Mira Suryani

Benchmarking of Document Image Analysis Tasks for Palm Leaf Manuscripts from Southeast Asia

This paper presents a comprehensive test of the principal tasks in document image analysis (DIA), starting with binarization, text line segmentation, and isolated character/glyph recognition, and continuing on to word recognition and transliteration for a new and challenging collection of palm leaf manuscripts from Southeast Asia. This research presents and is performed on a complete dataset collection of Southeast Asian palm leaf manuscripts. It contains three different scripts: Khmer script from Cambodia, and Balinese script and Sundanese script from Indonesia. The binarization task is evaluated on many methods up to the latest in some binarization competitions. The seam carving method is evaluated for the text line segmentation task, compared to a recently new text line segmentation method for palm leaf manuscripts. For the isolated character/glyph recognition task, the evaluation is reported from the handcrafted feature extraction method, the neural network with unsupervised learning feature, and the Convolutional Neural Network (CNN) based method. Finally, the Recurrent Neural Network-Long Short-Term Memory (RNN-LSTM) based method is used to analyze the word recognition and transliteration task for the palm leaf manuscripts. The results from all experiments provide the latest findings and a quantitative benchmark for palm leaf manuscripts analysis for researchers in the DIA community.

Multi-Layer Perceptron for Sleep Stage Classification

Sleep apnea is a sleep disorder that causes decreasing or even stopping of breathing during sleep. One way to detect whether a person has the disorder or not, then it can be done by conducting a sleep test (polysomnogram). Polysomnogram provides overall body activity during sleep. Polysomnogram records every process of breath changes, muscle tension, brain waves, eye movements that occur in sleep from awake to the patient has dreams and finally wakes up. Once polysomnogram is obtained, then the doctor will check it. One of the targets of the analysis conducted is sleep stage classification. It takes a long time if done manually. Therefore, it needs an application that automatically to make classification efficiently. It is the main reason for this research that must be done. Specifically, this research applies Multi-Layer Perceptron (MLP) to classify the sleep stage. The results show that MLP has a higher performance than Naive Bayes, Bayesian Networks, K-Nearest Neighbours, and Decision Tree.

Improved Line Segmentation Framework for Sundanese Old Manuscripts

Line segmentation can be a useful process for further text segmentation. There are some certain line segmentation framework that use binarization method as an initial step. But binarization process is still facing a major challenge, especially on old document palm-leaf manuscripts. As the quality of the image has varying degrees of noises in the non-text region. Seam Carving method, one of line segmentation methods that uses binarization-free approach, can be an alternative solution. However, this method can separate the incorrect text line on small element text located at the bottom or at the top of a main character contour. Therefore, an improvement on line segmentation framework is proposed by using hybrid binarization and its implemented on the smallest energy function to separate out the text-lines. The proposed framework have been evaluated on 44 Sundanese old manuscript images that consist of true color and binary images. The evaluation matrix shows that this framework can improve Niblack binarization process up to 50%. In addition, our framework does not only generate the number of text-lines to come near to the number of target lines, but it also can separate the text-lines well on small element text. Overall, the expected result can in the end be produced from the proposed line segmentation framework.

EVALUASI APLIKASI SEMI-IMMERSIVE VIRTUAL REALITY PADA BIDANG PENDIDIKAN MENURUT ASPEK HEURISTIK DAN PEMBELAJARAN

Makalah ini memaparkan percobaan evaluasi komprehensif terhadap aplikasi virtual reality (VR) bertipe semi-immersive dari sisi heuristik disain antarmuka aplikasi, peningkatan kemampuan kognitif, dan peningkatan motivasi belajar ketika aplikasi digunakan dalam proses pembelajaran. Evaluasi terhadap disain antarmuka VR ini menggunakan metode heuristik yang diusulkan oleh Sutcliffe, yaitu sebanyak dua belas prinsip. Selain faktor usabilitas, evaluasi heuristik ini mampu memberikan panduan evaluasi dengan memperhitungkan faktor keberadaan pengguna ketika berada dalam lingkungan maya. Hasil proses inspeksi evaluasi heuristik ini adalah penggabungan nilai evaluasi dari tiga orang penilai. Hasil evaluasi menunjukan bahwa secara heuristik aplikasi BIOTALAUT VR sudah merepresentasikan kondisi lingkungan bawah laut dengan baik. Namun ada beberapa fitur disain yang perlu diperbaiki, yaitu interaksi antar objek, grafik objek 3D biota dan fungsi kontrol. Sedangkan, proses evaluasi dari segi peningkatan kemampuan kognitif diimplementasikan pada 30 siswa tingkat sekolah menengah pertama melalui kegiatan pretes dan postes kemudian dianalisa secara statistik. Selain pretes dan postes, siswa juga mengisi kuisioner untuk mengetahui tingkat motivasi belajar setelah menggunakan aplikasi. Kemudian, setelah aplikasi digunakan pada proses pembelajaran, terdapat perbedaan kemampuan kognitif yang signifikan ke arah positif dengan nilai sig-value sebesar 0.448 dan peningkatan motivasi dilihat dari nilai rata-rata central tendency sebesar 4.49. Adapun hasil evaluasi ini dapat digunakan sebagai bahan pertimbangan dalam pengembangan aplikasi selanjutnya khususnya dari sudut pandang disain antarmuka aplikasi maupun dari konteks pembelajarannya. Selain itu, kejadian munculnya gejala cybersickness pada pengguna juga ditelaah dan dilaporkan dalam penelitian ini. Adapun posisi gerakan pengguna saat menjalankan aplikasi VR dan perangkat keras yang dipakai menjadi aspek utama yang menyebabkan cybersickness tersebut. Kata Kunci: cybersickness, evaluasi usabilitas heuristik, , kemampuan kognitif, motivasi belajar, virtual reality

Sundanese ancient manuscript retrieval system comparison of two probability approaches

Nowadays, the development of information technology both in terms of hardware and software has been growing rapidly. Many people used technology to search many types of information. On the other hand, there are information on Sundanese ancient manuscript as cultural heritage with many valuable information still accessed manually, such as the manuscript which located in Situs Kabuyutan Ciburuy, Garut, Jawa Barat. Many people with many purposes (i.e. Research, education, etc.) came to access directly. Its becoming a problem because due to lack of maintainability, the manuscripts became fragile. Furthermore, the information will be lost. So, the emergency solution should be proposed to preserve this valuable heritage. We proposed a retrieval system using the probability approach that can be effective for search the information in ancient Sundanese language. The two probability approaches: Bayesian Networks and Divergence form Randomness have been compared. The 50 queries for three different types of structured query have been run and evaluated by Mean Average Precision (MAP). The results give that the effective methods come from Bayesian Network. There is another finding during the building process of retrieval system. The interactive visualization can be delivered by the retrieval system according to the given query.