IntroductionThe rapid development of information technology makes the data communication and information delivery technology most effective. Moreover, this development has considerable advantages in every field of life, especially in education sector. Qomaruddin [1] proposed that using e-learning has many advantages over conventional learning, such as: quick feedback to students, saving of time in marking, consistently in marking and improve monitoring in students. While there are numerous e-learning solutions available today, the differentiating factors are the innovative instructional design and custom content development process [2]. Furthermore, to establish learning and development theories in web based learning, the system design should able to recognize the individual learning requirements [3]. The system has to recognize the individual requirements for ergonomic reasons, or adaptations to learning styles for an easier introduction into a topic.In the context of e-learning, the adaptation is about creating a learner experience that purposely adjusts to various conditions over a period of time with the intention of increasing success for the effectiveness of e-learning application. The adaptation concept in e-learning application has been on the e-learning research agenda for well over three decades in different research topics such as intelligent tutoring systems [4], adaptive hypermedia [5][6][7] and Multiagent systems [8] often based upon an instructional design model or guidelines and concept understanding. Linawati [9] explain that the students wer satisfied with adaptive hypermedia courseware, their academic achievement were rise significantly and the dropout rate were diminished.Meanwhile, several studies have focused on the pedagogical aspect of e-learning systems over the past few years, but they have provided insufficient guidelines for e-learning designers [10]. The development of e-learning standards is a complicated, time-consuming, and challenging process. Some projects have focused on determining the standard architecture and format for learning environments, such as IEEE learning technology systems architecture (LTSA), instructional management systems (IMS), and sharable content object reference model (SCORM) [11].Nowadays, the standardizations of e-learning application are abundant and cover all aspects of e-learning and distance education, from representation, packaging, and publishing of learning objects (LOs); to metadata that describe LOs. Furthermore, some standards
Computerized Adaptive Test (CAT) is a computer-based test framework which has ability to customize questions items given to the learner based on their estimated ability. In this research, the CAT system is build using Item Response Theory (IRT) techniques to develop an adaptive system based on question item's difficulty level and students' ability level. Moreover, to figure out the effectiveness of this CAT system, we do some experiments by comparing the average post-test score of students in CAT system and conventional system. The experiments result reveals that the average post-test score of students in the CAT system is much higher than the average post-test score of students in traditional test system.
Indonesia is an archipelagic country with a coastline of about 81,000 km and has a variety of very large biological and non-biological resources. Position as an archipelagic country with a very wide sea causes each region to have the potential to produce salt. The Covid-19 pandemic has resulted in various negative impacts on several fields such as the economy, social, SMEs and community services. Covid-19 has also resulted in a decrease in salt production and farmers also have difficulty marketing it. The research problem is the large number of salt farmers and number of indicators in providing assistance so that a model for measuring performance of salt farmers is needed. This performance measurement model is guided by several indicators, namely land area (K1), production result (K2), business capital (K3), and marketing system (K4). The method used Interval type-2 Fuzzy Analytic Hierarchy Process (IVFAHP). IVFAHP is used to determine indicators that most influence measurement of salt farmers. This study aims to build a model for measuring performance of salt farmers to increase economic productivity and ability of human resources to deal with COVID-19 pandemic. The contribution is a group-based decision by developing the fuzzy interval type-2 method with triangular fuzzy number (TFN) one midpoints. The findings from study are that the most influential indicators in dealing with COVID-19 pandemic are business capital and salt marketing. This research also produces recommendations for improvement salt farmers in an effort to increase salt production.
The Covid-19 pandemic has had an impact on domestic economy, such as a decrease in people’s consumption and purchasing power, a decline in company performance, as well as SMEs. This situation, SMEs sector controls 99.99% of all existing businesses, employs 97.16% of private sector workforce, and contributes 57.5% to Indonesia’s gross product. Various government program efforts in helping Batik SMEs players face Covid-19 pandemic so that they are right on target. The large number of SMEs in Bangkalan is around 166,768, causing department to find it difficult to determine recommendations for improvement for each MSME. Based on these problems, a cooperative model for the SMEs industry is needed so that official work program runs smoothly on target. The method used is FAHP and TOPSIS integration method, FAHP method is used to determine weighting and TOPSIS method is used for ranking and recommendations for improvement. The advantage of FAHP is consistency index to control error rate of decision. TOPSIS method is capable of making multi-criteria decisions based on alternative SMEs industry mapping process. The purpose is make a recommendation model for improvement using hybrid method of FAHP and TOPSIS with balanced scorecard indicators for learning and growth perspective. The research contribution is to make decisions based on group recommendations and consistency ratio (CR) is less than 0.1. The findings research, that the influential indicators are batik business ownership and variations of batik motifs. The recommendations for improvement, the average MSME still does not have branding.
Madura is one of the regions in East Java Province whose economy is supported by the SME sector. Industrial Revolution 4.0, this refers to the concept of using the internet for various things, as well as cloud-based and smart manufacturing. The agency has difficulty in identifying needs of Batik UKM, so a performance recommendation model for Batik SMEs is needed to assist Dinas and UKM players in making decisions to determine the performance improvement of Batik SMEs. The purpose of this study is to determine recommendations by measuring the performance of MSMEs in facing the industrial revolution 4.0. This performance measurement is based on 9 indicators, namely Employee Training or SME owners, Number of Batik Motif Variations, Number of Consumers, Product Brands or Branding, Owner Education, Number of Information Technology Certified Employees, Owning a Markerplace, Online Marketing, and Online Payment. The method used in this research is the FANP method. Fuzzy has excellent performance, the decision-making process is more flexible, and is able to handle data that contains uncertainty and inaccuracy by making decisions based on many criteria. The advantage of ANP is that there is dependence and feedback between each criterion, so that all criteria are calculated proportionally. The results of this study are the weighting of priority indicators on all indicators that affect the industrial revolution 4.0. Based on the research and consistency ratio tests, the main indicators needed for SMEs in Bangkalan Madura to face the industrial revolution 4.0 are marketplace, online marketing and information technology certified employees.
The need for domestic salt every year has increased, both for consumption and industrial salt. Some of the fisheries service programs include providing assistance to people's businesses, providing geomembrane, and online marketing training. A large number of salt farmers and official work programs have caused the implementation of the program to be less than optimal, resulting in low salt production. This study uses a type-2 fuzzy method by integrating two methods, namely type-2 Fuzzy Analytical Hierarchy Process AHP (FAHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Fuzzy type-2 has higher accuracy than fuzzy type-1 and is more efficient and more flexible in determining the linguistic scale for criteria. The Fuzzy Analytical Hierarchy Process AHP (FAHP) interval is used to determine the weight of the salt farmer mapping criteria. Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS), used to determine. The findings of this study are that the indicators that most influence the mapping of salt farmers are land area, marketing, and market. The results of the mapping of salt farmers are the classification of salt farmer class groups and recommendations for improvement for each salt farmer. Hybrid type-2 Fuzzy Analytical Hierarchy Process AHP (FAHP) method and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), can be used for mapping salt farmers based on the consistency ratio value below 10 percent, 37 percent enter high class, 28 percent enter the middle class and 35 percent enter low class
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