Shape is an important aspects in recognizing plants. Several

Several researches in leaf identification did not include color information as features. The main reason is caused by a fact that they used green colored leaves as samples. However, for foliage plants-plants with colorful leaves, fancy patterns in their leaves, and interesting plants with unique shape-color and also texture could not be neglected. For example, Epipremnum pinnatum 'Aureum' and Epipremnum pinnatum 'Marble Queen' have similar patterns, same shape, but different colors. Combination of shape, color, texture features, and other attribute contained on the leaf is very useful in leaf identification. In this research, Polar Fourier Transform and three kinds of geometric features were used to represent shape features, color moments that consist of mean, standard deviation, skewness were used to represent color features, texture features are extracted from GLCMs, and vein features were added to improve performance of the identification system. The identification system uses Probabilistic Neural Network (PNN) as a classifier. The result shows that the system gives average accuracy of 93.0833% for 60 kinds of foliage plants.

Cervical cancer is the fourth most prevalent disease in women. Accurate and timely cancer detection can save lives. Automatic and reliable cervical cancer detection methods can be devised through the accurate segmentation and classification of Pap smear cell images. This paper presents an approach to whole cervical cell segmentation using a mask regional convolutional neural network (Mask R-CNN) and classifies this using a smaller Visual Geometry Group-like Network (VGG-like Net). ResNet10 is used to make full use of spatial information and prior knowledge as the backbone of the Mask R-CNN. We evaluate our proposed method on the Herlev Pap Smear dataset. In the segmentation phase, when Mask R-CNN is applied on the whole cell, it outperforms the previous segmentation method in precision (0.92±0.06), recall (0.91±0.05) and ZSI (0.91±0.04). In the classification phase, VGG-like Net is applied on the whole segmented cell and yields a sensitivity score of more than 96% with low standard deviation (±2.8%) for the binary classification problem and yields a higher result of more than 95% with low standard deviation (maximum 4.2% in accuracy measurement) for the 7-class problem in terms of sensitivity, specificity, accuracy, h-mean, and F1 score.

Most of people likes living independently at home. Some activity in our daily life is prone to have some accidents, such as falls. Falls can make people in fatal conditions, even death. A prototype of fall detection system using accelerometer and gyroscope based on smartphone is presented in this paper. Accelerometerand gyroscope sensors are embedded in smartphone to get the result of fall detection more accurately.Automatic call as an alert will be sent to family members if someone using this application in fatal condition and need some help. This research also can distinguish condition of people between falls and activity daily living. Several scenarios were used in these experiments. The result showed that the proposed system could successfully record level of accuracy of the fall detection system till 93.3% in activity daily living and error detected of fall was 2%.

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Currently the detection of learning styles from the external aspect has not produced optimal results. This research tries to solve the problem by using an internal approach. The internal approach is one that derives from the personality of the learner. One of the personality traits that each learner possesses is prior knowledge. This research starts with the prior knowledge generation process using the Latent Semantic Indexing (LSI) method. LSI is a technique using Singular Value Decomposition (SVD) to find meaning in a sentence. LSI works to generate the prior knowledge of each learner. After the prior knowledge is raised, then one can predict learning style using the artificial neural network (ANN) method. The results of this study are more accurate than the results of detection conducted with an external approach.

AbstrakKeberhasilan dalam sebuah iklan atau promosi yang sesuai dengan kebutuhan masyarakat terhadap Informasi Layanan Pendidikan di jejaring sosial sangat bergantung pada kemasan tampilan yang menarik dan berita yang disampaikan. Pencapaian keberhasilan tujuan promosi tersebut akan membutuhkan tindakan yang berkesinambungan dan tepat sasaran. Untuk mengetahui apakah Facebook Huma Harati itu efektif atau tidak maka perlu adanya pengukuran terhadap Facebook itu sendiri, salah satunya menggunakan metode EPIC (Empaty, Persuation, Impact, and Communication). Hasil analisa menyatakan bahwa Fanpage Huma Harati merupakan tempat yang efektif sebagai media promosi, hal ini terlihat dari nilai empaty, persuasiona, impact and communication yang diperoleh. Nilai rata-rata pada EPIC rate adalah 3,978, dimensi komunikasi mendapat nilai tertinggi dari dimensi lainnya yaitu 4,02.Kata Kunci: Efektivitas ilkan jejaring sosial, EPIC model, Huma Harati PENDAHULUANPendidikan di Kalimantan Tengah dalam bidang pendidikan dalam artian sempit telah menunjukkan kemajuan yang cukup berarti, terlihat dalam data statistik tahun 2010 angka untuk penduduk buta aksara hanya 6,33%, namun data pada BPS Kalteng menunjukkan bahwa penduduk yang tidak menamatkan Sekolah Dasar mencapai angka 23,60%. Hal ini merupakan masalah yang serius, sehingga mendorong pemerintah Propinsi Kalimantan Tengah membuatkan program Kalteng Harati, salah satunya adalah pendirian Huma Harati yang pada dasarnya bertujuan untuk pemerataan layanan pendidikan prima untuk masyarakat Kalteng umumnya dan masyarakat Palangkaraya pada khususnya.Pemanfaatan Teknologi Informasi sangat berperan penting untuk mendukung penyebaran Informasi mengenai Huma Harati. Maraknya dunia periklanan menggunakan media jejaring sosial menjadi salah satu strategi yang dianggap efektif dan efisien untuk memangkas anggaran dalam mempublikasikan produk. Diantara media sosial yang paling banyak digunakan untuk mempromosikan produk adalah Facebook, Huma Harati dengan nama akun Huma Harati Kalteng dibuat sejak berdirinya Huma Harati yaitu tahun 2012, melalui Facebook, Huma Harati aktif memberikan informasi tentang kegiatan yang dilakukan di Huma Harati, informasi pendidikan dan tautan-tautan yang bersifat mendidik.

Obtaining quality learning behavior requires constant improvement. The development of learning methods often unsupported changes in the behavior of participants. This condition causes reluctance to use new learning methods by some users. Meanwhile, technological developments, especially Web 2.0, have the ability to change the way people communicate and interact. This study used the features and capabilities of Web 2.0 to improve learning behavior. The use of this technology will be adjusted with learning methods, especially online-learning that overgrows nowadays. The concept of an integrated system applied a persuasive strategy to bring persuasion. Modifications elearning were done by combining the concepts of Web 2.0 and persuasive system. Tests were performed on aspects that affect the user's intentions by comparing the initial and final conditions after the intervention. The behavior changes were expected to improve user involvement and intention in online learning. The results show that the modified technology by using persuasive concept can improve the users' intention.