Ultrasound Image Synthetic Generating Using Deep Convolution Generative Adversarial Network For Breast Cancer Identification

Breast cancer is the leading cause of death in women worldwide; prevention of possible death from breast cancer can be decreased by early identification ultrasound image analysis by classifying ultrasound images into three classes (Normal, Benign, and Malignant), where the dataset used has imbalanced data. Imbalanced data cause the classification system only to recognize the majority class, so it is necessary to handle imbalanced data. In this study, imbalanced data can be handled by implementing the Deep Convolution Generative Adversarial Network (DCGAN) method as the addition of synthetic images to the training data. The DCGAN method generates synthetic images with feature learning on a Convolutional Neural Network (CNN), making DCGAN more stable than the basic generative adversarial network method. Synthetic and original images were further classified using the CNN GoogleNet method, which performs well in image classification and with reasonable computation cost. Synthetic ultrasound images were generated using a tuning hyperparameter in the DCGAN method to adjust the input size on GoogleNet for imbalanced data handling. From the experiment result, the implementation of DCGAN-GoogleNet has a higher accuracy in handling imbalanced data than conventional augmentation and other previous research, with an accuracy value reaching 91.61%, which is 1% to 4% higher than the accuracy value in the previous method

User-Centered Design-Based Approach in Scheduling Management Application Design and Development

The process of manually making and setting course schedules using Microsoft Excel is ineffective, time-consuming, and still prone to errors. This research develops a website-based scheduling management application with a case study at SMK Pariwisata Margarana so that it can solve scheduling problems manually. The UserCentered Design (UCD) method is applied in the application prototype design stage. Open interviews, field observations, simulations, and questionnaires were used as research data collection methods. Three iterations were carried out at the prototype design stage to fulfill all user needs. The high-fidelity prototype in the last iteration is then implemented into an application. Application quality is measured using ISO/IEC 25010 with five characteristics. The test results on usability characteristics show that the scheduling management application obtains an average usability score of 91.2%. The appropriateness recognizability sub-characteristic obtained the highest usability score of 93.53%. UCD can help produce an application that can meet all the user’s needs when implemented in the application design phase

Project Delay Risk Assessment

Maintenance activities on power plant projects, which are located in remote areas, are prone to risks related to project delay due to the high complexity of work and limited completion time. This research aimed to fill the existing research gap by developing a delay risk assessment of those projects using a probability impact matrix, which is then transformed into a fuzzy set theory. A case study has been undertaken to represent this research topic at three PLTMGs in Nusa Tenggara. The research steps were potential delay risks identification, critical risk assessment, and risk response development. The results show that the critical risks are lack of skilled and experienced manpower, delay in material and equipment delivery, poor communication and coordination between the contractor and the client, unavailability of materials in the local market, and incomplete material received. Several risk responses are provided in this research, such as strengthening the qualification of the job vacancy, having regular training or sharing sessions before the project execution, and having a stock of emergency spare parts in the central warehouse

Analysis of Level Team Effectiveness in The Implementation of Scrum Using Evidence-Based Management (Case Study: Company A as A Fintech Industry)

In implementing Scrum in Company A, which is a fintech company, there is a Scrum Master who is responsible for ensuring the effectiveness of the Scrum team. The Scrum Master of Company A still uses the velocity chart to measure team effectiveness. Still, the use of the velocity chart itself cannot describe the level of responsiveness of the team in delivering products to users. In this study, the applica- tion of EBM is used as a metric to replace the velocity chart in analyzing the level of effectiveness of the Scrum team in Company A. Through FGDs with senior Scrum Masters. The EBM metric was selected to be used in the analysis. The application of EBM is carried out by collecting primary data from each team and secondary data from company data. Data from each team was analyzed and weighted. The results of this study indicate the effectiveness score of each team. Based on these scores, the Scrum Master can determine which team’s process needs to be improved. This research can be used as an illustration for companies that implement Scrum in mea- suring the effectiveness of Scrum teams

Data Quality Management Strategy To Improve Remote Sensing Data Quality: A Case Study On National Remote Sensing Data Bank

National Remote Sensing Data Bank (Bank Data Penginderaan Jauh Nasional; BDPJN) is the operational implementer in the field of remote sensing to meet the needs of national data on remote sensing images. Remote sensing images are essential in the Indonesian government for various needs, such as in regional (spatial planning, city boundaries), disaster (forest fires, floods, landslides, earthquakes, volcanic eruptions), plantation, natural resources, and environment sectors. Quality management of BDPJN’s satellite images becomes challenging due to the increasing number of products owned and users annually. For this reason, a data quality management strategy is needed to guarantee and improve the quality of BDPJN data. To develop such a strategy, an assessment of the maturity of BDPJN’s data quality man- agement was conducted from the aspect of data processing by implementing Loshin’s Data Quality Management Maturity Model (DQM3) to find out the characteristics that were lacking. The results were then mapped based on Data Quality Management (DQM) activities in DAMA-DMBOK as a recommendation for data quality management strategies. This study applies quantitative research where data collection was done by distributing questionnaires to 24 respondents who are data stewards of medium, high, and very high-resolution mosaic images. Based on the assessment, BDPJN is in the maturity level of Defined to Managed. The recommendations are 21 DQM activities that can be carried out to improve BDPJN data quality

Probabilistic Scheduling Based On Hybrid Bayesian Network–Program Evaluation Review Technique,

Project scheduling based on probabilistic methods commonly uses the Program Evaluation Review Technique (PERT). However, practitioners do not widely utilize PERT-based scheduling due to the difficulty in obtaining historical data for similar projects. PERT has several drawbacks, such as the inability to update activity dura- tions in real time. In reality, changes in project conditions related to resources have a highly dynamic nature. The availability of materials, fluctuating labor productiv- ity, and equipment significantly determine the project completion time. This research aims to propose a probabilistic scheduling model based on the Hybrid Bayesian Network-PERT. This model combines PERT with Bayesian Network (BN). BN is used to accommodate real-time changes in resource conditions. The modeling of BN diagrams and variables is obtained through an in-depth literature review, direct field observations, and distributing questionnaires to experts in project scheduling. The model is validated by applying the proposed model to a 60 m concrete bridge construction project in Indonesia. The simulation results of the proposed model are then compared with the case study project to assess the model’s accuracy. The result of the study shows that the proposed hybrid Bayesian-PERT model is accurate and can eliminate the weaknesses of the PERT method. Besides being able to provide an accurate prediction of project completion time (93.4%), this model can also be updated in real-time according to the actual condition of the projec

Deposition Silver Based Thin Film on Stainless Steel 316l as Antimicrobial Agent Using Electrophoretic Deposition Method

SUS316L stainless steel has been widely used in medical applications. However, some germs frequently adhere to the device surface, resulting in infections following implantation surgery. Unfortunately, the material lacks antibacterial characteristics that prevent microorganisms from adhering to the surface. This study aims to use electrophoretic deposition to deposit chitosan/silver (Ag) as an antibacterial agent on stainless steel 316L. The antimicrobial effects of chitosan and silver are well established. During the deposition, the rectifier voltage was adjusted to a constant 10 volts with a suspension pH range of 2.7 to 5.1. The effect of varying the pH of the suspension on the physical, mechanical, and antibacterial properties of chitosan/Ag thin films was investigated. The materials’ structure and morphology were studied using X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier- transform infrared spectroscopy (FTIR). The antimicrobial inhibition was examined using the Kirby-Bauer antimicrobial test. The results reveal that increasing the pH of the suspension causes an increase in the thickness, size, and aggregation of the chitosan/Ag thin film. The highest thickness achieved during deposition with a pH 5.1 suspension is 5.265 m. The best antibacterial agent is achieved at a pH 3.5 suspension sample with an inhibitory zone diameter of 4 m

Epidemiology and Characteristics of Resistant Typhoidal Salmonella Strains Prevalent in Lafia, Nigeria

Resistance to antibiotics by pathogens is a burden to disease management. The study characterized Salmonella species in patients with fever and determined their antibiotic susceptibility patterns in Dalhatu Araf Specialist Hospital Lafia, Nigeria. Faecal samples were collected from 400 patients, and Salmonella species were isolated. The isolates were rested against ten antibiotics to determine their multi-drug and extensively drug-resistant capabilities, after which molecular characterization was done. Male patients between the ages of 21 to 30 years had the highest prevalence of 17(44.7%) of the pathogen, and they were the most susceptible among those who regularly drank water from boreholes (19(50.0%)). Augmentin with 44(73.0%) Salmonella susceptibility was the most effective antibiotic, while gentamycin, ampicillin, chloramphenicol, and cotrimoxazole had the isolates obtaining resistance of 60(100%), 59(98.0%), 57(95.0%), and 56(93.4%) respectively. Only six of the 60 Salmonella isolates were not multidrug-resistant, while 25 were extensively drugresistant. Isolates S9 and S25 with staG genes were the only Salmonella typhi found in the study; others with ttr genes were of the Salmonella genera. The study concludes that the first-line antibiotics administered to patients with typhoid fever are no longer effective; hence, proactive measures should be put in place to surmount the observed challenge

Evaluation Of Dehydration Performance Of Belitung Taro (Xanthosoma Sagittifolium) Using Tray Dryer

Belitung Taro (Xanthosoma sagittifolium) is a plant that can be processed into various food products. The high-water content of taro and the lack of a precise drying system made this material easy to rot. This study aims to evaluate the dehydration performance of tray dryers to reduce the water content of Belitung Taro. The independent variables used were air velocity (3-6 m/s), taro thickness (1-4 mm), and drying time (30-120 min). The results showed that the optimum drying time of taro is 30 min. The dryer airflow of 5 m/s significantly reduces the water content. The thickness of the slices positively affects the drying rate. The lowest water content was obtained in drying with a thickness of 1 mm. The ANOVA results show the effect of thickness, time, and flow rate variations on the drying rate. Three types of mathematical modeling are used to estimate moisture content: Newton, Page, and Modified Page. The Modified Page equation was preferred to detect the moisture content of the taro. From this study, the optimum condition of the tray dryer can be the best solution to dehydrate Belitung Taro effectively and efficientl

Feature Selection Using Hybrid Binary Grey Wolf Optimizer for Arabic Text Classification

Feature selection in Arabic text is a challenging task due to the complex and rich nature of Arabic. The feature selection requires solution quality, stability, conver- gence speed, and the ability to find the global optimal. This study proposes a feature selection method using the Hybrid Binary Gray Wolf Optimizer (HBGWO) for Ara- bic text classification. The HBGWO method combines the local search capabilities or exploratory of the BGWO and the search capabilities around the best solutions or exploits of the PSO. HBGWO method also combines SCA’s capabilities in finding global solutions. The data set used Arabic text from islambook.com, which consists of five Hadith books. The books selected five classes: Tauhid, Prayer, Zakat, Fasting, and Hajj. The results showed that the BGWO-PSO-SCA feature selection method with the fitness function search and classification method using SVM could per- form better on Arabic text classification problems. BGWO-PSO with fitness function and the classification method using SVM (C=1.0) gives a high accuracy value of 76.37% compared to without feature selection. The BGWO-PSO-SCA feature selec- tion method provides an accuracy value of 88.08%. This accuracy value is higher than the BGWO-PSO feature selection and other feature selection methods