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International Journal of Informatics and Data Science
Published by ADA Research Center
ISSN : -     EISSN : 30267315     DOI : -
Core Subject : Science,
Computer Science & IT
International Journal of Informatics and Data Science publishes manuscripts of Computer Science, but is not limited to the fields of: 1. Natural Language Processing Pattern Classification, 2. Speech recognition and synthesis, 3. Robotic Intelligence, 4. Big Data, 5. Informatics Techniques, 6. Image and Speech Signal Processing, 7. Data Mining 8. Decision Support System, 9. Experts System, and 10. Cryptography
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 15 Documents
 1   2 
Application of OCRA Method with ROC Weighting in Selection of Best Prudential Agent Artha Uliana Sinaga; Mesran Mesran
International Journal of Informatics and Data Science Vol. 1 No. 1 (2023): December 2023
Publisher : ADA Research Center

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Abstract

The problem that often arises is the gap in the selection of the best agents which was previously influenced by a lack of objectivity in recruiting, and many agents do not match the existing knowledge and criteria. The impact is a discrepancy in selecting the best agent with predetermined criteria, resulting in stagnation and disrupting overall operations. This condition risks damaging the smooth operation and disrupting the achievement of the desired goals. Thus, it is necessary (DSS) to assist in the process of selecting the best agent. The solution is to apply the OCRA method using ROC weighting. The application of the OCRA method with ROC weighting is expected to provide an optimal solution in selecting the best agent based on predetermined criteria. This method was chosen because it is able to determine the weight value for each attribute. From the preference assessment, it can be seen that the value of 0.833 has the highest value. Therefore, it can be concluded that in the tenth alternative (A10), there is a choice that is considered the best agent. This choice was given to Lastri Simbolon, who was ranked as the best agent.
Decision Support System for Selecting the Best Chat Application using the TOPSIS Method Cindy Nanda Sari; Rosnizam; Mesran Mesran
International Journal of Informatics and Data Science Vol. 1 No. 1 (2023): December 2023
Publisher : ADA Research Center

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Abstract

Chat applications are features that allow users to send and exchange messages with others using an internet connection as a means of communication. However, with the increasing number of chat application features available today, smartphone users often complain and feel confused when choosing the best chat application feature. Considerations need to be made in determining the best chat application feature to help smartphone users find solutions to handle incompatible chat application features. With chat application features, individuals can communicate over long distances without worry, as chat applications not only support text-based communication but also enable image sharing, text messaging, voice messages, and video calls. This research involves five criteria: storage, security, user interface, application features, and network usage. The Decision Support System (DSS) aims to facilitate and solve problems by selecting the best chat application through the TOPSIS method. The result of the highest ranking is WhatsApp with a score of 0.9113. The use of the TOPSIS method in this research helps generate the best alternative with accurate and high-quality values.
Pharmacist Acceptance Decision Support System Applying AHP and COPRAS Methods Siska Zega; Mesran Mesran
International Journal of Informatics and Data Science Vol. 1 No. 1 (2023): December 2023
Publisher : ADA Research Center

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Abstract

A pharmacist is a profession that is responsible for drugs both synthetic and herbal for the purpose of human health, namely starting from designing drugs, producing them, distributing them, monitoring whether the drugs prescribed by doctors are appropriate and of high quality and safe for patients. Qualified pharmacists will make it easier for companies to select pharmacists during the recruitment process. The pharmacist recruitment process requires a professional and accurate way to produce human resources that can support the quality and success of an organization. Pharmacist recruitment usually takes a long time, because the organization or company must first carefully examine and select the criteria and requirements completed by prospective pharmacists. Seeing this situation, in selecting pharmacist acceptance, a decision support system (SPK) is needed so that pharmacist acceptance can be carried out more accurately, quickly and not subjectively. Decision-making techniques using the Analytic Hierarchy Process (AHP) method developed by Thomas L Saaty are to help solve complex problems by compiling a hierarchy of criteria, subjectively assessed by interested parties and then draw various considerations to develop weights or priorities, while decision-making techniques using the COmplex PRoportional ASsessment (COPRAS) method are used to assist decision-making in making decisions on several alternative decisions to get an accurate and optimal decision. The final results obtained Billy Surkawi, S.Farm, is a pharmacist candidate who has the first highest score with a final score of 100.00, and second place Nurul andini, S.Farm with a final score of 93.66. So that the two pharmacist candidates can be proposed to become pharmacists from the results of the selection carried out.
Application of the ANN Algorithm to Predict Access to Drinkable Water in North Sumatra Regency/City Muhammad Alfahrizi Lubis; Deza Geraldin Salsabilah Saragih; Indah Dea Anastasia; Agus Perdana Windarto; Putrama Alkhairi
International Journal of Informatics and Data Science Vol. 1 No. 1 (2023): December 2023
Publisher : ADA Research Center

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Abstract

The increase in population has an impact on increasing the need for drinking water, but this is not in line with the fact that not 100% of the people in Indonesia physically receive or consume safe drinking water. This analysis is based on data from the Central Statistics Agency to look at the social, economic and demographic factors of households regarding the availability of adequate physical quality drinking water. This research aims to predict the percentage of households that have access to adequate drinking water using the Artificial Neural Network (ANN) method. The technique used is Backpropogation. Backrpopagation is a supervised neural network training method, it evaluates the error contribution of each neuron after a set of data has been processed. The goal of backpropagataion is to modify weights to train a neural network to map arbitrary inputs to outputs correctly. Therefore, looking at the above problems, this research aims to determine access to adequate drinking water sources by predicting which households have adequate drinking water so that there is no lack of adequate drinking water sources in the City Regency area. Methods and basic data are needed to make predictions. In this research, data was obtained from BPS which used data from 2014 - 2021, with training data from 2014 - 2020 and testing data from 2015 - 2021. Based on the best architecture produced in this research, namely the 6-17-1 architecture with an accretion of 90%. Thus it can be concluded that the Backpropagation Neural Network can provide good accuracy in carrying out the prediction process.
Decision Support System for Determining New Branch Locations Applying the Multi Attribute Utility Theory (MAUT) Method Muhammad Zakaria Lubis; Ruziana; Rizkah Fadillah; Ridha Maya Faza Lubis
International Journal of Informatics and Data Science Vol. 1 No. 1 (2023): December 2023
Publisher : ADA Research Center

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Abstract

The location of new branches that are close to community activities and have adequate facilities makes it easier for consumers to get the services and products they need. Determining the feasibility of new branch locations from several product or service producers still uses a system that is not accurate, which can cause problems in determining the location of new strategic and targeted branches. However, there are several obstacles in the selection of new branch locations, so technological assistance is needed in determining the location, product analysis, marketing management, and other matters concerning the development of the business being carried out. Technology that is considered efficient, easy, and flexible and is used by entrepreneurs, especially in determining the location of new branches using a decision support system using the MAUT method, is expected to help the location of new branches that are efficient and strategic. The decision support system is a conclusion and determination of the best using some data and computerized testing in each criterion so as to get valid results. After calculating each criterion and alternative, the best ranking is obtained in alternative A1 with a value of 0.7925 on Pertahanan Street.
Clustering of YouTube Viewer Data Based on Preferences using Leiden Algorithm Erlin Windia Ambarsari; Aulia Paramita; Desyanti
International Journal of Informatics and Data Science Vol. 1 No. 2 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v1i2.45

Abstract

This study aims to analyze YouTube viewer engagement patterns by applying the Leiden algorithm for clustering based on user interactions such as likes, dislikes, and subscription behaviors in correlation with video duration. Therefore, the method that we used begins with data cleaning to ensure completeness, followed by selecting relevant features and applying z-score normalization to equalize their contributions. A similarity graph is constructed using cosine similarity, representing instances as nodes and their relationships as edges. The Leiden algorithm is then applied to optimize modularity and extract clusters, with results integrated into the original dataset for analysis. Dimensionality reduction using PCA facilitates cluster visualization, while statistical summaries and distribution plots provide deeper insights into cluster characteristics. Subsequently, we obtained a dataset sourced from the YouTube content creator @ArmanVesona, which includes 237 instances with ten features: Shares, Comments Added, Dislikes, Likes, Subscribers Lost, Subscribers Gained, Views, Watch Time (hours), Impressions, and Click-Through Rate (%). The analysis reveals two distinct clusters: Cluster 0, characterized by lower engagement and stable audience, and Cluster 1, exhibiting higher engagement but higher subscriber churn. The findings highlight the effectiveness of the Leiden algorithm in detecting well-connected communities and provide insights into viewer behavior, aiding in the development of improved content strategies and targeted marketing approaches.
Customer Service Recruitment Decision Support System Applying MAUT Method Ruziana binti Mohamad Rasli; Mesran; Febrianus Gea; Setiawansyah
International Journal of Informatics and Data Science Vol. 1 No. 2 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v1i2.46

Abstract

Customer service is a service provided by the company to consumers who are controlled online or offline by employees of the company, either before or after purchasing products or services. Eligibility in recruitment is very important where a customer service must be able to have good and clear public speaking so that it has an impact on customers. The expected labour problem is not easy and simple, this is because the process is still manual and only based on career level, age and experience. Where, these problems also lack qualified human resources and this makes the recruitment process inaccurate and in accordance with the desired demands.  So the solution is provided through a decision support system, a highly interactive computer-based system that assists in making a decision to utilise data and models in solving unstructured and semi-structured problems. In making decisions apply the MAUT method. In this research conducted using the Multi Attribute Utility Theory (MAUT) Method which is able to obtain maximum results to obtain superior recruitment personnel, namely alternative A1 with a result of 0.8975 as the top alternative after going through the method application stage.
Application of EDAS Method with Entropy Weighting in Performance Assessment of the Best Student Activity Unit Uswatun Hasanah; Mesran; Rian Syahputra
International Journal of Informatics and Data Science Vol. 1 No. 2 (2024): June 2024
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v1i2.52

Abstract

The Student Activity Unit (UKM) is an institution formed as a forum for all student activities in developing the interests, talents, creativity and expertise of its members. Performance appraisal is needed to evaluate every achievement and motivate SMEs. Based on the results of interviews conducted with the Vice Chancellor III for Student Affairs at Budi Darma University, he explained that the performance assessment of SMEs at Budi Darma University is still based on the activity of SMEs on campus and has not used other criteria that are clearer and more structured when assessing the performance of the best SMEs at Budi Darma University. . This is certainly less effective and prone to errors. Therefore, a Decision Support System (DSS) is needed as a solution to overcome these problems. In this study, the Entropy method and the EDAS method were applied to 5 criteria and 8 alternatives. Then the alternative chosen according to the criteria for evaluating the performance of the best UKM at Budi Darma University is in alternative A4 with a score of 0.9685, namely SSBD (Sanggar Seni Budi Darma).
Decision Support System for Selecting the Best Graduates of Undergraduate Students Using the Analytical Hierarchy Process (AHP) Method Telaumbanua, Lucius Yupiter; Siregar, Realdo Alfonsius
International Journal of Informatics and Data Science Vol. 2 No. 2 (2025): June 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v2i2.28

Abstract

The selection of top graduates is a crucial process in higher education, aiming to reward students who demonstrate the best performance during their studies. However, in practice, this process often only considers academic grades such as the Grade Point Average (GPA), without considering other factors such as organizational activity, non-academic achievements, or student attitudes and ethics. This can lead to unfairness and subjectivity in decision-making. This study aims to develop a Decision Support System (DSS) to assist the selection process of top undergraduate graduates objectively and measurably using the Analytical Hierarchy Process (AHP) method. AHP is used to determine the weight of each criterion based on its relative importance through pairwise comparisons. The criteria used include GPA, academic and non-academic achievements, organizational activity, and student behavior. This system provides a final result in the form of a graduate ranking based on the highest score. Test results indicate that the system is able to improve accuracy and transparency in the selection process of top graduates. This research is expected to become an information technology solution that supports fair and data-based decision-making in higher education.
Decision Support System for Selecting Student Recipients of Single Tuition Fee (STF) Assistance using Multi-Objective Optimization on the Basis of Simple Ratio Analysis (MOOSRA) Method Sihombing, Johannes Syahputra; Naibaho, Dahner Junedi; Mesran
International Journal of Informatics and Data Science Vol. 2 No. 2 (2025): June 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/ijids.v2i2.29

Abstract

Single Tuition Fee (STF) is a tuition fee borne by each prospective new student based on their economic capability. The process of determining the STF groups requires precision and time, as student data needs to be compared with the STF criteria one by one. The decision-making system in determining the STF groups that exist currently utilizes five criteria in assessing the parents' ability to pay for their child's education, namely: Parental Income, Possession of PKH Card, Document Completeness, Parental Dependents, and Academic Performance. Therefore, a decision support system is needed that applies the MOOSRA method to assist in determining the STF groups. There are five criteria used in this research: parental income, ownership of the PKH card, document completeness, parental dependents, and academic performance. The calculation results for several sample data yield the best final optimization value in the selection of students eligible for STF assistance, which is found in alternative A7 (Meli) with a total score of 0.863.

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