is a system to conduct a comprehensive exam and test score management, which is also carried out with the Computer-Based Test. The two systems are connected, these are running with a data-based application programming interface (API) synchronization on two different servers. Two servers running simultaneously with the synchronized API. Special methods of solving this problem are needed to back up supported information systems and computer-based tests. Disaster Recovery is a term for recovery and resumption. A disaster recovery plan is a plan to improve information technology (IT) infrastructure from other disasters that endanger the information infrastructure. One method of recovering business processes is to restore the data backup itself. Data backup is one of the important elements, the data backup method will be applied is the disk mirroring method, which is making a permanent backup from the main data center, data backup will be provided a real-time backup using the Distributed Replicated Block Device (DRBD) concept. In our research concluded automatically synchronizes implementation backup data using the DRBD concept.
E-learning merupakan suatu jenis media untuk melakukan proses belajar mengajar secara mandiri yang memungkinkan tersampaikan bahan ajar ke mahasiswa melalui media jaringan komputer atau internet. E-learning semakin banyak digunakan oleh lembaga pendidikan karena mempermudah para pengguna untuk dapat mengakses dimanapun dan kapanpun tanpa adanya pembatasan ruang dan waktu sehingga mahasiswa dapat dengan leluasa memperoleh materi-materi kuliah yang ditempuh. Tetapi untuk e-learning yang berbasis web ini dirasa masih banyak yang kekurangan sehingga dirasa sangat sulit digunakan atau tidak menarik penggunanya dan tidak dipakai secara efektif dan efisien sebagaimana mestinya. Hal ini dikarenakan usability pada web tidak diperhatikan sehingga hubungan interaksi antara manusia yang merupakan salah satu faktor penting dalam sebuah sistem terabaikan. Usabilitas terdiri dari learnability (mudah dipelajari), efficiency (efisien), memorability (kemudahan dalam mengingat), errors (pencegahan kesalahan), dan satisfaction (kepuasan pengguna). Penelitian ini bertujuan untuk mengukur seberapa tinggi tingkat usabilitas yang telah ada pada sistem dan bagaimana respon pengguna terhadap web e-learning tersebut. Hasil penelitian adalah tingkat usability dari website e-learning sehingga dapat mengetahui kriteria apa saja yang belum diperbaiki sebagai dasar pengembangan user interface dari e-learning tersebut.
This paper presents the logical relationships of Aristotle's square of opposition on four basic categorial prepositions (i.e., contrary, contradictory, subcontrary, and subaltern) of Joint Opposite Selection (JOS). JOS brings a mutual reinforcement by joining two opposition strategies of Dynamic Opposite (DO) and Selective Leading Opposition (SLO). The DO and SLO improve the balance of exploration and exploitation, respectively, in a given search space. We also propose an enhancement of Golden Jackal Optimization (GJO) with Joint Opposite Selection named GJO-JOS. In the optimization process, JOS assists GJO in assaulting the prey swiftly using SLO. DO assists GJO in finding better chances to locate the fittest prey. With JOS, the GJO succeeds in elevating its performance. We evaluate the performance of GJO-JOS in a competition of CEC 2017 on a set of 29 benchmark functions. The benchmark functions include unimodal, multimodal, hybrid, and composition. Based on these benchmark functions, the evaluation results of GJO-JOS are competitive to GJO with seven single opposition-based learning strategies (OBLs). We also compare GJO-JOS to eight nature-inspired algorithms including the original version of GJO. GJO-JOS produces promising results among seven single OBLs, eight natured-inspired algorithms, and GJO. The experimental results confirm that GJO-JOS generates equilibrium in the balance mechanism effectively.
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