Associated Patterns in Open-Ended Concept Maps within E-Learning

A concept map is a diagram that visualizes the structure of individual cognitive knowledge. An approach to creating a concept map structure that allows users to contribute concepts and linkages that express their understanding freely is known as an "open-ended concept map." It has been demonstrated that an open-ended concept map accurately depicts student knowledge structures and reveals student differences. However, manually analyzing an open-ended map is difficult, time-consuming, and includes many propositions, especially in a big classroom. Educational data mining could be used to further process and analyze a collection of concept maps. However, many works attempted to employ data mining in order to produce concept maps structure from text documents rather than examining the knowledge representation. This study aimed to identify hidden students' knowledge representation combination patterns using association rules analysis. The dataset used in this study consisted of 27 open-concept maps created by university students. This study found interesting patterns that reveal students' knowledge in understanding the material given by the teacher

The performance of text similarity algorithms

Text similarity measurement compares text with available references to indicate the degree of similarity between those objects. There have been many studies of text similarity and resulting in various approaches and algorithms. This paper investigates four majors text similarity measurements which include String-based, Corpus-based, Knowledge-based, and Hybrid similarities. The results of the investigation showed that the semantic similarity approach is more rational in finding substantial relationship between texts

PEMBELAJARAN BERBANTUAN KOMPUTER UNTUK ANAK KESULITAN MENULIS (DISGRAFIA)

Salah satu kendala dalam pencapaian pendidikan untuk semua adalah masih minimnyalayanan pendidikan bagi anak berkesulitan belajar. Kondisi ini mengakibatkanpenurunan kualitas pendidikan nasional yang berdampak pada pembangunan sumber dayamanusia. Makalah ini mengemukakan pengembangan aplikasi pembelajaran berbantuankomputer berbasis web untuk meningkatkan layanan pendidikan bagi anak yang mengalamikesulitan belajar menulis (disgrafia). Metode yang digunakan pada penelitian ini adalahmetode pengembangan yang melibatkan validitas materi dan media . Hasil implementasidan pengujian memperlihatkan bahwa aplikasi yang dikembangkan dapat dimanfaatkan untukmembantu anak-anak yang mengalami kesulitan belajar menulis

KESIAPAN PEMBELAJARAN BERBASIS BUKU DIGITAL

Penggunaan buku digital di dalam pembelajaran sangat strategis dan mampu mengurangi kelemahan-kelemahan yang ada pada buku cetak. Sebagai terobosan baru, agar penerapan buku digital bisa maksimal maka diperlukan penelitian mengenai kesiapan pebelajar. Tulisan ini mengungkapkan kesiapan pembelajaran berbasis buku digital dengan format ePub di program studi Pendidikan Teknik Informatika Universitas Negeri Malang (UM). Metode penelitian yang digunakan adalah deskriptif kuantitatif. Hasil penelitian memperlihatkan sebanyak 92,22% responden menyatakan memiliki peralatan untuk mengakses buku digital, siap menggunakan, dan mengembangkan buku digital di dalam pembelajaran

Improving Knowledge Structure through Extended Scratch-Build Concept Mapping

Extended concept mapping is a potential technique to elicit missing ideas and relationships. This study explored an Extended Scratch-Build (ESB) concept mapping in improving learners' knowledge structure. ESB is an expansion of an open-ended approach that asks students to connect the prior-existing original concept map with the new additional map on related material topics. The practical use of ESB has been conducted and proves positive effects on learning achievements. However, no information has been provided regarding the performance of the concept map components that describe the broad overview of students' attainments. This observational study focused on improving learners' knowledge using quantity measurements based on concept map features, consists of a number of concepts, number of links, and a number of propositions. University students (N = 27) with a major in Informatics Engineering participated in the study. The results reported that students' knowledge structure on additional maps significantly increased compared to the prior original map

Web-based Campus Virtual Tour Application using ORB Image Stitching

Information disclosure in the digital age has demanded the public to obtain information easily and meaningful. In this paper, we propose the development of web-based campus virtual tour 360-degree information system application at the State University of Malang, Indonesia which aims to introduce the assets of the institution in an interesting view to public. This application receives a stitched or panoramic image generated through the ORB image stitching algorithm as an input and displays it in virtual tour manner. This paper realizes the image stitching algorithm to present the visualization of the 360-degree dynamic building and campus environment, so it looks real as if it were in the actual location. Virtual tour approach can produce a more immersive and attractive appearance than regular photos

Feature Space Augmentation for Negation Handling on Sentiment Analysis

One crucial issue affecting the performance of sentiment analysis tasks is negation. Handling negation involves determining the negation scope and negation cue. Feature space augmentation is one approach used to address negation. Feature space augmentation has been carried out by some previous researchers using a negation flag with the rule that the negation scope includes all words from the explicit negation cue to the punctuation mark. This study aimed to analyze the classifier's performance when negation handling was applied by adding a new rule for the negation scope. The new rule for determining the negation scope no longer took all words from the negation cue to the punctuation mark, but only considered or ignored words with certain POS tags. The results of this study showed that using the new rule for negation scope contributed to improving the performance of the classifier in sentiment analysis tasks. The proposed approach for negation handling was better than the previous approach in terms of accuracy, precision, recall, and f1-score

ORANGEO : PEMANFATAAN TEKNOLOGI WIRAUSAHA WISATA OUTBOND DALAM PEMBERDAYAAN MASYARAKAT DISEKITAR KEBUN JERUK DESA SELOREJO DAU MALANG

 Abstrak Program pemberdayaan masyarakat dalam membentuk wirausaha baru dengan konsep techno-entrepreneurship meningkatkan produk dan jasa. Program  yang dirancang mimiliki guna dan  nilai jual dalam menyelesaikan persoalan ekonomi kerakyatan dan permasalahan sosial yang ada di desa Selorejo Dau Malang. Program pengembangan SDM dan potensi yang dimiliki oleh warga sekitar area lokasi kegiatan sangat mendukung menimbulkan jiwa wirausaha dengan melalui jasa outbond bagi anak-anak sekolah sebagai game edukasi dengan pembuatan produk olahan jeruk menjadi produk permen dan makanan menarik bagi anak-anak.             Pengembangan potensi desa dan pemuda dalam mengelolah perkebunan jeruk selain sebagai lokasi wisata petik jeruk di desa ini perlu peningkatan kegiatan wirausaha juga sebagai layanan edukasi anak-anak dan pengenalan karakter dengan nuansa wisata alam. Tujuan kegiatan pengabdian ini adalah memberikan peluang usaha bagi masyarakat dalam usaha kreatifitas pengembangan produk hasil perkebunan jeruk dengan mengolah jeruk yang memiliki kualitas rendah menjadi produk yang bernilai dengan gizi yang baik di desa Seleroje Dau Malang. Usaha ini dikembangkan dengan teknologi tepat guna (perancangan alat-alat proses pengolahan jeruk menjadi makanan kesukaan anak-anak). Program  dapat dijadikan sebagai kegiatan masyaralat dalam membentuk life skill secara tidak langsung dapat digunakan untuk pengembangan usaha yang kedepannya berkesinambungan sebagai pusat pengelolaan hasil olahan jeruk di Malang.  Kata kunci— techno-entrepreneurship, game edukasi, pengolahan jeruk, life skill

Detecting emotions using a combination of bidirectional encoder representations from transformers embedding and bidirectional long short-term memory

One of the most difficult topics in natural language understanding (NLU) is emotion detection in text because human emotions are difficult to understand without knowing facial expressions. Because the structure of Indonesian differs from other languages, this study focuses on emotion detection in Indonesian text. The nine experimental scenarios of this study incorporate word embedding (bidirectional encoder representations from transformers (BERT), Word2Vec, and GloVe) and emotion detection models (bidirectional long short-term memory (BiLSTM), LSTM, and convolutional neural network (CNN)). With values of 88.28%, 88.42%, and 89.20% for Commuter Line, Transjakarta, and Commuter Line+Transjakarta, respectively, BERT-BiLSTM generates the highest accuracy on the data. In general, BiLSTM produces the highest accuracy, followed by LSTM, and finally CNN. When it came to word embedding, BERT embedding outperformed Word2Vec and GloVe. In addition, the BERT-BiLSTM model generates the highest precision, recall, and F1-measure values in each data scenario when compared to other models. According to the results of this study, BERT-BiLSTM can enhance the performance of the classification model when compared to previous studies that only used BERT or BiLSTM for emotion detection in Indonesian texts

Development of Mobile Based Educational Game as a Learning Media for Basic Programming in VHS

The purpose of this research is to develop mobile based education game which will be used as the learning media of basic programming for grade X VHS student as well as to know the its eligibility level. The developed education game consists of four basic programming competencies. This learning media is developed using ADDIE model with waterfall model for the flow development. The validation process involved 2 material experts, 1 media expert, and two groups of eligibility testing. The type of data is qualitative and quantitative with the method of data collection is questionnaire. The measurement uses five scale of likert. This study concluded that the developed educational game are valid and eligible to be used as a basic programming learning media