Search

Banyaknya teknologi kesehatan yang tersedia saat ini, menyebabkan adanya kebutuhan terkait penilaian pada berbagai aspek. Penilaian tersebut biasa disebut dengan Health Technology Assessment (HTA). HTA adalah evaluasi secara sistematis, efek, dan/atau dampak dari teknologi kesehatan yang bertujuan untuk memberikan informasi kepada pembuat kebijakan yang berhubungan dengan teknologi kesehatan, dengan demikian dapat meminimalkan biaya dan mencegah penggunaan teknologi yang diragukan. HTA telah banyak digunakan dalam melakukan penilaian terhadap teknologi kesehatan. Teknologi kesehatan yang dimaksud dapat berupa obat-obatan, terapi, prosedur tindakan medis, maupun alat kesehatan. Proses dan metodologi HTA untuk obat-obatan telah banyak dilakukan sedangkan untuk alat kesehatan masih jarang. Dari beberapa literatur review yang dilakukan sebelumnya, penggunaan kriteria HTA berbeda-beda meskipun objeknya alat kesehatan. Penelitian ini bertujuan untuk mengetahui mengenai kriteria apa saja yang sering digunakan pada HTA untuk alat kesehatan medis. Metode penelitian scoping review pada publikasi HTA sebelumnya (n=392) dilakukan untuk membahas tujuan tersebut dengan menggunakan database Pubmed dan Science Direct. Berdasarkan hasil pencarian literatur dengan menggunakan PRISMA, didapatkan 7 artikel sesuai dengan kriteria inklusi yang berhubungan dengan HTA untuk alat kesehatan dengan subjek yang berbeda, yaitu: alat kesehatan dan HTA berbasis rumah sakit. Kesimpulan dari hasil temuan tersebut, diketahui bahwa kriteria yang sering digunakan dalam HTA untuk alat kesehatan yaitu, ekonomi, keamanan, efektivitas, dan organisasi. Saran penelitian ini adalah hasil kriteria yang didapatkan divalidasi terlebih dahulu oleh ahlinya atau stakeholder.

Perawatan kulit wajah (skincare) menjadi hal yang sangat digemari, tidak hanya usia dewasa bahkan sejak seseorang menginjak usia remaja telah aware terhadap kondisi kulit wajahnya. Pada saat ini, kemajuan teknologi semakin pesat dan ditandai dengan penggunaan smartphone menjadi hal yang biasa digunakan oleh anak-anak. UII Skin Analyzer merupakan aplikasi android berbasis smartphone yang dikembangkan untuk mempercepat proses deteksi dan analisis permasalahan kulit wajah. UII Skin Analyzer memperhatikan aspek UI/UX yang sesuai dengan kebutuhan dan relevan dengan isi aplikasi tersebut. UI (User Interface) bagian dari suatu aplikasi yang berfungsi sebagai penghubung antara suatu mesin komputer dengan pengguna. UX (User Experience) pengalaman pengguna atau semua respon dari interaksi pengguna dengan sistem mulai dari emosi, perasaan, hingga pikiran pengguna. Pentingnya peran UI/UX dalam sebuah aplikasi sejalan dengan pentingnya pengembangan UI/UX terhadap aplikasi UII Skin Analyzer. Pengembangan ini bertujuan untuk memastikan bahwa aplikasi tersebut dapat berjalan sesuai fungsionalitas yang sudah dirancang dan dapat diterima oleh masyarakat. Pada penelitian ini, pengembangan UI/UX aplikasi dilakukan dengan pengujian usabilitas menggunakan metode Cognitive Walkthrough dan System Usability Scale (SUS). Berdasarkan dua metode tersebut diperoleh hasil pengujian menggunakan Cognitive Walkthrough sebesar 96% responden dapat mengerjakan tugasnya dan dengan System Usability Scale diperoleh nilai sebesar 82.6%. Sehingga dapat disimpulkan bahwa aplikasi UII Skin Analyzer berada pada nilai A dan menurut skala Likert memiliki kategori Sangat Baik.

ODHA adalah sebutan bagi orang-orang yang telah terjangkit penyakit HIV/AIDS. Agar para ODHA tetap dapat dalam kondisi baik, dibutuhkan obat yang secara resmi direkomendasikan oleh pemerintah yaitu berupa terapi antiretroviral (ART). Dalam menjalankan terapi ARV harus meminum obat dengan disiplin ketat dan terus menerus seumur hidup ODHA untuk menghambat replikasi virus HIV, namun dalam kenyataanya banyak ODHA yang tidak mendapatkan hasil yang optimal dalam menjalankan terapi tersebut, karena kurangnya tingkat kepatuhan pasien dalam mengkonsumsi obat ARV dan juga tidak termonitoring dengan baik oleh para pendamping. Untuk itu dipandang perlu untuk merancang desain prototipe sistem monitoring minum obat bagi ODHA sebagai solusi masalah tersebut. Metode penelitian yang digunakan dengan studi pustaka, review aplikasi sejenis dan wawancara dengan petugas klinik pengobatan HIV/AIDS, Orang dengan HIV/AIDS (ODHA) dan Pendamping ODHA. Sistem ini dikembangkan dengan metode Participatory Design yaitu Teknik Design dengan melibatkan users. Hasil dari penelitian ini berupa desain prototipe sistem monitoring minum obat bagi ODHA. Desain prototipe yang dihasilkan kemudian di uji menggunakan metode Questionnaire for User Interface Satisfaction (QUIS). Hasil pengujian dengan indikator penilaian keseluruhan sistem menunjukan nilai 72%, penilaian tampilan layar menunjukkan 77%, penilaian istilah dan informasi menunjukan 66%, penilaian mempelajari sistem mununjukan 80% dan perhitungan persentase indikator pengujian untuk penilaian kemampuan sistem 76%. Sehingga dilihat dari persentase hasil pengujian desain prototipe menunjukan sangat baik.

Maternal mortality rates are still high in several areas, including Bantul Regency, Special Region of Yogyakarta. Based on the data obtained from the Bantul District Health Office, from 2018 to 2019, 28 pregnant women died. Posyandu and Puskesmas cadres often encounter problems in collecting data on pregnant women because they still use manual methods. Manual records using books has disadvantages because sometimes pregnant women forget to bring their books. Therefore, an application for recording pregnancy history is needed to enable convenient monitoring by Posyandu cadres, Puskesmas, doctors, and hospitals in order that pregnant women patients can be handled properly in case of emergency. The application used by pregnant women is Mobile App-based, meanwhile, the Web-based Monitoring Information System is used by Posyandu cadres, Puskesmas, doctors, and hospitals. The application allows displaying the medical history and makes it easier for pregnant women to have counseling or examinations without meeting directly with the doctor. If there are any problems in the womb, the doctor will immediately provide a solution or recommendation. The results of the system testing with 15 respondents as users show that 52,1% strongly agree, 37,7% agree, and 10,2% neutral in response to the system interface. The implementation of the information system for monitoring high-risk pregnant women in the majority is accepted by all actors. Hence, it can be concluded that in an attempt to digitalize manual recording of pregnant women's examinations, this information system for monitoring high-risk pregnant women is reliable to be implemented.

One facial skin problem is redness. On site examination currently relies on examination through direct observations conducted by doctors and the patient's medical history. However, some patients are reluctant to consult with a doctor because of shame or prohibitive costs. This study attempts to utilize digital image processing algorithms to analyze the patient's facial skin condition automatically, especially redness detection in the face image. The method used for detecting red objects on face skin for this research is Redness method. The output of the Redness method will be optimized by feature selection based on area, mean intensity of the RGB color space, and mean intensity of the Hue Intensity. The dataset used in this research consists of 35 facial images. The sensitivity, specificity, and accuracy are used to measure the detection performance. The performance achieved 54%, 99.1%, and 96.2% for sensitivity, specificity, and accuracy, respectively, according to dermatologists. Meanwhile, according to PT. AVO personnel, the performance achieved 67.4%, 99.1%, and 97.7%, for sensitivity, specificity, and accuracy, respectively. Based on the result, the system is good enough to detect redness in facial images. ABSTRAK: Salah satu masalah kulit wajah adalah kemerahan muka. Pemeriksaan di lokasi kini bergantung pada pemeriksaan melalui pemerhatian langsung yang dilakukan oleh doktor dan sejarah perubatan pesakit. Namun, sebilangan pesakit enggan berunding dengan doktor kerana rasa malu atau kos yang terhad. Kajian ini cuba membuat sistem pengesanan kemerahan wajah yang dapat menganalisis keadaan wajah, terutama kemerahan, melalui gambar kulit wajah. Kaedah yang digunakan untuk mengesan objek merah pada kulit wajah bagi penyelidikan ini adalah kaedah Kemerahan. Keluaran kaedah Kemerahan akan dioptimumkan dengan pemilihan ciri berdasarkan luas, intensiti min RGB, dan intensiti min Hue Intensity. Set data yang digunakan dalam penyelidikan ini terdiri daripada 35 gambar wajah. Nilai pengesahan yang digunakan adalah kepekaan, kekhususan, dan ketepatan. Hasil yang diperoleh berdasarkan pakar dermatologi masing-masing adalah 54%, 99.1%, dan 96.2% untuk kepekaan, kekhususan, dan ketepatan. Sementara itu, PT. Selain itu, menurut kakitangan AVO 67.4%, 99.1%, dan 97.7%, bagi kepekaan, kekhususan, dan ketepatan, masing-masing. Berdasarkan dapatan kajian ini, sistem ini cukup baik bagi mengesan kemerahan pada gambar wajah.

Researches with early detection of caries using x-ray topic has been widely developed, generally before doing object detection, the early step is segmentation. Image segmentation is one of the digital image processing steps used to segregate an area or object observed with other areas or objects. Segmentation has an important role as the initial determination of the desired area or object so that it can be continued to the identification stage. FCM (fuzzy c-means) algorithm is one of object segmentation technique or object grouping in the field of digital image processing study. The basic concept of FCM is to determine the centroid and members of each group adaptively, in principle FCM uses a fuzzy grouping model so that a data or element becomes a member of all the clusters that are formed. Segmentation of the dental area using FCM with 4 clusters aims to segment the enamel, dentin, pulp, and backround areas. The result of segmentation using FCM is influenced by the condition of the dataset used. The background area of the entire dataset can be well segmented. FCM is also capable of segmenting the enamel area but in some datasets, the enamel segmentation results are still mixed with other teeth areas. For the dentin and pulp areas, the segmentation result of these two areas is not optimal yet; most of the dentin and or pulp areas are still segmented with the other teeth’s area.

High blood disease or famous to known as hypertension almost 95% the cause is very difficult to know. One way to know the condition of our health is by checking routine to the nearest clinic or hospital. Hypertension is one of the risk factors for dangerous diseases, such as stroke, heart attack, and kidney failure. Hypertension can cause high morbidity (pain) and mortality (death), hypertension is often called silent killer disease. People with Hypertension rarely show early symptoms, and their recognition is usually through screening, or when seeking medical treatment for unrelated health problems. The cause factors of hypertension include weight and height, body fat, and alcohol levels inside of body. To know the condition of body to hypertension need a monitoring system and use tool tensimeter. In this research has been made the means of detecting factor symptoms of hypertension. After the measurements are done by each sensor then the data is processed by Arduino Microcontroller to be processed to computer via serial port (USB). On the computer data that has been sent will be processed using decision tables with databases obtained from experts, the resultin a decision will give classification of hypertension and non-pharmacological management.

Cancer is one of the main causes of mortality in the world. Colorectal cancer, also known as colon cancer, is a malignant tumor of the colon and rectum that begins with a polyp. Early inspection is needed to prevent and cure of colorectal cancer because in the early stages colorectal cancer showed no symptoms. At this time the development of information technology allows the quick information retrieval from an image. The aim of this research is to produce a preliminary work in the stages of information analyzing on colorectal endoscopic image extraction result in the form of polyp and bleeding by utilizing extraction technique of image information based on shape and texture. This research aimed can be the basis for the development of colorectal cancer detection system framework. The research that has been carried out gives result of characteristics that can be differentiate between colon bleeding, colon polyp, and normal colon conditions, they are aspect ratio, triangle, correlation, and energy.

The automatic interpretation of Pap Smear image is one of challenging issues in some aspects. Accurate segmentation for each cell is an important procedurethat must be done so that no information is lost during the evaluation process. However, the presence of overlapping cells in Pap Smear image make the automated analysis of these cytology images become more difficult. In most ofthe studies, cytoplasm segmentation is the difficult stage because the boundaries between cells are very thin. In this study, we propose an algorithm that can segment the overlapping cytoplasm. First, the morphology operation and global thresholding to segment cytoplasm is done. Second, the overlapping area on cytoplasm region is separated using morphological operation and distance criteria on each pixel. The proposed method has been evaluated against the results of manual tracing by experts. The experiment results show that the proposed method can segment the overlapping cytoplasm as similar as experts do, i.e., 2:897 3:632 (mean std) using Hausdorff distance.

Electronic Medical Record (EMR) has now become a trend in the world of health care. Lot of obstacles and barriers that interfere implementation of EMR. This paper discussed the eleven factors suspected to affect the implementation of EMR, with a case study hospital in Banyumas. By using logistic regression analysis obtained eight of the eleven factors that significantly affect the implementation of RME. The eight factors are financial factors, Human Resources (HR), the process of changing, psychological factors, legal factors, the time factor, organizational factors, and ICT trends. Technology, infrastructure, and social is a factor that does not significantly affect the implementation of EMR in hospital. ICT trends are new factors that significantly affect the implementation of EMR in hosital.

Even compared to the same age, the growth of every child is way different. The parent has to do an assessment against their child so that they could understand about how and how much the child grows. One of assessment methods that could be used is a Denver Development Screening Test (DDST) or usually called Denver II. Denver II contains 4 sectors which tested against children, those: Social Personal, Soft Motoric, Language, and Hard Motoric. An assessment using the Denver II could be conducted not only in the clinic or hospital but also in patient home using a help from a psychologist or other health workers as a tester. A DDST application based on Android was designed to facilitate a tester doing an assessment out of the clinic or hospital. Data of an assessment managed over a decision support system that build alongside a DDST application. Application was constructed based on instrument of Denver II, which are question form and manual test. Application testing conducted in two ways: usability testing, which could show whether an application could run well as the need lists; and validation testing using Single Decision Threshold have sensitivity amount of 100%, specificity amount of 87.5% and value apps performance amount of 90%. Using Coefficient Cohen’s Kappa has an accuracy amount of 0.74 (Strong).

We report the results of the detection of types of acne on the human face that are identified directly by a specialist skin and genitals. The proposed algorithm has been tested on a standard image and gives very reasonable results, there are 5 types of acne identified, namely Blackhead Blackheads, Blackhead Blackheads, Papules, Pustules and Nodules. Work completed using PYTHON.

In order to obtain a diagnosis of cervical cancer information, the characteristics of each cell nucleus must be identified and evaluated properly through a Pap smear test. The presence of inflammatory cells in Pap smear images can complicate the process of identification of cell nuclei in the early detection of cervical cancer. Inflammatory cells need to be eliminated to assist pathologists in reading Pap smear slides. In this work, we developed a novel method to extract the inflammatory cells that allow detection of cell nuclei more accuracy. The proposed algorithm consists of two stages: extraction of inflammatory cells using the distance criterion and image transformation. This experiment applied to the 1358 cells comprising 378 nuclei cells and 980 inflammatory cells from 25 Pap smear images. The results showed that our method can significantly reduce the amount of inflammation that can disrupt the cell nuclei in the detection process. The proposed method has promising results with a sensitivity level of 97% and a specificity of 84.38%.

We evaluate the characteristic of the normal epithelial cervical cell in Pap Smear images, using feature analysis. The evaluation affects the determination of proper pap smear image determination. This study aims to analyze the performance of feature selection on data classification and discovering features which significantly affect the classification of the normal epithelial cervical cell. Feature selection process has been done to 54 features in the nuclei area and the cytoplasm of the cervical epithelial cell, using Feature Subset Selection. Furthermore, we compare the performance of two classification methods: K-Nearest Neighbors (KNN) and Backpropagation. Both methods resulting in the same 12 features to differentiate between normal cervical cells. The classification accuracies for both methods are 92.29% for KNN and 91.51% for Backpropagation.

Heart disease is a disease with a high mortality risk. Errors in diagnosis increase the risk of death. Some efforts to reduce misdiagnosis are developing algorithms for interpretation of ECG signals. This paper presents and discusses decision support system for ECG interpretation, the types of heart disease, electrocardiogram wave, expert system and smart ECG using MKNN (Modified K-Nearest Neighbor) algorithm. MKNN is a method of classification of types of assisted (supervised). In this experiment, we used ECG data from MIT BIH. Because sample is limited, we divide heart disease into 3 classes, that is normal, myocardial infarction and others. The accuracy of MKNN in this study is 71.2% with a value of K = 3.

One of the major challenges in the development of early diagnosis to assess HER2 status is recognized in the form of Gold Standard. The accuracy, validity and refraction of the Gold Standard HER2 methods are widely used in laboratory (Perez, et al., 2014). Method determining the status of HER2 (human epidermal growth factor receptor 2) is affected by reproductive problems and not reliable in predicting the benefit from anti-HER2 therapy (Nuciforo, et al., 2016). We extracted color features by methods adopting Statistics-based segmentation using a continuous-scale naïve Bayes approach. In this study, there were three parts of the main groups, namely image acquisition, image segmentation, and image testing. The stages of image acquisition consisted of image data collection and color deconvolution. The stages of image segmentation consisted of color features, classifier training, classifier prediction, and skeletonization. The stages of image testing were image testing, expert validation, and expert validation results. Area segmentation of the membrane is false positive and false negative. False positive and false negative from area are called the area of system failure. The failure of the system can be validated by experts that the results of segmentation region is not membrane HER2 (noise) and the segmentation of the cytoplasm region. The average from 40 data of HER2 score 2+ membrane images show that 75.13% of the area is successfully recognized by the system.

In this study, a robust method is proposed for accurately separating overlapping cell nuclei in cervical microscopic images. This method is based on watershed transformation and an elliptical approach. Since the watershed transformation process of taking the initial seed is done manually, the method was developed to obtain the initial seed automatically. Total initial seeds at this stage represents the number of nuclei that exist in the image of a pap smear, either overlapping or not. Furthermore, a method was developed based on an elliptical approach to obtain the area of each of the nuclei automatically. This method can successfully separate several (more than two) clustered cell nuclei. In addition, the proposed method was evaluated by experts and was proven to have better results than methods from previous studies in terms of accuracy and execution time. The proposed method can determine overlapping and non-overlapping boundaries of nuclei fast and accurately. The proposed method provides better decision-making on areas with overlapping nuclei and can help to improve the accuracy of image analysis and avoid information loss during the process of image segmentation.

The modeling of the proposed mosquito identification system is one of the efforts to support the efforts of the Indonesian people in handling zoonotic cases. The incidence of deaths caused by a disease that is naturally transmitted between animals and humans is still quite high. This group of zoonotic diseases include dengue hemorrhagic fever, leptospirosis, cikunguya, and so forth. In the stages of diagnosis, it is necessary to read and identify the type of vector that causes zoonotic disease through microscopic observation. This process is often not done because in this laboratory examination service is not available evenly at the clinic level. In addition, with various types of vectors that the number of variations is very much, needed a way to be able to recognize the vector easily and quickly. Therefore, the prototype of this mosquito identification system needs to be developed. The data used to test system modeling consists of digital microscopic images of mosquito preparations taken from the Parasitology Laboratory of the Faculty of Medicine, Islamic University of Indonesia. Lecturer coordinator of this Parasitology lab will serve as a resource in determining the characteristics of vector and also as a provider of ground truth in the testing phase of the system.

Elephantiasis is a chronic disease (chronic) that could attack humans and animals, and causes a permanent disability if not immediately given treatment. Some filaria species in Indonesia include Wuchereria bancrofti, Brugia malayi, and Brugia timori. The main goal in the early treatment of people with this disease is to eradicate parasites or larvae that develop in the patient's body, so that the level of transmission can be reduced. To help identifying the type of microfilaria that develops in the body of the patient, the authors took the initiative to create a computer-assisted program that is expected to recognize microfilaria on peripheral blood preparation. In this case, there are 4 stages of analysis of the microscopic images, namely image readings, preprocessing, segmentation, and shape analysis to identity the microfilaria.

The main idea in this research is the utilization of Fuzzy C Means (FCM) method as the determination of patient's nutritional status, which is implemented, in mobile application. Parameters used to cluster nutritional status are height, weight and age. The result of the decision will give 3 clusters on nutritional status is good nutrition, malnutrition and better nutrition. Mobile apps are used as a reminder of the nutritional value or ingredients contained in the packaging of food products while consuming food. The result of system testing for application of FCM algorithm in this mobile application obtained validation of 80%.

Makalah ini membahas mengenai proses desain, implementasi, dan evaluasi kerangka kerja permainan digital untuk alat bantu terapi kemampuan sosial anak autis. Anak autis memiliki karakter yang unik, sehingga mereka memiliki preferensi khusus. Desain kerangka kerja permainan digital untuk anak autis juga masih sangat terbatas. Proses desain kerangka kerja dihasilkan dari analisis komponen permainan digital komersial yang dimainkan oleh anak autis, penelitian yang membahas desain permainan digital untuk anak autis, serta konsultasi dengan pakar, psikolog, dan terapis. Kerangka kerja yang dihasilkan kemudian digunakan sebagai panduan untuk mengembangkan permainan digital multipemain. Sebagai bentuk proof of concept dari kerangka kerja yang dihasilkan, permainan digital multipemain ini telah mampu digunakan sebagai media terapi untuk meningkatkan kemampuan sosial pada anak autis, yaitu interaksi mata, inisiasi, dan interaksi timbal balik.

Deteksi peristiwa biomolekuler dalam visual yang akan dianalisis menggunakan komputasi untuk mendeteksi efektivitas dan akurasi penyakit. Sebagai hasil utama, banyak analisis visual, mulai dari pengelompokan gen hingga filogenetik, menghasilkan pohon hierarkis. Toolkit Lingkungan Eksplorasi Pohon (ETE) yang membantu manipulasi, analisis, dan visualisasi pohon hierarkis otomatis. Kemudian, dalam makalah ini, daftar mutasi β-thalassemia yang merupakan kelompok kelainan darah herediter yang ditandai oleh anomali dalam sintesis rantai beta hemoglobin yang menghasilkan berbagai fenotipe mulai dari anemia berat hingga individu tanpa gejala klinis. Hasil ini adalah ETEToolkit dapat menguraikan mutasi ini untuk ditampilkan melalui pohon dan penyelarasan dalam satu bingkai, kemudian kita dapat menyesuaikan dan merender ke dalam gambar PDF. Mutasi ini berlokasi di pusat Jawa, Indonesia.

Penelitian ini mengusulkan salah satu pendekatan pengolahan citra dan klasifikasi dalam analisis urin (urinalisis) dengan metode carik celup menggunakan dipstik urin sepuluh parameter (dipstik 10P). Adapun yang diurinalisis dalam pemeriksaan urin meliputi leukosit, nitrit, urobilinogen, protein, keasaman, darah, berat jenis, keton, bilirubin dan glukosa pada urine. Penggunaan kamera yang disematkan pada smartphone dapat menjadi solusi dalam akuisisi citra untuk data reference dan data uji dipstik. Setelah akuisi citra dilanjutkan dengan skema pemrosesan citra dipstik. Citra hasil tangkapan kamera smartphone menempati ruang warna RGB yang selanjutnya digunakan sebagai nilai ekstraksi fitur. Hasil dari ekstraksi fitur warna RGB digunakan sebagai nilai untuk mengukur jarak kedekatan antara reference dan data uji. Metode yang digunakan adalah Jarak Manhattan. Nilai jarak terdekat menjadi solusi dalam masalah klasifikasi hasil urinalisis ini. Perancangan sistem menggunakan bahasa pemrograman Python dengan package OpenCV. Hasil dari perancangan ini menunjukkan sistem dapat melakukan klasifikasi.

Breast cancer is a disease occurs as a result of uncontrolled cells growth. One examination method of breast cancer cells is using Immunohistochemistry (IHC) to determine status of Human Epidermal Growth Factor Receptor2 (HER2) protein. This study helps anatomic pathologist to determine HER2 scores using image processing techniques to obtain HER2 overexpression positive area percentages of 1+ and 3+ scores. This is done because the score of 0 is HER2 negative cells and 2+ scores have equivocal results, which means it could not be determined whether it is necessary to give targeted therapy or not. HER2 overexpression positive area percentage is done by dividing the area with a HER2 positive tumor area. To obtain better tumor area, repair is done by eliminating lymphocytes area which is not tumor area using morphological opening. Results of 10 images IHC scores of 1+ and 3+ and 10 IHC images testing without losing lymphocytes area in tumor area, has proven that the system has been able to provide an overall correct classification in accordance with the experts analysis. However by doing operation to remove non-tumor areas, classification can be done correctly 100% for scores of 3+ and 65% for scores of 1+.

Indonesian Robotic Competition is an annual robot competition conducted by Indonesian minister of education. One of branch competition is robot dance whereas robot should dance according to Indonesian traditional music. The aim of this study is to make an application that is capable to recognize instrument especially gong in javanesse traditional music so that it can helps future development of robot dance in simulate instrument recognition. Recognition methods that are used in this study is on time domain and frequency domain. Furthermore, pattern recognition also provided in two version, namely realtime and non-realtime. Result of this study is an application to recognize gong in a music. Evaluation result shows pattern recognition is successfully recognise the gong note in time domain.

This study proposes two specific prototype systems used for the physical examination of skin diseases by a doctor. The objective of this study is to enhance the comfort level of the doctor while performing physical examination of skin diseases using a computer-assisted system. In the previous study, we found that physicians were more comfortable with the process of physical examination using some variety of a particular dialogue. In this study, we propose two prototype systems, namely, an icon-based model and a graphic user interface (GUI)-based model. These prototypes were evaluated by eight medical doctors through a focus group discussion (FGD) to obtain the desired model. From the results obtained by the doctors, it was found that the acceptance level of the GUI-based model was approximately 81% and that this model was better than the icon-based model. Further, the proposed prototype can be used as a reference model in future studies for developing a user interface system, particularly a system that requires physical examination of skin diseases.

Human foot consisted of some parts that work in an integrated system that allows the body to stand and walk. The problems that disturb these functions can be caused by accident or disability since birth. There are some treatmens that allow some patients to walk with ease by using special footwear or shoes. This special shoes need to have the size and shape of the feet measured correctly. And in some cases, the patient couldnot be asked to lay their feet on the printed board. In this case, the use of two pose image based measurement can help. Moreover, the 3D reconstruction using both images is presented.

Stroke patients who experience a decrease in muscle strength need to do exercises so that they can increase their muscle strength. In order to enable the patient does exercise independently the multimedia-based stroke therapy model is needed. These exercises can be done independently, with supervision of the family member at home. So, we develop prototype of the multimedia-based therapy for the family member so that they can assist patients performing exercises without attending therapy session in hospital. This model was built according to the advices from physiotherapist and a medical rehabilitation doctor. This model has been evaluated through focused group discussion by physiotherapists. And they gave positive responses to this proposed model.