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Journal of Computing and Informatics Research
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 2808375X     DOI : -
Core Subject : Science,
Computer Science & IT
Fokus kajian Journal of Computing and Informatics Research mempublikasikan hasil-hasil penelitian pada bidang informatika, namun tidak terbatas pada bidang ilmu komputer yang lain, seperti: 1. Kriptografi, 2. Artificial Intelligence, 3. Expert System, 4. Decision Support System, 5. Data Mining, dan lainnya.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 88 Documents
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Implementasi Metode K-Medoids Untuk Clustring Penerima Bantuan Berdasarkan Normalisasi Data Masyarakat Miskin Dengan Metode Desimal Scaling Rispandi
Journal of Computing and Informatics Research Vol 3 No 1 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i1.1063

Abstract

The Social Welfare Office is the distributor of aid for the economically disadvantaged population in accordance with the regulations set by the Minister of Social Affairs of the Republic of Indonesia Number 20 of 2019. This aid is provided to the economically disadvantaged population selectively, not continuously, in the form of goods or cash, aiming to improve the welfare of the economically disadvantaged and socially vulnerable. The data of aid recipients from the economically disadvantaged population needs to be processed and normalized to obtain the desired information, facilitating the grouping of aid recipients at the Southeast Aceh Social Welfare Office. The aid recipients' data is processed and normalized to ease the grouping process using Decimal Scaling method, enabling the extraction of desired information. Subsequently, the data is clustered using the K-Medoids method to group aid recipients based on the normalized data, thus simplifying the identification of the most suitable aid recipients. This research employs a system capable of providing a solution for clustering aid recipient data using the K-Medoids method and the RapidMiner application
Klasifikasi Peminatan Topik Keilmuan Dalam Penyelesaian Studi Menggunakan Algoritma Naive Bayes Waldi Setiawan; Dedy Hartama; Muhammad Ridwan Lubis; Ihsan Syajidan; Agus Perdana Windarto
Journal of Computing and Informatics Research Vol 3 No 2 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i2.1200

Abstract

Academic expertise is a subject of study taught at the university level to assist students in completing their thesis writing, thereby enabling them to successfully complete their graduate studies. The chosen academic specialization aligns with the vision and mission of each program and can have a positive impact on the university. Students' chosen fields of expertise in completing their studies may either align or not align with the program's vision and mission. The variables used in this research are GPA, MKRV1, MKRV2, and Academic Expertise. The aim of this research is to determine how many students select an academic topic that aligns with the program's vision and mission, particularly in this case, the Computer Science program, as they complete their studies. The Naïve Bayes algorithm is employed in this research, yielding an accuracy rate of 98.11%. This research can provide valuable insights for STIKOM Tunas Bangsa Pematang Siantar to understand the extent to which students from other programs choose academic expertise that aligns with the vision and mission of each program.
Sistem Pendukung Keputusan Pemilihan Smartphone Kelas Midrange 2023 dengan Menggunakan Metode MAUT Afri Nirmalasari Halawa; Helfrida Hotmaria Sihite; Muhammad Syahrizal
Journal of Computing and Informatics Research Vol 3 No 2 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i2.1201

Abstract

Smart phones (HP) have become a basic need for society in various aspects of life, from communication, entertainment, information, to work. There are various kinds of cellphones on the market, with various features and specifications offered. The price of cellphones is getting more and more expensive, so consumers' needs for using cellphones are also different. Midrange cellphones are suitable for users who want a cellphone with fairly good specifications, but at a relatively affordable price. Midrange is a category of cellphone that is between the entry-level and high-end categories. Midrange cellphones usually have better specifications than entry-level cellphones, but are not as expensive as high-end cellphones. Therefore, an appropriate midrange class cellphone selection process is needed for people to get a cellphone that suits their needs at an affordable price. In the selection process for midrange class cellphones, a decision-making technique known as SPK (Decision Support System) is required. In this research, the MAUT method is used for the midrange class HP selection process. The level of importance of each criterion is determined by the researcher himself. The final result obtained is that the A5 is the highest midrange class cellphone with a final value (Ui) of 0.865. The second ranked alternative is A13 with a final value (Ui) of 0.857 and the third ranked alternative is A17 with a final value (Ui) of 0.657.
Implementation of the Simple Additive Weighting (SAW) Method in Selection of Students Recipients of Single Tuition Fee Assistance Riki Sulistio; Ahmad Fahreza Nasution; Muhammad Tawaf Akbar; Rima Tamara Aldisa; Bister Purba
Journal of Computing and Informatics Research Vol 3 No 2 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i2.1202

Abstract

Higher education in Indonesia, including at Budi Darma University, continues to be committed to creating an inclusive and equitable learning environment for all students. In line with this determination, Budi Darma University is implementing the Single Tuition Assistance (BUKT) program to support educational accessibility. Obstacles in the selection process, which is subjective and lacks a structured framework, can lead to inequality in the distribution of aid. This can result in students who should receive greater support being overlooked, while those who may need less may receive greater aid. In the BUKT selection process, there are a number of requirements that must be met, such as parents' income, PKH card ownership, completeness of documents, parents' dependents and home ownership. It is hoped that the use of a decision support system can be a solution to overcome this challenge. Decision Support Systems (DSS) integrate computer technology, mathematical models, and data to provide structured and organized support within a decision-making framework. The Simple Additive Weighting (SAW) method is a multi-criteria decision making method that allows relative weighing between criteria to determine the final score for each alternative. By applying SAW in the selection of BUKT recipient students, it is hoped that more objective and data-based decisions can be obtained. The research results produced the best alternative with a value of 100.00 in the alternative with code A5 in Fitri's name, so that Fitri was declared entitled to receive single tuition assistance.
Utilizing K-Means Clustering to Understanding Audience Interest in SEO-Optimized Media Content Erlin Windia Ambarsari; Dedin Fathudin; Gravita Alfiani
Journal of Computing and Informatics Research Vol 3 No 2 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i2.1207

Abstract

This study observes k-means clustering for segmenting SEO data to understand audience interests, identifying the elbow method as crucial for determining the optimal number of clusters. It highlights notable differences in content engagement across clusters, emphasizing the need for refined SEO strategies and a deeper understanding of audience segmentation. Despite challenges like SEO's dynamic nature and data reliance, this methodology provides a strong foundation for enhancing content strategies. Future research suggestions include cross-platform data integration, longitudinal studies, sentiment analysis, content experimentation, user experience (UX) focus, and monitoring algorithm updates to develop more adaptive content and SEO strategies aligned with changing audience behaviors.
Implementasi Metode Additive Ratio Assessment (ARAS) Dalam Penilaian Kinerja Perangkat Desa Pada Kantor Pemerintahan Desa Tebing Linggahara Siti Sundari
Journal of Computing and Informatics Research Vol 3 No 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i3.1491

Abstract

Village Apparatus is a public service personnel who has duties and responsibilities towards community service, assisting the village head in carrying out his duties. So far, the performance assessment of village apparatus at the Tebing Linggahara Village government office is still manual so it takes a long time. Therefore, a decision support system is needed that can provide convenience in assisting the local government to assess the performance of village apparatus at the Tebing Linggahara Village government office. In this study, a decision support system is proposed that can assist in assessing the performance of village apparatus, namely using the Additive Ratio Assessment (ARAS) method. The ARAS method is part of the Multi Criteria Decision Making (MCDM) which is closely related to the Decision Support System. The ARAS method can also be used to make decisions from each alternative, then from each alternative has several criteria that are used as a reference in calculations using the ARAS Method. The ARAS method is used for ranking values. With this ranking method, Aminah Ritonga (A3) is the village apparatus with the best performance in the Tebing Linggahara Village Government office with the largest value of 6.5187, followed by Ramlan Saragih (A12) in second place with a value of 3.0966, then Samsuddin (A2) in third place with a value of 2.8224. It is hoped that the assessment of village apparatus performance will be more precise because it is based on the predetermined criteria and weight values, so that it will get maximum results.
Penerapan Sistem Pendukung Keputusan Seleksi Dosen Non Komputer Terbaik Menggunakan Metode Weighted Product (WP) Lumban, Romayani; Muhammad Syahrizal
Journal of Computing and Informatics Research Vol 3 No 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i3.1492

Abstract

Lecturers are individuals who have professional and scientific expertise, with the main task of changing, developing and disseminating knowledge, technology and art through educational activities, research and community service. Until now, the selection process for Non-Computer Lecturers has focused on experience as an educator, although there are several other criteria that can be used as a basis for selecting Non-Computer Lecturers. These criteria include Grade Point Average (GPA), ability to collaborate in a team, physical and mental health, expertise in interpersonal skills, and ability in Micro Teaching. The selection process for Non-Computer Lecturers requires support from a decision support system (DSS). DSS is part of a computer-based information system (including knowledge-based systems) that is used to assist in decision making in various types of organizations or entities. In this research, the Weighted Product (WP) method is used to select the best Non-Computer Lecturers. The choice of this method is based on its ability to evaluate and select the best solution from a variety of available alternatives. The results obtained from this research are that alternative A1 with the name Lecturer "Melda Panjaitan, M.Pd" with a value of Vi = 0.2220 is the best alternative.
Decision Support System for Determining the Best School Extracurricular Activities by Combining the ROC and MAUT Methods Jahril; Abdul Karim; Erlin Windia Ambarsari; Agus Perdana Windarto
Journal of Computing and Informatics Research Vol 3 No 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i3.1493

Abstract

The various extracurricular activities at school make students confused and difficult to choose which extracurricular activities are more suitable for participation. However, sometimes there are also students choosing extracurricular activities based on many of their friends. Therefore, determining the best school extracurricular activities is the best solution for students as a reference to find which is the best extracurricular activity. The criteria used in this study in choosing the best extracurricular activities are Regional Event Activities, Allocation, Creativity and Talent Channeling. By utilizing SPK, decision makers can make more systematic decisions, based on a deeper understanding of the various alternatives available and relevant criteria. SPK or decision support system is a technique that has the ability to determine a decision using a technical design based on alternatives and predetermined criteria. SPK or decision support system is a technique that has the ability to determine a decision using a technical design based on alternatives and predetermined criteria. In the context of extracurricular school selection, combining the ROC (Rank Order Centroid) and MAUT (Multi-Attribute Utility Theory) methods in a Decision Support System is an interesting approach. The ROC method is used to cluster and rank schools based on certain criteria, while MAUT helps in the calculation of appropriate weights for these criteria. By integrating these two methods, the SPK can provide a more structured guideline in the selection of extracurricular activities that suit students' interests and needs. The research results obtained show that the Futsal alternative is the first recommendation as the best extracurricular with a final value of 0.655086.
Best Sales Selection Using a Combination of Reciprocal Rank Weighting Method and Multi-Attribute Utility Theory Palupiningsih, Pritasari; Setiawansyah, Setiawansyah
Journal of Computing and Informatics Research Vol 3 No 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i3.1496

Abstract

The best salespeople are individuals who are not only able to meet or exceed sales targets, but also demonstrate exceptional skills in building relationships with customers, understanding their needs, and offering effective solutions. The problem of selecting the best salespeople often involves the challenge of an objective and fair assessment, as diverse evaluation criteria can affect the final result. One of the main obstacles is the presence of subjectivity in judgment, which can arise from personal preferences or pressure to maintain good relationships. This study aims to implement a sales performance evaluation model that combines the Reciprocal Rank Weighting and Multi-Attribute Utility Theory (MAUT) methods to obtain a more accurate and objective assessment of sales performance. This research contributes to the management literature and decision support systems by offering a new approach in sales performance evaluation. This opens up opportunities for further research and practical applications in the field of performance evaluation and salesforce management. Based on the final score calculated using the MAUT method, the salesperson rank from best to lowest is as follows: Sales 7 is ranked top with a value of 0.646, indicating the best overall performance. Sales 3 followed in second place with a value of 0.6125, followed by Sales 9 with a value of 0.5604 in third position.
Implementasi Kombinasi Metode ROC dan MAUT Dalam Menentukan Aplikasi Chatting Terbaik Hetty Rohayani; M. Reinaldi; Bister Purba
Journal of Computing and Informatics Research Vol 3 No 3 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v3i3.1500

Abstract

The rapid development of technology makes it easier for humans to communicate with each other more easily by using the best chatting applications. The purpose of this research is to help users who have just used a smartphone to choose the chatting application that suits their needs. The method used in this study is a Decision Support System with Rank Order Centroid (ROC) as the weight value and Multi Attribute Utility Theory (MAUT) as a solution. The alternatives used are Whatsapp, Messager, Discord, Telegram, Line, WeChatting and the criteria used are Security, Storage Media, Network Usage, application features, Display / Interface. The results obtained indicate that the Whatsapp alternative is the first recommendation as the best chatting application with a final value of 0.929456. The Telegram alternative became the second recommendation with a final value of 0.847485 and Line became the third recommendation with a final value of 0,624656.

Page 7 of 9 | Total Record : 88

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