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Abstrak :
This paper presents a lip and smile detection method based-on the normalized RGB chromaticity diagram. The method employs the popular Viola-Jones detection method to detect the face. To avoid the false positive, the eye detector is introduced in the detection stage. Only the face candidates with the detected eyes are considered as the face. Once the face is detected, the lip region is localized using the simple geometric rule. Further, the the red color thresholding based-on the normalized RGB chromaticity diagram is proposed to extract the lip. The projection technique is employed for detecting the smile state. From the experiment results, the proposed method achieves the lip detection rate of 97% and the smile detection rate of 94%.

Paper ini menyajikan medote pendeteksi bibir dan senyum berdasarkan diagram tingkat kromatis RGB ternormalisasi. Metode ini menggunakan metode Viola-Jones yang populer untuk mendeteksi wajah. Untuk menghindari kesalahan positif, detektor mata diperkenalkan pada tahapan deteksi. Hanya kandidat wajah dengan mata yang telah terdeteksi yang dianggap sebagai wajah. Setelah wajah dideteksi, bagian bibir ditempatkan dengan menggunakan aturan geometris sederhana. Selanjutnya, batasan warna merah berdasarkan pada diagram kromatisitas RGB ternormalisasi digunakan untuk mengekstrak bibir. Teknik proyeksi digunakan untuk mendeteksi keadaan tersenyum. Dari hasil percobaan, metode yang diusulkan mencapai 97% untuk tingkat deteksi bibir dan 94% untuk tingkat deteksi senyum.

Abstrak :
Deteksi dini kanker payudara sangat penting dilakukan bagi wanita berisiko, khususnya Pemeriksaan Payudara Sendiri (SADARI). Pemeriksaan ini secara rutin dilakukan untuk mendeteksi adanya kelainan atau benjolan sejak awal. Penelitian ini bertujuan menganalisis faktor-faktor yang mempengaruhi deteksi dini kanker payudara pada wanita berisiko kanker payudara. Desain yang digunakan Crossectional dengan 135 responden yang teknik concecutive sampling. Hasil penelitian menunjukan ada hubungan yang signifikan antara pengetahuan tanda dan gejala, pengetahuan deteksi dini, pendidikan, riwayat operasi, dimana faktor yang dominan yaitu variabel pengetahuan tanda dan gejala (p< 0,05;OR=0.095 C.I: 0.013-0,687). Faktor-faktor tersebut dapat dijadiakan salah satu eviden base dalam mengidentifikasi masalah dalam usaha mencegah terjadinya kanker payudara pada wanita berisiko kanker payudara. ......Early detection for breast cancer is very important for the high-risk women especially Self Breast Examination (BSE). This examination is done routinely detects the unusual changes or lumps. This research aims to identify the factors influencing early detection of breast cancer in women at risk for breast cancer. Cross sectional design to 135 respondents that were selected by consecutive sampling. The results show that there is significant correlation between the knowledge about signs and symptoms, knowledge about early detection, knowledge about surgery records by which the dominant factor is the knowledge about signs and symptoms (p< 0,05;OR=0.095 C.I: 0.013-0,687). These factors can be presented as an evidence base in identifying problems in an effort to prevent breast cancer in high-risk women for breast cancer.

Abstrak :
With recent advances in the basic analysis of speaker recognition, the technology can be expanded to a new system of audio event detection. The analysis of audio events is important in a variety of applications including audio surveillance, sports highlights and hearing disability support. Past project has given many challenges regarding to the detection and recognition speaker. This report presents an audio event detection method by using the Maximum Likelihood techniques. The algorithm uses Gauss/an Mixture Model (GMM) to provide a model of several types of sound. The Maximum Likelihood methods will give an estimation of all the parameters of the Gauss/an Mixture Model that can be used to identify what event(s) happen in audio signals. The focus of this work is on the ability of modelling different types of audio files and identifying what events occur regarding to the models. A complete experimental evaluation of the Gauss/an Mixture Model is conducted on a 150 speaker, 3 different types of sound, with each type of sound consisting of 10 audio files. The approach of Expectation Maximisation algorithm is applied in order to improve the performance of the classifier.

Abstrak :
Pendeteksian wajah manusia merupakan proses dasar dari aplikasi yg lebih luas. Salah satu metodenya adalah pemanfaatan informasi warna. Sebuah model warna kulit yg merepresentasikan warna kulit manusia dibuat utk mensegmentasi skin region dan non skin region dlm gambar berwarna. Tiga persyaratan di terapkan utk menyeleksi skin region yg mempresentasikan wajah manusia (jumlah lubang dlm satu region, rasio tinggi terhadap lebar region dan koefesien korelasi siang antara region dengantemplete face).Makalah ini mensimulasikan deteksi wajah manusia dengan menggunakan segmentasi dan templete matching .Hasil simulasi menunjukan bahwa skin region yaitu jumlah lubang ,rasio tinggi terhadap lebar dan korelasi region dengan templete,ketiganya berperan cukup baik,sedangkan keberhasilan deteksi sangat tergantung pd proses sebelumnya yaitu segmentasi.

Abstrak :
Cancer detection medium such as serum & biopsy often make patient uncooperative due to lack of safety, convenience & economic. This condition causes cancer to be detected at late stadium & causes death. This paper discusses the role of saliva as cancer detection medium of choice. Some tumor markers have been identified in saliva such as c-erbB-2, CA 15-3, p53 & CA 125. Each corresponds to certain type of cancer. These tumor markers are protein, thus the use of saliva to detect cancer can utilize protein analysis technique such as ELISA. ELISA can be used for early detection & monitoring of the effectiveness of breast cancer treatment by showing the expression of c-erbB-2 & CA 15-3 in saliva. Saliva has high potential as cancer detection medium & cancer treatment monitor, especially breast cancer. Further various researches are needed for different tumor marker with other protein analysis technique.

Abstrak :
ABSTRAK
Penelitian ini bertujuan untuk mengembangkan sebuah sistem teknologi alat bantu mobilitas untuk orang dengan gangguan penglihatan (OdGP) yang dinamakan dengan Smart Environment Explorer Stick (SEES) . Tujuan khusus penelitian ini adalah mengembangkan algoritma baru dalam meningkatkan akurasi SEE-stick untuk mendeteksi tiang dengan metode perhitungan jarak dan pencarian pasangan garis vertikal berbasis optimasi deteksi tepi Canny dan Transformasi Hough. Algoritma deteksi tiang ini dinamakan algoritma YuRHoS. Hasil penelitian ini adalah telah dikembangkan SEES sebagai sistem pendukung mobilitas OdGP yang mengintegrasikan perangkat global remote server iSEE , embedded local server SEE-phone dan smart stick SEE-stick . Kinerja SEE-stick dapat ditingkatkan melalui algoritma YuRHoS yang mampu memperbaiki akurasi SEE-stick dalam mendeteksi tiang. Perbandingan hasil uji deteksi tiang antara algoritma YuRHoS dengan algoritma deteksi tiang lainnya menyimpulkan bahwa algoritma YuRHoS memiliki tingkat akurasi lebih baik dalam mendeteksi tiang. Dua faktor dominan yang signifikan mempengaruhi kemampuan SEE-stick dalam mendeteksi tiang adalah lokasi uji dan warna tiang. Tingkat akurasi SEE-stick akan optimal dalam mendeteksi tiang di luar ruangan dan tiang berwarna perak. Hasil uji statistik menunjukkan bahwa kinerja algoritma YuRHoS pada uji di dalam ruangan 0,085 kali lebih buruk dibandingkan uji di luar ruangan, sedangkan penggunaan tiang berwarna perak sebagai obyek deteksi dapat meningkatkan kinerja algoritma YuRHoS 12 kali lebih baik dibandingkan penggunaan tiang berwarna hitam.

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ABSTRACT
This research aimed to develop a technology system of mobility aid for Visually Impaired Person (VIP) called Smart Environment Explorer Stick (SEES) . Particular purpose of this research was developing new algorithm in improving accuracy of SEE stick for pole detection using distance calculation method and vertical line pair search based on Canny edge detection optimization and Hough transform. Henceforth, the pole detection algorithm was named as YuRHoS algorithm. The developed SEES as supporting system of VIP mobility aid had been successfully integrated several devices such as global remote server iSEE , embedded local server SEE phone and smart stick SEE stick . Performance of SEE stick could be improved through YuRHoS algorithm which was able to fix the accuracy of SEE stick in detecting pole. Test comparison of pole detection results among others algorithm concluded that YuRHoS algorithm had better accuracy in pole detection. Two most significant factors affecting SEE stick ability in detecting pole was test location and pole color. Level of accuracy of SEE stick would be optimum once the test location was performed outdoor and pole color was silver. Statistics result shown that YuRHoS algorithm performance indoor was 0.085 times worse than outdoor. Meanwhile, silver pole color as object detection could increase YuRHoS algorithm performance as much as 12 times better compare to black pole color.