Recommender Systems: Past, Present, Future

The origins of modern recommender systems date back to the early 1990s when they were mainly applied experimentally to personal email and information filtering. Today, 30 years later, personalized recommendations are ubiquitous and research in this highly successful application area of AI is flourishing more than ever. Much of the research in the last decades was fueled by advances in machine learning technology. However, building a successful recommender sys-tem requires more than a clever general-purpose algorithm. It requires an in-depth understanding of the specifics of the application environment and the expected effects of the system on its users. Ultimately, making recommendations is a human-computer interaction problem, where a computerized system supports users in information search or decision-making contexts. This special issue contains a selection of papers reflecting this multi-faceted nature of the problem and puts open research challenges in recommender systems to the fore-front. It features articles on the latest learning technology, reflects on the human-computer interaction aspects, reports on the use of recommender systems in practice, and it finally critically discusses our research methodology.

Development and use of a computerized system to track the competency development of family medicine residents: analysis of the convergence between system proposals and assessor decisions

In recent decades, a number of training environments have moved toward program approaches targeting the development of competencies. Because of their complexity, monitoring the development of those competencies is a considerable challenge. Our hypothesis is that a computerized system could help overcome this challenge if it is well accepted by its users. We first summarize the context surrounding the implementation of such approaches. Next, we present a computerized assessment system established in the Family Medicine Residency Program of Laval University (Québec, Canada) that we have developed for tracking the development of residents’ competencies. We then present the analysis of interactions between the system and users and the various proposals that were made to improve the system and longitudinal tracking of the development of the targeted competencies. We consider that this research provides useful guidelines for the computerized monitoring of learners' competencies development and for the design of such systems.

Trend Moment Method to Predict Sales of Pekanbaru Hoya Bread

Hoya or better known as Hoya Bakery is located on Durian Street, Pekanbaru City. Is one of the shops and factories that produce and sell various kinds of bread and market snacks located in various places in Pekanbaru. Especially in meeting the demand that will be distributed to consumers which is relatively large so that there are often out of stock bread and excess stock. Therefore, accurate and efficient predictions of bread sales are needed using the trend moment method. A forecast to produce forecasts of bread supplies in the future. In this study, data on bread sales are used every month from October 2019 to September 2020. The sales record for each month is useful to see whether it has increased or decreased. The result of this research is the creation of a computerized system that is able to generate estimates for the next month using the PHP and MySQL programming languages, making it easier to find out how much bread will be sold and consider how much will be produced in the following month so that there is no shortage or excess stock of bread

Perancangan Sistem Data Hasil Belajar Murid SMA Islam Said Na’um Berbasis Java

SMAI Said Na'um is a senior secondary education institution in the Jakarta area. The system at this school has not used a computerized system optimally so it has several problems. The problems in Said Na'um SMAI include recording values using paper files which take a very long time. Lack of storage media, the data search process takes a little time. The information received is currently less fast and less accurate. Often there are data errors or inaccurate data in making reports. Data storage that is still in the form of physical files can cause damage to data. Based on this information, the research carried out aims to create an information system for learning assessment for students of Said Na'um Senior High School, Central Jakarta. This research was conducted by creating a data system on student learning outcomes at Said Na'um Islamic Senior High School using a Java-based programming language.

Reliability and Efficiency of Computerized Systems for Admission into Colleges of Education Affiliated with the University of Cape Coast

The automated selection system used by colleges of education affiliated to the University of Cape Coast is a multiuser computerized system which students can access and apply to universities at any place with internet access, and can be admitted, rejected, or included in a waiting list for further assessment. The study sought to investigate the extent to which the computerized selection system at educational colleges affiliated with the Cape Coast University has impacted the efficiency and credibility of the process, by evaluating the step by step stages in admission processes that are handled electronically. The study contribute to literature since there is no studies on the reliability and efficiency of Ghanaian colleges of education affiliated to the universities. The type of research design for the study was descriptive design with a quantitative research method. The total population comprises of all admission officers, quality assurance staff, and Heads of departments at the colleges of education affiliated with the University of Cape Coast. The researchers' sample size for the study was one hundred and ninety-two (192). The questionnaire survey was carried out to collect data for the study. Quantitative analysis was done with the use of Statistical Package for Social Sciences. The results show that electronic sorting and selection of applications is efficient in checking the application forms, testing duplicate files, verifying college requirements, and verifying seat availability. The study revealed that there was a positive and high relationship between the efficiency of electronic sorting and selection of admission applications and the reliability of the computerized system.

Convolutional Neural Network for Offline Signature Verification via Multiple Classifiers

The signature process is one of the most significant processes used by organizations to preserve the security of information and protect it from unwanted penetration or access. As organizations and individuals move into the digital environment, there is an essential need for a computerized system able to distinguish between genuine and forged signatures in order to protect people's authorization and decide what permissions they have. In this paper, we used Pre-Trained CNN for extracts features from genuine and forged signatures, and three widely used classification algorithms, SVM (Support Vector Machine), NB (Naive Bayes) and KNN (k-nearest neighbors), these algorithms are compared to calculate the run time, classification error, classification loss and accuracy for test-set consist of signature images (genuine and forgery). Three classifiers have been applied using (UTSig) dataset; where run time, classification error, classification loss and accuracy were calculated for each classifier in the verification phase, the results showed that the SVM and KNN got the best accuracy (76.21), while the SVM got the best run time (0.13) result among other classifiers, therefore the SVM classifier got the best result among the other classifiers in terms of our measures.

Klasifikasi Tekstur Kematangan Buah Jeruk Manis Berdasarkan Tingkat Kecerahan Warna dengan Metode Deep Learning Convolutional Neural Network

Sweet orange is very much consumed by humans because oranges are rich in vitamin C, sweet oranges can be consumed directly to drink. The classification carried out to determine proper (good) and unfit (rotten) oranges still uses manual methods, This classification has several weaknesses, namely the existence of human visual limitations, is influenced by the psychological condition of the observations and takes a long time. One of the classification methods for sweet orange fruit with a computerized system the Convolutional Neural Network (CNN) is algorithm deep learning to the development of the Multilayer Perceptron (MLP) with 100 datasets of sweet orange images, the classification accuracy rate was 97.5184%. the classification was carried out, the result was 67.8221%. Testing of 10 citrus fruit images divided into 5 good citrus images and 5 rotten citrus images at 96% for training 92% for testing which were considered to have been able to classify the appropriateness of sweet orange fruit very well. The graph of the results of the accuracy testing is 0.92 or 92%. This result is quite good, for the RGB histogram display the orange image is good

Rancang Bangun Sistem Informasi Akademik Berbasis Web: Studi Kasus: SD Negeri 18 Tanah Abang

SD Negeri 18 Tanah Abang is one of the elementary schools located in Tanjung Dalam Village. In line with the rapid development of technology, there are demands on educational institutions or others to provide fast, precise, and accurate information. In processing the data, SD Negeri 18 Tanah Abang has not used a computerized system, therefore the research conducted by the author aims to create an Academic Information System so that it can help and facilitate data processing.

Analisis Usability Sistem Komputerisasi Haji Terpadu Palembang Menggunakan Metode System Usability Scale (SUS)

The Palembang Integrated Hajj Computerized System which is currently used as an information system for Hajj and Umrah pilgrims, because the entire data processing process for the purpose of making Hajj documents such as passports, departure and return flights, banking and biodata of prospective pilgrims refers to the integrated computer system. Both internally and externally there has never been an evaluation, either at the time of design, manufacture or implementation. This research was conducted with the title "Usability Analysis of the Palembang Integrated Hajj Computerized System Using the System Usability Scale (SUS) Method". Aims to measure the level of usefulness of the Palembang Siskohat Application and test the validity and reliability using SPSS 24. System Usability Scale (SUS) With 16 questions as a benchmark for assessing the application. 30 respondents were selected among the administrative staff of the Hajj and Umrah pilgrims in Palembang. The results of the usability test showed the value of Learnibilty 4.68, Efficiency 4.46, Memorabilty 4.64, Error 3.34 Satisfaction 3.74, the average usability value was expressed by Very good reliability and validity on each variable indicate that the questionnaire for each variable has a fairly good level of reliability.