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Sistem Pendukung Keputusan Pemilihan Kartu Internet Smartphone Menggunakan Metode MOORA dan WASPAS Annisa Risqi Sulistya Kusuma Wardhani; Sitti Rachmawati Yahya; Tanwir Tanwir; Usanto S; A Ahyuna
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3039

Abstract

Currently the internet is the most widely used source of information among the public to find the information needed. The use of the internet can meet the needs of information sources that are fast, easy, precise, accurate and inexpensive. Through the internet can access a variety of information and knowledge according to relevant needs. The internet also has several advantages that are not shared by other conventional sources of information, access to information can be done with restrictions on distance, time and space which is part of the advantages of the internet. Making it possible to get the source of the information obtained. Thus, based on the results of a survey conducted by the previous author, involving 30 respondents who had used internet service packages before, the result was that 90% of respondents had difficulty making the right choice, according to the criteria they wanted. With a decision support system using the MOORA and WASPAS methods, it will be easier to find a solution to the problem of choosing an internet package based on the conditions offered by the various internet operators themselves. These criteria include speed, signal, internet quota, active period and price. Based on the calculations of these two methods, the best smartphone internet card title is alternative A1 with the name Telkomsel with a value for the MOORA method, which is 0.437, while the WASPAS method is 0.942 as the best alternative. So that people don't need to worry about choosing an internet card for smartphones that are good and have good access speeds
Implementasi Metode Preference Selection Index (PSI) dalam Seleksi Penerimaan Content Creator Media Sosial Usanto S
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 2 (2023): April 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i2.5936

Abstract

Currently social media in the world of work has an important role and can also be a place of business competition. Social media is now being used as an easier and more efficient promotional platform designed to capture the attention of the audience so as to expand the target market for higher profits. Content creators have an important role for business actors, content creators are responsible for social media owned by business actors. The selection process for accepting content creators is still carried out conventionally so that the selection process is sometimes not appropriate in accepting the best content creators. So with that, business actors must choose quality content creators so that their social media continues to be active and get a wider target audience. In selecting content creators, several criteria have been determined, namely skills, work experience, number of followers, interviews and education. Because of these problems, a system is needed that can assist in obtaining reliable and targeted recommendations. The application of a decision support system in this study was used by implementing the PSI (Preference Selection Index) method in which this method is very helpful in producing the best weight and preference values from alternative data and criteria so that the final result is the recommendation for the best content creator in Medan city in the Alternative A3 is Andriana with a value of 0.9236.
Penerapan Data Mining Dengan Mengimplementasikan Algoritma K-Means Dalam Proses Clustering Untuk Pengelompokan Mahasiswa Calon Penerima Beasiswa KIP Usanto S
Building of Informatics, Technology and Science (BITS) Vol 5 No 1 (2023): Juni 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v5i1.3411

Abstract

This research is about the grouping of prospective students who will receive KIP scholarships. Data mining is a conception or design made with the aim of finding an added value contained in a database that will be able to identify a useful knowledge information. In this study, the concept of data mining was applied to assist campuses in predicting students who will get KIP scholarships by implementing the K-MeansClustering Algorithm, where the K-MeansClustering algorithm can later group each data into clusters so that data that has the same characteristics will be grouped in the same cluster and vice versa if the data has different characteristics then it is grouped into another cluster. The results of this study are 3 cluster results which will be the final result, namely data received as scholarship recipients as many as 52 data, 32 data are grouped as recipient data which will be recommended to the next stage. while the remaining 16 data are grouped as data that is not accepted
Evaluating the Suitability of Online Courses using the ELECTRE Method S Sahyunu; Jimmy Moedjahedy; Iwan Adhicandra; Yogasetya Suhanda; Usanto S; Robbi Rahim
AL-ISHLAH: Jurnal Pendidikan Vol 15, No 3 (2023): AL-ISHLAH: JURNAL PENDIDIKAN
Publisher : STAI Hubbulwathan Duri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35445/alishlah.v15i3.3912

Abstract

This study aims to explore the use of the Elimination and Choice Expressing Reality (ELECTRE) method for selecting and evaluating online courses. The pairwise comparison method determined a set of criteria and weights, including course quality, instructor experience, accreditation, student engagement, flexibility, technical support, and cost. The study used a mixed-methods approach, which means it combines quantitative and qualitative data. The ELECTRE method was then applied to rank five online courses based on their suitability for the participants' needs and expectations. The concordance and discordance indices were calculated for each course, and the net flow was used to determine the ranking. The results showed that the ELECTRE method can be a useful tool for participants in choosing and evaluating online courses based on a set of tailored criteria and weights. Future research could investigate how the results of the ELECTRE method can be combined with other methods to enhance the accuracy and validity of the ranking. Overall, the ELECTRE method provides a useful framework for participants to decide which online course is best suited to their individual preferences and goals.