The population of active students in the Informatics Bachelor Program, Universitas Amikom Yogyakarta, odd semester 2021 is 3,870. Efforts to track interest three concentration options were carried out early on through article literacy recommendations. Various articles are produced continuously and provided an ongoing basis students. However, many offered daily make overwhelmed tend choose that ...

This paper explores and studies recommendation technologies based on content filtering user collaborative proposes a hybrid algorithm filtering. method not only makes use of the advantages but also can carry out similarity matching for all items, especially when items are evaluated by any user, which be filtered recommended to users, thus avoiding problem early level. At same time, this takes a...

Microgrids (MGs) offers grid-connected (GC) and islanded (ID) operational modes. However, these dynamic modes of operation pose different microgrid protection challenges. This paper presents a new method for MGs based on discrete one-dimensional recursive Median filter (1-DRMF). In the first step, 1-DRMF is applied measured current signal every single phase individually targeted feature extract...

Web Services (WS) are application components which help in integrating various Web based applications. WS are used by almost all web applications. With the help of WS, web applications can provide service on the internet without any restrictions to the operating system or programming language. Today the number of WS on the internet is rising and it is difficult for the user to select a well sui...

A robust skin detector is the primary need of many fields of computer vision, including face detection, gesture recognition, and pornography filtering. Less than 10 years ago, the first paper on automatic pornography filtering was published. Since then, different researchers claim different color spaces to be the best choice for skin detection in pornography filtering. Unfortunately, no com...

Enabling computer systems to understand human thinking or behaviors has ever been an exciting challenge to computer scientists. In recent years one such a topic, information filtering, emerges to help users find desired information items (e.g. movies, books, news) from large amount of available data, and has become crucial in many applications, like product recommendation, image retrieval, spam...

Collaborative filtering is an often successful method for personalized item selection in Recommender systems. However, in domains where items are frequently added, collaborative filtering encounters the latency problem. Characterized by the system’s inability to select recently added items, the latency problem appears because new items in a collaborative filtering system must be reviewed before...

Now days, huge amount of information is available on the web and it is difficult to user to find relevant information. Recommender systems are very useful to give suggestions. Recommendation quality depends on number of criteria, diversity is one major criterion i.e. recommending less popular and more personalized items. The proposed system uses collaborative filtering and content based recomme...

For recommender systems to be successful, they need to achieve a certain level of accuracy in their recommendations that is acceptable to the users. In order to achieve higher levels of accuracy, several researchers advocated the integration of the collaborative and the content-based filtering approaches [Balabanovic & Shoham 1997, Konstan et al. 1998, Pazzani 1999]. In fact, Pazzani [1999] sho...

User personalization and profiling is key to many succesful Web sites. Consider that there is considerable free content on the Web, but comparatively few tools to help us organize or mine such content for specific purposes. One solution is to ask users to rate resources so that they can help each other find better content: we call this rating-based collaborative filtering. This paper presents a...