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International Journal Artificial Intelligent and Informatics
Published by Research and Social Study Institute
ISSN : -     EISSN : 2622626X     DOI : https://doi.org/10.33292
Core Subject : Economy, Science,
Computer Science & IT Economics, Econometrics & Finance
International Journal of Artificial Intelligence and Informatics is a scientific journal dedicated to the exploration of theories, methods, and applications of artificial intelligence in time series analysis, forecasting, and prediction. This journal serves as a platform for researchers, academics, and practitioners to publish their work on predictive models applied to various time-dependent phenomena. Topics within the journal’s scope include, but are not limited to: 1. Predictive Methodologies and Models Deep learning models for forecasting (LSTM, GRU, Transformer, etc.) Machine learning algorithms for time series forecasting (ARIMA, SARIMA, XGBoost, etc.) Optimization of forecasting models using metaheuristic approaches (PSO, GA, etc.) Hybrid models for improving prediction accuracy Statistical methods and Bayesian approaches in forecasting 2. Applications of Time Series and Forecasting Across Various Fields Financial and stock market prediction Weather forecasting and climate change analysis Energy demand forecasting and resource management Time series analysis in healthcare and epidemiology Forecasting in manufacturing and supply chain management User behavior prediction in e-commerce and social media 3. Data and Infrastructure for Forecasting Big data management in time series analysis Streaming data and real-time forecasting Explainable AI (XAI) in predictive models Data augmentation and synthetic data for forecasting The journal welcomes research articles, review papers, and case studies that provide significant contributions to the development of theories and implementation of predictive systems based on artificial intelligence.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
 1 
Search results for , issue "Vol 1, No 1 (2018)" : 5 Documents clear
The design of information technology strategic plans in educational institutions Astuti, Dwi; Winarno, Wing Wahyu; Sofyan, Amir Fatah
International Journal Artificial Intelligent and Informatics Vol 1, No 1 (2018)
Publisher : Research and Social Study Institute (ReSSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (559.155 KB) | DOI: 10.33292/ijarlit.v1i1.2

Abstract

Strategic Plan, which is usually taken from Vision, Mission, Objectives, Policies, Programs and activities that are oriented towards the goal for a certain period relating to the main tasks and functions of the Agency / Institution, prepared by consider the developments of strategic environment, the sustainability of organization without strategic plan will not be directed and guaranteed because there are no management guidelines and system improvements in order to increase the competition with other business actors. STMIK Bina Patria is a private university (PTS), but it does not have an information system (SI) strategic plan. The information system contributes to improve the quality of students’ services, operational efficiency, and students’ satisfaction. With SI / IT, the monitoring, coordination, and decision can be performed effectively. The goal can be achieved if the organization has a clear plan. And, researchers make an IT strategic plan for STMIK Bina Patria according to the TOGAF Framework with data analysis methods of Value Chain, Critical Success Factors, and SWOT. The analysis results showed that by the availability of 4 applications, 3 applications do not require any improvement, namely SI-KEU, E-LEARNING and E-JOURNAL. In contrast, an application which is SI-AKAD requires additional features. There were 5 proposed applications to be built, namely SI-PMB, SI-ALUMNI, SI-MUTU, SI-PERPUST and SI-DASHBOARD. All of application proposals are mapped into the application development roadmap within the next 5 years.
Implementation of topsis algorithm for evaluating lecturer performance Fatkhurrochman, Fatkhurrochman; Kusrini, Kusrini; Alfatta, Hanif
International Journal Artificial Intelligent and Informatics Vol 1, No 1 (2018)
Publisher : Research and Social Study Institute (ReSSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (497.939 KB) | DOI: 10.33292/ijarlit.v1i1.3

Abstract

Higher education is an education unit that able to carry out academic, professional and / or vocational programs. Lecturers are professional and scientific educators with the main task of transforming and developing, and disseminating science, technology and art through education, research and community service. The performance evaluation applies seven criterias, namely: attendance, teaching, research, dedication, loyalty, cooperation and responsibility. The problems are; the lecturers’ performance evaluation is not optimal yet because there is no specific method to implement it. Therefore, it is necessary to build a decision support system by applying the Technique For Others Reference by Similarity to Ideal Solution (TOPSIS). This system will later help us in determining the best lecturer in accordance with the regulation. The TOPSIS method uses the principle that the chosen alternative must have the longest (farthest) distance from the negative ideal solution from geometric point of view using the relative proximity of an alternative. The alternative means the lecturers’ performance with predetermined criterias. This method produces a lecturers rankings based on the best performance on numerical scores and sorted by the greatest preference scores. The particular study used 5 lecturers as alternative to be tested. They were Lecturers 1, Lecturers 2, Lecturers 3, Lecturers 4, and Lecturers 5. The results showed that Lecturer 1 was the best lecturer with the biggest preference score of 0.612.
Determination of receipt of UPZ assistance using the SAW method Listyanto, Ahmad Wildan; Kusrini, Kusrini; Sudarmawan, Sudarmawan
International Journal Artificial Intelligent and Informatics Vol 1, No 1 (2018)
Publisher : Research and Social Study Institute (ReSSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (693.21 KB) | DOI: 10.33292/ijarlit.v1i1.9

Abstract

Zakat has a very strategic position in giving the impact of welfare and improving the community's economy if the collection and distribution are managed in trustworthy, transparent and professional. An institution on zakat management is National Zakat Agency (BAZNAS), which an institution manages the zakat management nationally, and non-structural government institution that is independent and responsible to President through the Minister of Religion. BAZNAS is located in capital city and assisted by zakat collection unit (UPZ). Along this time, they conduct manually in determining the person who will receive the assistance, but it often occur errors in its implementation. Therefore, a decision support system is needed to assist UPZ in determining the person who will receive the assistance. The decision support system was designed using SAW (Simple Additive Weighting) method, then the administrators obtain an alternative data in the form of lists of students who receive the UPZ assistance. The SAW algorithm is an algorithms for decision making. The SAW algorithm is also known as an algorithm with additive weighting method. The method requires normalization process of decision matrix (x) into a scale and can be compared to the entire available alternative ratings. The study showed that SAW can be applied to determine the acceptance of UPZ assistance by the calculation results of 16. The result of calculation and recommendation of decision support system for person who receive the UPZ acceptance, have the same data on output, namely Astin Dwi Wulan.
Calculating vehicle intensiveness increase on eid al-fitr day with anfis method Pratama, Rendy Bagus; Utami, Ema; Wibowo, Ferry Wahyu
International Journal Artificial Intelligent and Informatics Vol 1, No 1 (2018)
Publisher : Research and Social Study Institute (ReSSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (266.592 KB) | DOI: 10.33292/ijarlit.v1i1.10

Abstract

the number of motorized vehicles increases every year, especially private vehicles and is not offset by inadequate access until the road becomes more crowded, even traffic jams occur, especially during public holidays and national holidays. for example, during eid holidays there is a density of traffic flow when going back and forth every year, with the development of current technology the density of traffic flows that occur can be calculated so that it will be easier to anticipate in the future. but in this study only will examine the parameter values that cause the vehicle to occur density and accumulation, because it can be developed with parameter values so that the results can be obtained efficiently in solving traffic density. From the results of the anfis method, efficiency is obtained, namely on h-1 and h days of 2014, and 2017 can use Parameters with magins of 6,3% and 4,32%, while 2015 and 2016 can use parameters with margins 1,79% and 0,79%. and for the h + 1 day of 2014, 2016, and 2017, it is more efficient to use parameters with margins 1,4% and only parameters in 2015 which have the efficiency value using parameters with margin -6,17. anfis application in this calculation can be developed in a prediction system.
Face recognition methods analysis Zarei, Shima
International Journal Artificial Intelligent and Informatics Vol 1, No 1 (2018)
Publisher : Research and Social Study Institute (ReSSI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (452.231 KB) | DOI: 10.33292/ijarlit.v1i1.13

Abstract

Face Recognition is one of the most important issues in Image processing tasks. It is important because it uses for various purposes in real world such as Criminal detection or for detecting fraud in passport and visa check in airports. Face book is a nice example of Face recognition application, when it sends notification to one user’s friends who are recognized by their images that user uploaded in face book page. To solve Face Recognition problem different methods are introduced such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Hidden Markov Models (HMM) which are explained and analyzed. Also algorithms like; Eigen face, Fisher face and Local Binary Pattern Histogram (LBPH) which are simplest and most accurate methods are implemented in this project for ATT dataset to recognize the most similar face to other faces in this data set. To this end these algorithms are explained and advantages and disadvantages of each one are analyzed as well. Consequently, the best method is selected with comparison between the results of face reconstruction by Engine face, Fisher face and Local binary pattern histogram methods. In this project Eigen face method has best result. It should be noted that for implementing face recognition algorithms color map methods are used to distinguish the facial features more precisely. In this work Rainbow color map in Eigen Face algorithm and HSV color map in Fisher Face algorithm are utilized and results shows that HSV color map is more accurate than rainbow color map.

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