Usage of Unsupported Technologies in Websites Worldwide

Websites using unsupported 3rd party technologies (libraries, frameworks, plugins, etc) are generally not recommended, especially due to security issues that are left unfixed. However, upgrading to supported technologies is also challenging, hence not all web maintainers upgrade their technology dependencies. Measuring the existence of unsupported technologies in the wild may contribute to the sense of urgency in keeping technologies updated. Our research proposed a method to measure the existence of unsupported technologies in international websites, using HTTP Archive as the data source. The contribution from our research is the method as well as the snapshot result from January 2023 data. The method is composed of four steps, namely: identify the list of websites, identify technologies used, group by technology names and retrieve currently supported versions, and compare versions between usage and supported versions. From the January 2023 data, we found several interesting results. One is that the higher the website rank is, the higher the number of supported technologies used. Another finding was that worldwide websites also generally use more supported versions of technologies, compared to Indonesian websites. Further research may be performed for longitudinal analysis of technology support evolution

In silico study of the essential oil compounds of ginger and thyme on Coronavirus-2 receptors

Coronavirus-2 (SARS-Cov-2) is a virus that attacks the respiratory system and causes the Covid-19 pandemic. After the pandemic, prevention and appropriate therapy research continue to be carried out to anticipate the emergence of more dangerous viruses. In line with the culture of consuming herbs that has arisen due to the effects of the pandemic, in this study, an insilico screening was carried out for essential oil compounds produced by ginger and thyme herbs which have been widely consumed by the public. The aim of the research was to find the essential oil content that has the most potential as an antiviral against coronavirus-2. The research method was carried out in silico, including ligand preparation, receptor and method validation, and analysis of ligand-receptor binding interactions using the AutoDoc 4.2.6 program. As a comparison, a study was conducted on remdesivir and favipiravir, which have been used as antivirals. The three components that have the most potential based on the calculation of the free energy value, were determined by the ADMET parameters using the Admet lab 2.0 program. The results showed that the three components in the essential oil exhibited better interactions when compared to remdesivir and favipiravir at the 3-Cl protease and spike glycoprotein receptors. The results of the insilico study and ADMET prediction test showed that of the three most potent compounds, lamda-farnesen was the most potent and safe to us

The legal protection of domain names in Jordanian legislation and the rules of the unified domain name dispute resolution policy issued by ICANN

Introduction to The Problem: The problem of the study was that the Jordanian legislative system is devoid of any special legal regulation or even a system that defines domain names in terms of their nature and means of legal protection for them. There is only the “Registration Policy” that the Ministry of Digital Economy and Entrepreneurship is implementing to register national domain names. This policy only addresses the technical and procedural aspect of domain name registration without specifying its legal nature.Purpose/Objective Study: The purpose of the study is to illustrate the topic's uniqueness and theoretical and practical significance. Due to the lack of specific regulations in many countries and the rise of cases handled by courts in this area, it presents several practical and legal issues. Therefore, the study aims to shed light on this phenomenon and try to find the best solutions to it in light of Jordanian legislation and the rules of the Unified Policy for Resolving Domain Name Disputes issued by ICANN.Design/Methodology/Approach: In its preparation, the study relies on the descriptive and analytical approach by describing the case, citing relevant legal texts, analyzing them, and applying them to reality. This is done by analyzing the texts of the Jordanian national domain name registration policy and comparing it with the legal texts contained in the rules of the Unified Policy for Resolving Domain Name Disputes issued by the ICANN under study.Findings: The study recommended a number of recommendations, the most important of which is the need to enact legislation specific to national domain names to determine the nature of these names and their legal nature. This legislation also includes provisions for their legal protection, stipulating appropriate legal ways and means to confront the assault on them, and provisions for liability resulting from them.Paper Type: Research Articl

Protection of patient data privacy on IoT devices for healthcare in the era of smart cities: a health law perspective

Introduction to the Problem: The Internet of Things (IoT) has enabled the use of medical devices in the healthcare sector while presenting challenges in regard to the security and privacy of patients’ medical data. This article conducts a systematic literature review to evaluate the existing regulations related to the security and privacy of the patient’s medical data in real-time data collection through IoT in the context of a Smart City.Purpose/Study Objectives: This study aims to identify gaps in the existing regulations, analyze the implementation of these regulations in practice, and evaluate the impact of IoT technology on the privacy and security rights of patients’ medical information in the healthcare sector.Design/Methodology/Approach: The research employed a systematic literature review, by analyzing relevant articles, legal documents, and regulations. Data were examined from a case study of the implementation of IoT devices for healthcare in Smart Cities as well as interviews with legal experts in the field of healthcare services.Findings: The existence of the Electronic Information and Transaction Law, Personal Data Protection Law, and the latest Health Law provides the initial regulatory foundation for ensuring the security of personal data in the integrated governance of Smart Cities, especially in telemedicine services. Implementing regulations for these laws are necessary to technically accommodate the needs for the security of the patients’ data, ensuring that there is no imbalance between the provisions of the laws that are enacted and their implementation in the community.Paper Type: Research Articl

Standardization of Paku Lindung extract (Pneumatopteris callosa (Blume))

The standardization of the paku lindung extract was carried out to obtain new data regarding the standardization of the hedgehog extract which had not previously been established. In addition, this determination is carried out to obtain quality preparations in the form of a guarantee process, that the extract obtained has certain parameter values that are constant after the data has been determined. Extract standardization test includes specific parameters including organoleptic, soluble compounds in certain solvents. Non-specific parameter tests include drying shrinkage, moisture content, ash content, heavy metal contamination, microbial contamination. Chemical content test includes chromatogram pattern, determination of total flavonoid content. The yield of the resulting extract was 13.88±3.19% g. The test results of non-specific parameters include drying shrinkage 0.47±0.01%, moisture content 8.28±0.16%, total ash content 18.97±3.53%, acid insoluble ash content 1.69± 0.02%, total plate number 7.8x104±12.91 colonies/gram, yeast mold number 1x102±0.24 colonies/gram, heavy metal contamination of Cd, Cr and Pb negative and Fe of 73.88 ppm. The results of the specific parameter test include 85.55±4.29% water soluble compounds, 31.27±5.06% ethanol soluble compounds. The results of the chemical content test included the total flavonoid content of 16.6±17.60 mgEQ/g, the Rf value of the extract was the same as the Rf of quercetin with 5 variations of the mobile phase. The test results were carried out to meet the predetermined determination and provide new data on the standardization of the paku lindung extract

Adaptive Traffic Light Signal Control Using Fuzzy Logic Based on Real-Time Vehicle Detection from Video Surveillance

Intersections often become the focal points of congestion due to poor traffic signal management, reduced productivity, increased travel duration, gas emissions, and fuel consumption. Existing traffic light systems maintained constant signal duration regardless of traffic situations, resulting in green signals for lanes with no vehicle queues that increased waiting times in other lanes. Therefore, a real-time traffic signal optimization system using Fuzzy Logic control, utilizing vehicle queue and flow rate real-time data from video surveillance, is needed. This research used recorded video from surveillance cameras in Banten Province, Indonesia, during daylight conditions. Vehicle queues and flow rate data were used as parameters to determine traffic light signals. The YOLO algorithm obtained these parameter values, then served them as inputs for the Fuzzy Logic system to determine signal duration. The accuracy of the traffic situation estimation system fluctuated within a range of 40% to 100%. Simulation results showed an improvement of approximately 18% by evaluating the total number of vehicles that exited the queue and reduced vehicle waiting time by about 21% compared to the existing system on intersection efficiency. Consequently, the proposed system can reduce pollution and fuel consumption, contributing to urban sustainability and public well-being enhancement. Despite the improvements over the previous systems, the accuracy of the vehicle detection system may vary with traffic density based on the extent of occlusions present, which is an area that needs further refinement. This research's contributions include utilizing real-time video footage from surveillance cameras above traffic lights to obtain real traffic conditions and identify potential errors such as occlusion of overlapping vehicle due to very congested roads. Another contribution is the adjustment of the Fuzzy membership function based on the vehicle detection system's ability to ensure precise determination of green signal duration, even when the input data contains errors

The Effect of Growth Mindset and Grit on Career Decision Making Self-Efficacy in Fresh Graduates

Indonesia is experiencing significant economic growth and industrial development. The role of fresh graduates in shaping and supporting this growth is crucial. However, unemployment remains a challenge, with 7.86 million people unemployed as of August 2023, and approximately 12% of them being bachelor’s and diploma graduates. The limited availability of jobs cannot keep pace with the growing number of job seekers, which increases with population growth each year. Students who possess a growth mindset, high levels of grit, and strong self-efficacy tend to achieve better learning outcomes, as these traits encourage continuous self-improvement and skill development. Consequently, researchers believe that a growth mindset and grit can significantly influence career decision-making self-efficacy, particularly among fresh graduates. This study employed a quantitative research approach with a correlational design. The sampling technique used was non-probability sampling. The sample size was determined using G*Power software, resulting in a minimum sample of 472 respondents. Three adapted measuring instruments were used in the study. The results indicate that growth mindset and grit positively impact career decision self-efficacy by 22.5%, while 77.5% is influenced by other factors. These findings confirm that growth mindset and grit play a significant role in career decision self-efficacy

Medication-related burden of chronic renal failure patients at regional general hospital Sleman Yogyakarta

Patients with chronic renal failure must undergo lifelong treatment. The condition raises treatment-related responsibilities and may affect their treatment adhesion. The aim of this study was to determine the correlation between the burden of medication and the level of medication adherence among chronic kidney failure patients at Sleman Regional Hospital in Yogyakarta. This study took the form of observational study with a cross-sectional design. Data were collected using LMQ (Living with Medicine Questionnaire) and Visual Analog Sacle (VAS) overall burden to determine the burden and MARS (Medication Adherence Rating Scale) to determine medication adherence level. The samples in this study were 60 patients from all patients  undergoing hemodialysis who met the inclusion criteria. Sampling was taken using a consecutive sampling technique with inclusion criteria of patients willing to complete the questionnaire and patients diagnosed with chronic renal  failure aged more than 18 years. To determine the relationship between medication burden and medication adherence, data was examined using the Spearman test.  The results of this study showed that 40 patients (66.7%) had moderate medication burden and 50 patients (83%) had moderate medication adherence. There was a significant correlation between the LMQ score and MARS (correlation-coefficient = 0.581, p=0.000) and a significant correlation between the VAS score and MARS (correlation-coefficient= 0.651, p=0.000). Thus, it can be concluded that there is a positive relationship between treatment burden and the level of treatment compliance, where the higher the burden, the higher the level of compliance in chronic kidney failure patients

The effect of recompression and concentration of polyvinylpyrrolidone (PVP) K-30 on the quality of paracetamol tablets

Quality control during production is a critical process that ensures the quality of the tablets until it reaches the consumer. In the pharmaceutical industry, there is a possibility of reworking, including tablet recompression. Nevertheless, the recompression process may have affected the potential of PVP K-30 as a binder to reunite the particles of tablet ingredients. However, the difference of PVP K-30 concentration might be resulting in the differences of granule and tablet characteristics. This study aims to determine whether there is an effect of recompression and the difference of PVP K-30 on the quality of paracetamol tablets. The effect of recompression and the difference of PVP K-30 was seen based on whether there is a significant different on physical properties of the mixture of tablet ingredients (mixture’s flow rate and compressibility) and the tablets (compatibility and tablet’s hardness, friability, and disintegration time) from the formula with a concentration of 2% w/w and 4% w/w PVP K-30 after experiencing 2 times of recompression. Paracetamol tablets were made by wet granulation method through the stages of granulation, lubrication, physical properties testing of the mixture, tablet compression, physical properties testing of tablets, crushing, and recompression. Data analysis was performed statistically using the Shapiro-Wilk normality test, followed by two-way Analysis of Variance (ANOVA) or Kruskal-Wallis test and Post Hoc Mann Whitney test. The results showed there was an effect of recompression and different concentration of PVP K-30 on the potential of PVP K-30 as a binder as seen from significant differences in the physical properties of the mixture and tablets in each test group

XgBoost Hyper-Parameter Tuning Using Particle Swarm Optimization for Stock Price Forecasting

Investment in the capital market has become a lifestyle for millennials in Indonesia as seen from the increasing number of SID (Single Investor Identification) from 2.4 million in 2019 to 10.3 million in December 2022. The increase is due to various reasons, starting from the Covid-19 pandemic, which limited the space for social interaction and the easy way to invest in the capital market through various e-commerce platforms. These investors generally use fundamental and technical analysis to maximize profits and minimize the risk of loss in stock investment. These methods may lead to problem where subjectivity and different interpretation may appear in the process. Additionally, these methods are time consuming due to the need in the deep research on the financial statements, economic conditions and company reports. Machine learning by utilizing historical stock price data which is time-series data is one of the methods that can be used for the stock price forecasting. This paper proposed XGBoost optimized by Particle Swarm Optimization (PSO) for stock price forecasting. XGBoost is known for its ability to make predictions accurately and efficiently. PSO is used to optimize the hyper-parameter values of XGBoost. The results of optimizing the hyper-parameter of the XGBoost algorithm using the Particle Swarm Optimization (PSO) method achieved the best performance when compared with standard XGBoost, Long Short-Term Memory (LSTM), Support Vector Regression (SVR) and Random Forest. The results in RSME, MAE and MAPE shows the lowest values in the proposed method, which are, 0.0011, 0.0008, and 0.0772%, respectively. Meanwhile, the  reaches the highest value. It is seen that the PSO-optimized XGBoost is able to predict the stock price with a low error rate, and can be a promising model to be implemented for the stock price forecasting. This result shows the contribution of the proposed method