Comparison of GLCM and First Order Feature Extraction Methods for Classification of Mammogram Images

Breast cancer is one of the main causes of death in women and ranks first in cancer cases in Indonesia. Therefore, an early detection and prevention of breast cancer is necessary, one of which is through mammography procedures. A machine learning classifier such as Support Vector Machines (SVM) could be used as an aid to the doctors and radiologist in diagnosing breast cancer from the mammogram images. The aim of this paper is to compare two feature extraction methods used in SVM, namely the Gray Level Co-Occurrence Matrix (GLCM) and first order with two kernels for each method, namely Gaussian and Polynomial. Classification using SVM method is carried out by testing several parameters such as the value of C, gamma, degree and varying the pixel spacing values ​​in GLCM, which usually in previous studies only used the default pixel spacing. The dataset consists of 500 mammogram images containing 250 benign and malignant images, respectively. This study is expected to find out the best method with the highest accuracy between these two texture feature extractions and and able to distinguish between benign and malignant classes correctly. The result achieved that Gray Level Co-Occurrence Matrix (GLCM) feature extraction method with both Gaussian and Polynomial kernel yields the best performance with an accuracy of 89%

Perancangan Sistem Pemantauan Lokal dan Jarak Jauh bagi Panel Surya

Solar photovoltaic monitoring system can be directly conducted locally for the experimental purposes. However, indirect or remote monitoring is also needed since the solar panel are often installed in a a high place, rural location, or remote area. This study offers a dual solar panel monitoring system i.e. local and remote. Local monitoring system consists of voltage, current, temperature and light intensity sensors that were integrated in a kit called PVmeter. The data in the local monitoring system were displayed on a LCD or on a PC monitor using data logger. While in the remote monitoring system, the data were uploaded to the internet and displayed on Thinkspeak website hence the data are accessible whenever and wherever needed. In the local system, monitored data were successfully displayed on *.txt file format for every 5 minutes. While in the remote system, the data were successfully displayed on Thinkspeak website with a mean transfer rate of 52.5 seconds

Simulasi Efek Jumlah Event Terhadap Respon Energi TLD LiF: Mg, Cu, P

The effect of different number of events on the bare thermoluminescent dosimeter (TLD) LiF:Mg,Cu,P chip energy response has been simulated using Geant4. This simulation aims to determine the optimum number of events with a minimum computational time. 14 photon energies in a range of 16–1250 keV with a range number of events 2×107 – 2×1012 were applied. A LiF: Mg, Cu, P chip with 4.5 mm diameter and 0.9 mm thick on the surface of 30×30 cm2 water phantom and a thin 10 µm slice of water (at 10 mm deep in the phantom) were considered as the sensitive volumes to calculate the respective absorbed dose DTLD and DW. The relative energy response R was calculated from the ratio of DTLD and DW for each energy normalised to DTLD and DW ratio of energy 662 keV. 2×109 number of events were found to be the optimum number of events with a minimum computational time.The simulation results were validated to the measurement results and the mean deviation of 0,59% was yielded. As the deviation are within the acceptable limit of ±25%, it was concluded that the results were considered satisfactory and the materials and physics processes applied in the code were correct

Seizure Detection in Epileptic EEG Using Short-Time Fourier Transform and Support Vector Machine

Epilepsy is the most common form of neurological disease. The electroencephalogram (EEG) is the main tool in the observation of epilepsy. The detection and prediction of seizures in EEG signals require multi-domain analysis, one of which is the time domain combined with other approaches for feature extraction. In this study, a method for detecting seizures in epileptic EEG is proposed using analysis of the distribution of the signal spectrum in the time range t. The EEG signal which includes normal, inter-ictal and ictal is transformed into the time-frequency domain using the Short-Time Fourier Transform (STFT). Simulations were carried out on varying window length, overlap and FFT points to find the highest detection accuracy. The frequency distribution and first-order statistics were then calculated as feature vectors for the classification process. A support vector machine was employed to evaluate the proposed method. The simulation results showed the highest accuracy of 92.3% using 25-20-512 STFT and quadratic SVM. The proposed method in this study is expected to be a basis for the detection and prediction of seizures in long-term EEG recordings or real-time EEG monitoring of epilepsy patients

Radiological risks related to natural radionuclide in Selected fish from east coast of peninsular, Malaysia

Systematic investigations are essential in establishing the current water quality because numerous industrial and anthropogenic sources are responsible for polluting the ecosystem along Peninsular Malaysia's east coast. Since aquatic stocks play a significant role in the daily diets of the surrounding populations, the present study used the ICP-MS technique to measure the levels of three natural radionuclides 232Th, 238U and 40K in three fish species collected from three locations along the east coast of Peninsular Malaysia. The activity concentration ranges from 23.13 ± 1.70 to 43.31 ± 2.10 Bq kg-1for 40K, 0.06 ± 0.01 to 0.33 ± 0.05 Bq kg-1 for 232Th and 0.11 ± 0.08 to 0.48 ± 0.10 Bq kg-1 for 238U. The determined activity concentration of radionuclides was used to estimate the annual effective dose and cancer risk. The findings showed that the predicted yearly effective doses (µSv year-1) for 232Th, 238U and 40K were 1.67, 0.70, and 11.92 correspondingly, which were much lower than the UNSCEAR recommendation and considered to be safe. Based on the estimated annual effective dose and a life expectancy of 70 years, the cancer risk factor for adults is predicted to be 3.00 × 10-5. Compared to the UNSCEAR cancer risk factor of 8.4 × 10-3 and ICRP cancer risk factor of 3.5 × 10-3, this value is much lower. According to the current study, the dose that locals consume from eating fish is safe for human consumption, relatively minimal, and does not impair human health

Determination of the radiological risk from the natural radioactivity in irrigation at selected areas of Peninsular Malaysia

This study involves a comprehensive analysis of 226Ra, 232Th, and 40K concentration from irrigation water samples. Water samples were obtained, and the physical parameters were examined. Subsequently, the corresponding radiological risks to human health were estimated. The concentration levels of 226Ra, 232Th, and 40K in water samples amounted to 1.51 ± 0.30, 0.17 ± 0.09, and 7.67 ± 3.07 Bq L-1, respectively, which were within the concentration levels reported in the literature from Malaysia and other countries worldwide. Based on the food intake rate by MoH and UNSCEAR, the annual ingestion effective dose (ID) and the cancer risks corresponding to radionuclide intake in irrigation were below the recommended maximum values. Meanwhile, the average hazard indices and annual outdoor effective dose (ED) amounted to 0.01 and 1.39 mSv year-1, respectively. It was inferred from the findings of this study that the water used as the sample does not have any significant radiological impacts to human body and is safe to be used as irrigation in the related area

Pemanfaatan marketplace tokopedia untuk pengembangan usaha dalam meningkatkan perekonomian di tengah dampak pandemi covid-19

Dampak pandemi Covid-19 bagi masyarakat Indonesia sangat luar biasa. Kebijakan pemerintah dalam membatasi kegiatan masyarakat mengakibatkan sektor ekonomi usaha mikro menjadi sektor paling terpuruk karena berkurangnya transaksi jual beli. Akibatnya, Usaha Mikro, Kecil, dan Menengah (UMKM) mengalami penurunan besar pada kegiatan ekonomi. Platform digital merupakan solusi dan cara dalam mempertahankan dan mengembangkan usaha. Di Indonesia sudah banyak pilihan marketplace yang dapat digunakan untuk meningkatkan usaha. Berbagai produk dapat dipasarkan melalui marketplace. Selain itu, marketplace memiliki keuntungan dalam memasarkan produk karena memiliki jaringan yang sangat luas. Oleh karena itu, sosialisasi dan pelatihan memanfaatkan platform digital sangat diperlukan untuk menghadapi pandemi Covid-19 ini. Masyarakat sasar anggota pemuda pengurus masjid Al-Fitroh memiliki latar belakang pendidikan Sekolah Menengah Akhir (SMA) dan belum mendapatkan pekerjaan tetap membutuhkan keahlian usaha untuk menghadapi pandemi. Oleh karena itu, pelatihan usaha dengan memanfaatkan marketplace Tokopedia diperlukan untuk meningkatkan dan mempertahankan daya ekonomi di masa pandemi atau di luar masa pandemi. Hasil dari survei menunjukkan bahwa peserta mendapatkan manfaat dari pelatihan ini dan memiliki ketertarikan untuk membangun usaha atau mengembangkan usaha secara online. Sehingga, peserta dapat beradaptasi dengan kondisi pandemi Covid-19 ini yang tidak bisa berjualan secara normal. Selain itu, pelatihan ini memiliki potensi untuk menghasilkan pengusaha baru