Journal Of Natural Sciences And Mathematics Research
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Design of an Arduino-based automatic sound timer system for mosques and prayer rooms
Full text linkThe uncontrolled use of sound systems in mosques, especially after the call to prayer and iqomah, often leads to waste of energy and disturbances to the surrounding environment. This research aims to develop an Arduino-based automation system that can set the time of turning on and off the sound system in the mosque according to the adhan schedule, in order to improve operational efficiency and reduce electricity consumption. The system is designed using an Arduino UNO microcontroller, which regulates the sound device via a relay based on manually entered timing. Testing was carried out using Wokwi software simulations, and the results were then applied to a physical prototype. Testing is carried out with various time settings (5, 10, 15, and 20 minutes) to assess the accuracy and reliability of the system. The test results showed that the system was able to control the sound device with a 100% success rate in all the times tested. This system has proven to be effective in reducing the duration of unnecessary use of sound devices, potentially saving energy. The developed system provides a practical solution to reduce energy waste in mosques and improve the operational management of sound devices. Further implementation of this system in mosques can provide significant social and environmental benefits, especially in terms of congregational comfort and energy savings. Field testing as well as the development of IoT-based technologies in the future can expand the functionality of these systems
Efficiency of new Canonical polynomials in Solving nonlinear Fractional Integro-Differential equations
Full text linkThis paper is aimed to solve nonlinear fractional integro-differential equations, specifically of the Volterra-types, utilizing newly constructed versatile canonical polynomials. The technique involves the use of the Lanczos method. The popular numerical method known as the collocation method is presented to evaluate the evolving equations and subsequently to determine the values of the embedded unknown coefficients. The equations exhibit both derivatives and integrals. The resulting approximate solutions are compared with the given exact solutions. Numerical experiments are conducted to showcase the efficiency and accuracy of the technique, which is achieved by estimating the errors in the approximate solutions in order to significantly establish the convergence of the method. The mathematical tool utilized to obtain the required results is Maple 18 software package
Dynamics of proton tunneling in Hydrogen-Bonded systems through Green's function formalism
Full text linkThis study proposes a new theoretical model based on Green's function formalism for studying proton tunneling via hydrogen bonding. This approach allows calculating the tunneling probability and the tunneling energy that proton transfer occurs along a given path inferred a priori. The method is extended to multiple protons tunneling, characterizing the behaviour of some biological molecules. Specifically, the cases of the proton transfer in the Fujicurin A molecule and the double proton tunneling in the Guanine-Cytosine base-pair are investigated. The new approach is an alternative to those present in the literature. It allows straightforwardly predicting the mechanisms of intramolecular and intermolecular proton transfers involving the rearrangement of conjugated electrons
Isolation and characterization of Humic Acid from organic waste as an adsorbent for Rhodamine B
Full text linkHumic acid compounds are organic materials distributed across various terrestrial and aquatic ecosystems, playing a crucial role in environmental pollutant absorption. This study aims to isolate and characterize humic acid from organic waste as an adsorbent for rhodamine B. The isolation process of humic acid was conducted using the extraction method with 0.5 N NaOH solution followed by acidification using 3 M HCl solution. Characterization was carried out using a UV-Vis spectrophotometer and Fourier Transform Infrared (FTIR) spectrophotometer. The UV-Vis characterization results showed that the maximum wavelength of humic acid is 286 nm. FTIR analysis of humic acid indicates the presence of functional groups such as hydroxyl, carboxylate, and aromatic groups, consistent with the typical characteristics of humic acid. The adsorption kinetics was determined by interacting rhodamine B with humic acid after determining the optimal pH of 4, optimal time of 30 minutes, and optimal concentration of 20 ppm. The research results indicate that the adsorption kinetics of rhodamine B on humic acid follows pseudo-second-order kinetics with a reaction rate of 0.0566 min?¹ and follows the Freundlich adsorption isotherm
An unsupervised machine learning algorithm approach using K-Means Clustering for optimizing Surface Wave Filtering in seismic reflection data
Full text linkSurface waves often cause significant noise in seismic data, complicating the interpretation of subsurface structures. Traditional filtering methods, such as FK filtering, usually struggle with non-stationary noise and require extensive manual parameter tuning. This study explores the effectiveness of using K-means clustering, incorporating attributes such as amplitude, frequency, and phase to filter surface waves from seismic data. Synthetic seismic data were first generated to test the proposed method, ensuring its robustness before application to real field data. Attributes were extracted from each seismic trace, including instantaneous amplitude, frequency, and phase. These attributes were used as input parameters for the K-means clustering algorithm. The identified clusters corresponding to surface waves were then used to filter these waves from the seismic data. The K-Means clustering effectively differentiated surface waves from reflected waves in both synthetic and real seismic datasets. The method demonstrated that by including phase as an attribute, alongside amplitude and frequency, the accuracy of surface wave detection and filtering significantly improved. The synthetic data showed a clear separation of wave types, validating the method. When applied to real field data, the approach consistently removed surface waves, clarity of seismic reflections crucial for subsurface analysis
Chemical analysis of Cyproheptadine Hydrochloride in appetite-stimulating herbs marketed in Banyumas regency: ensuring consumer safety
Full text linkJamu, a traditional Indonesian herbal medicine, is widely used in traditional healing practices nationwide, including the Banyumas Regency. The Indonesian government has implemented restrictions that forbid the inclusion of medicinal compounds in jamu, as their unregulated usage poses possible health hazards. Cyproheptadine hydrochloride is a frequently encountered medicinal component in appetite-stimulating herbs. However, the extent of adulteration of cyproheptadine hydrochloride in appetite-stimulating herbs marketed in Banyumas Regency is undisclosed. This study purposed to analyze and quantify the presence of cyproheptadine hydrochloride in appetite-stimulating herbs that are available for sale in the Banyumas Regency. The aim was to inform customers about these herbs' possible pharmaceutical ingredient content. The study utilized a qualitative analysis of thin-layer chromatography (TLC) and a quantitative analysis with a UV-Vis spectrophotometer. Fourteen samples of appetite-stimulating herbs in powdered, capsule, and tablet forms were gathered from different areas within the Banyumas Regency. Qualitative analysis revealed cyproheptadine hydrochloride in two herbal samples, SNM TG and SNM AM. The quantitative examination revealed that the content of cyproheptadine hydrochloride in SNM TG was 10.92 mg/5g, whereas in SNM AM, it was 7.93 mg/5g. These findings indicate that there have been breaches of regulations, and individuals who ingest these herbs may be susceptible to health problems. Further investigation is required to analyze a broader range of appetite-stimulating herbal samples, particularly those in liquid form, to ascertain the level of contamination with cyproheptadine hydrochloride and provide essential data for health regulations
Investigating visual engagement of Generation Z with presidential campaign infographics through Eye-Tracking technology
Full text linkThis study was designed to investigate the visual engagement of Generation Z with Indonesian presidential election campaign infographics utilizing eye-tracking technology. Notably, Generation Z forms a significant segment of first-time voters in the 2024 General Election and plays an integral role in political decision-making processes. Despite their pivotal role, a marked disengagement with political activities among this demographic presents significant challenges. Prior research has demonstrated that visual attention is modulated by experiential factors and personal biases. Consequently, this investigation seeks to elucidate the impact of infographics on the visual attention of participants with pre-established preferences for presidential candidates. Employing eye-tracking technology facilitated an objective assessment of the participants' subconscious reactions to the infographics. This study analyzed the distribution of visual attention across six defined Regions of Interest (ROI) among 60 participants. The findings reveal that 50% of the participants directed their gaze predominantly at the names of the candidate pairs, 27% at the image of the presidential candidate, 15% at quotes, 5% at the image of the vice-presidential candidate, 2% at the candidate number, and 1% at the vision statement. Additionally, it was observed that 55% of the participants consistently fixated on the infographics that corresponded to their preferred candidate pair from the onset to the conclusion of the recording, while 45% demonstrated variability in their viewing patterns. These insights afford valuable implications for political strategists aiming to forge more effective communication strategies with Generation Z, thereby enhancing their engagement in the political discourse, particularly in the context of general elections
Enhancing the productivity of irrigated rice fields in West Nusa Tenggara through utilizing Multilayer Perceptron (MLP) and Self-Organising Maps (SOM)
Full text linkAs Indonesia's population grows, ensuring a stable food supply becomes increasingly important. Recent changes in weather patterns have significantly impacted food production, particularly rice farming. In West Nusa Tenggara (NTB), a key area for rice production, maintaining consistent output is crucial. However, varying responses to unpredictable weather have led to significant differences in productivity across NTB's regencies and cities. This study aims to enhance the productivity of irrigated rice fields in NTB by predicting productivity levels for 2023 to 2024 using the best multilayer perceptron (MLP) model. We will compare 5 MLP model architectures to identify the optimal model for the prediction process. We will use the prediction results to cluster areas regionally through the self-organizing map (SOM) algorithm. We used the Davies-Bouldin Index (DBI) to determine the optimal number of clusters. This research compared DBI values for cluster counts of 2, 3, 4, and 5, determining the optimal cluster number by the smallest DBI value. The lowest DBI is 0.391 observed for 3 clusters. From this clustering, Cluster 1 consists of 7 regencies/cities with the lowest productivity level, Cluster 2 contains 1 regency with a moderate productivity level, and Cluster 3 includes 2 regencies/cities with the highest productivity level. The study concludes that the 7 regencies/cities in Cluster 1, identified as having low productivity require greater focus from local governments to optimize land area and paddy yields to enhance productivity in those areas
Numerical computational approach for 6th order boundary value problems
Full text linkThis study introduces numerical computational methods that employ fourth-kind Chebyshev polynomials as basis functions to solve sixth-order boundary value problems. The approach transforms the BVPs into a system of linear algebraic equations, expressed as unknown Chebyshev coefficients, which are subsequently solved through matrix inversion. Numerical experiments were conducted to validate the accuracy and efficiency of the technique, demonstrating its simplicity and superiority over existing solutions. The graphical representation of the method's solution is also presented
Analysis of return period and seismic risk of Shallow Earthquake occurrence in Cianjur and surrounding areas
Full text linkDetermination of the seismic risk and return period of shallow earthquakes in Cianjur and surrounding areas is very important as a reference in earthquake disaster mitigation programs. Within this return period, structural and non-structural conditions can be prepared in stages that are ready to face disasters if the earthquake recurs. In this study used the least squares statistical method to determine the relationship between frequency and magnitude, level of risk, and earthquake return period. The earthquake data used in this study is sourced from the earthquake catalog of the United States Geological Survey (USGS) spanning 50 years (1973 – 2023). A total of 57 shallow earthquakes that occurred in Cianjur area and its surroundings at coordinates (06°-08°S and 106°-108°E) with magnitude greater or equal to 5.0 at a depth of 0-60 km were used as sample data. Based on the results of data processing and analysis, the return periods are 3.17 to 29.1 years for earthquakes with magnitudes between 5.0 and 6.0, and 29.1 to 267.38 years for earthquakes with magnitudes between 6.0 and 7.0.. Earthquake risk for 10 to 20 years with magnitude greater than 5.0 is 95.74 to 99.82 %, with magnitude greater than 6.0 is 20.09 to 49.70 %, and with magnitude 7.0 is 3.67 to 7.21 %. From the results of processing and analysis of the earthquake data, it shows that the Cianjur area and its surroundings are earthquake-prone areas with a high risk