Reviewerly/exHarmony huggingface dataset:
Fertilizer Classification for Identifying Effectively Commodity to The Crop Land Using Naïve Bayes and Decision Tree Classifier

Agriculture has a crucial role in meeting the food needs of the community and other farmer groups. One of the efforts to empower farmers is through farmer groups that aim to increase productivity, income, and welfare among farmers. Farmer groups must develop communities as a condition for obtaining subsidized fertilizer from the government. This study uses machine learning classifier methods, especially ID3 and Naïve Bayes algorithms, to identify farmer group communities’ data and predict subsidized fertilizer orders for subsectors and commodities. The evaluation show that both classification algorithms have a high accuracy rate, reaching about 99%. The ID3 algorithm provides high precision for the Urea fertilizer class, while Naïve Bayes has a lower precision for the nitrogen, phosphorus, and potassium (NPK) class. However, Naïve Bayes showed a higher recall value for the NPK class. This algorithm provides valuable insights and information to more effectively manage farm resources. The results of this research are expected to increase agricultural output, improve the welfare of farmers, and support community food security. In conclusion, this study successfully used machine learning to predict subsidized fertilizer orders for subsectors and commodities. Both algorithms give accurate results, and the use of any of them depends on individual preferences and needs.
Presentation of Strategic Information in the Agriculture Domain at the Agriculture Office of Garut Regency using Data Visualization

The purpose of this research is to produce the right visualization to help the Food Crops Sector obtain the information needed more quickly. The form of information presentation uses tables in Microsoft Excel, resulting in the field of food crops taking longer to get information. So that it hampers the understanding of information and policymaking. The method used in this research is data visualization. Based on research on data visualization, it is stated that effective data presentation is by transforming data into visual form. This research produces a visualization design and is implemented in the form of a prototype. The next stage is to test the results of the prototype using the usability testing method for food crop staff. Based on the test results, it can be concluded that the prototype of food crop data visualization can help the food crop field understand the information needed more quickly.
Radar Engineering Immersive Laboratory (REIL) application to support Air Traffic Surveillance Radar Engineering Training

Virtual Laboratory provides flexibility and reduces the cost of traditional laboratory, integration of Augmented Reality in a virtual laboratory in the chance for aviation engineering learning such as Radar training. This study's purpose is to develop a virtual laboratory augmented reality-based to support radar training, by using prototyping dan the RAD method of the Radar Engineering Immersive Laboratory (REIL) built related to the International Civil Aviation Organization competency-based education framework. The architecture consists of a Learning Management System, Virtual Laboratory activity, and troubleshooting. The result shows the dynamic 3D depiction of each stage of the learning process in the REIL program ensuring student learning enjoyment and ease.
Analysis of Educational Website Display in Indonesia and Japan

The aim of this research is to describe the functional description of the dimensions of usability, graphic design, content, compatibility, navigation system, and loading time. Functions in user perception of the design of university websites from UNIKOM and universities in Japan to compare the two websites in terms of design. This research was carried out using the research object website unikom.ac.id and waseda.jp variables which used usability, navigation system, graphic design, content, compatibility as references. Every visitor will feel comfortable when the website has good design elements. If a website has a high rating, then of course the information published reaches the main users very quickly. So, to achieve this goal, an analysis method was applied using CNET (builder) and the book The Principle of Beautiful Web Design. Components in CNET (builder) include Usability, Navigation System, Graphic Design, Content, Compatibility, Loading Time, Function. Meanwhile, The Principle of Beautiful Web Design describes websites from Defining Good Design, Web Page Anatomy, Grid Theory, Balance, Unity, Bread and Butter Layouts, Fresh Trends
Adaptive Vehicle Headlights Direction System based on Road Lane Detection

Almost half of the vehicle accident fatalities occur at night. Driving at night is riskier. Even the most familiar roads can look distant in the dark. It becomes difficult to see other vehicles, pedestrians, and other objects. One of the problems is the lack of light, especially at road bends, because the vehicle headlights are always straight. The purpose of the research is to design the adaptive vehicle headlights direction that is always facing the road even if it is on the curving road. There are several processes to implement the system are detecting roads, processing detected road conditions and controlling the direction of the headlights. To detect the road using the camera sensor and image processing based the road lane and recognizing it using Hough Transform algorithm. the results of road detection are processed to drive the servo motor which adjust the direction of the lights. The implemented system works with the success rate 76.63% with accuracy error rate 1.28 degrees for the left bend and 80% with accuracy error rate 1.45 degrees to the right bend.
Envisioning Risk Management for Smart Contracts: A Conceptual Model

This study proposes a smart contract risk management model built on the NIST Risk Management Framework (RMF) to help identify, assess, and manage the risks of smart contracts. While smart contracts are beloved as a means to automate and disintermediate business processes, their security vulnerabilities can be critical. The main issue discussed in this paper is the lack of a holistic approach to risk management smart contracts. The resulting framework consists of six steps: Risk identification, assessment, prioritization, mitigation, testing, and continuous monitoring (and was developed through reviewing existing literature on smart contract security and the NIST RMF). It is recommended that a case study be performed to prove the proposed model's effectiveness in managing the risks of smart contracts and minimizing financial losses and reputational harm. The paper presents a risk management framework for smart contracts to increase trust and adoption to enhance security while reducing financial losses and reputation damage. This has wider implications for the security of smart contracts and can be used as a starting point for future work. This study is expected to significantly contribute to smart contract security by introducing an organized way to address these contracts' risks using the NIST RMF.
Implementation of Modified Ant-Colony Optimization Algorithm using Crazyflie Nano Quadcopters

Multi-UAV systems have been widely used in various fields, including agriculture. Effective coordination and task allocation are essential components of these systems. This study focuses on optimizing the coordination of multi-UAVs by adapting Modified Ant Colony Optimization (M-ACO) and K-Means Algorithms. Prior to implementing these algorithms, it is necessary to configure a multi/swarm-UAV system. In this study, we have configured the Crazyflie UAVs and Crazyswarm software for a laboratory experiment. Subsequently, the configured swarm-UAV system undergoes testing using the M-ACO algorithm, and the results are compared with the actual positions in real experiments. The experiments revealed that the average position errors for the UAVs are as follows: -0.084 ± 0.033 cm for the x-axis, -0.251 ± 0.2 cm for the y-axis, and 0.01 ± 0.09 cm for the z-axis. These results indicate that, in general, the UAVs can achieve their target positions with a relatively low margin of error.
A Spatio-Temporal Switchable Data Prefetcher for Convolutional Neural Networks

In this paper, we propose a spatio-temporal switchable data prefetcher that can adapt to the locality characteristics of CNN models. The proposed prefetcher records the recent delta history by leveraging two tables. The first table predicts spatial address patterns by comparing the delta score with the last delta, while the second table predicts temporal address patterns by recording and reordering the delta sequence from the delta history. Consequently, the proposed prefetcher is capable of appropriately switching between these two prediction methodologies based on spatial and temporal localities. The experimental results on CNN inference workloads show that we achieved high average accuracy of 83.8% and coverage of 81.6%, and hence the proposed prefetcher improves system performance by 33.8% over a baseline with no data prefetcher and 21% over the best-performing prior spatio-temporal prefetcher.
Ransomware Resilience: Investigating Organizational Security Culture and Its Impact on Cybersecurity Practices against Ransomware Threats

The increasing threat of ransomware attacks in an interconnected and digital world presents important hurdles for cybersecurity, prompting further examination into how organizational security culture affects their ability to withstand these malicious threats. This study examines the impact and importance of organizational security culture in ransomware threat mitigation. We have surveyed five organizations, giving points from 1 to 5 for each question on cultural factors, leadership support, employee awareness and involvement (compliance), communication, behavior change or BBS practice incorporation, learning/training delivery methodology, and Size and industry impact on their security culture. The results indicate that a robust security culture, with leadership and effective communication, builds stronger resilience to ransomware. Organizations with jointly accountable cybersecurity and training practices are highly efficient. Suggestions range from establishing a secure environment to increasing management buy-in and integrating compliance. This work helps advance our understanding of ransomware resilience and highlights the key role of organizational security culture. The resulting learnings can help to inform organizations' security posture, ultimately helping them better protect their defenses against ransomware threats.
Analysis of predictive coding model with hierarchical reservoir computing for modeling Stroop effects

Human beings take many times to recognize or even misrecognize some visual information because of the mismatch of colors and meanings under some situations, that is called Stroop effects. Including Stroop effects, the cognitive process of the brain is still elusive. As a first step of understanding the cognitive process, we construct and analyze a predictive coding model with hierarchical reservoir computing for modeling Stroop effects in this study. The model learns respectively colors, a shape, and a gender of normal images where a pictogram is illustrated, and that predicts their gender from the input images. Normal and abnormal images are applied to the model, whose gender predictions succeed by 90% for the normals but by 18% for the abnormals.
Preliminary Study on Reducing Memory Overhead in Accelerating Quantum Computer Simulations Using PIM Technology

Recent developments in quantum algorithms have demonstrated the promise of quantum computers, even in the era of noisy intermediate-scale quantum computing (NISQ). However, accessing real quantum computers remains challenging due to cost and long wait times. Additionally, the limited scale and noise of these computers can impact the outcomes of algorithms. To overcome these challenges, researchers often rely on quantum computer simulators. However, these simulators, which use CPUs and/or GPUs, suffer from high memory overhead. To address this issue, we propose a processing-in-memory (PIM)-based technology for quantum computer simulation. We confirmed that our proposed approach reduces data movement cycles in memory by 2.76 times on average compared to traditional execution on CPUs.
A Study of Changes in Prediction Performance Influenced by Attractor State in Oscillator Reservoir Computing

AI technologies have proven their capabilities in solving complex problems, but they often require significant computational resources and power. This study proposes a reservoir computing (RC) model utilizing Bonhoeffer-van der Pol (BVP) oscillators, leveraging their chaotic dynamics to generate complex, high-dimensional internal states. The paper investigates the impact of the attractor states of these oscillators on the prediction performance of a speech recognition task. Results indicated that the asymmetric attractors led to lower Word Error Rates (WER) compared to periodic ones, suggesting that the diversity of circuit responses is beneficial for RC performance.
Optimizing Image Classification with Inverse Depthwise Separable Convolution for Edge Devices

Deep Neural Networks (DNNs) have catalyzed a revolution in the field of object classification, achieving levels of accuracy that occasionally surpass human capabilities. Despite these significant advancements, the deployment of DNNs on edge devices presents new challenges due to inherent constraints in size, computational resources, and energy efficiency. Addressing these challenges necessitates innovative solutions that strike a balance between computational efficiency and classification accuracy. In this research paper, we introduce a novel Image Classification (IC) model that leverages Inverse Depthwise Separable Convolution, a technique specifically designed to optimize both accuracy and computational cost. With a lean structure of only 0.20M parameters, our proposed model achieves an impressive accuracy of 90.1% on the CIFAR-10 dataset. Moreover, the model’s compact size of 2.9 MB makes it an ideal candidate for deployment on edge/hardware devices. This work represents a significant contribution to the ongoing efforts to develop lightweight and efficient models without compromising performance, thereby facilitating broader applications in real-world edge computing scenarios.
Website User Interface Design Using The Design Thinking Method

The user interface is one of the aspects in the initial design of a website that acts as a link between the website and the user. The website created must have a solution to the problems experienced by users, so that later it will create a pleasant and easy experience in providing or obtaining information to users. This study aims to produce a user interface design for the bluesclues band website, which will later refer to the results of user interviews. The method used in this study is the design thinking method with five stages, namely emphatize, define, ideate, prototype, and the last is testing. Aspects of testing used in testing the design of this application namely effectiveness, efficiency, and satisfaction, by using the usability testing method with the system usability scale. based on the results of testing on related parties for the effectiveness aspect a value of 96% was obtained, for the efficiency aspect a time-based efficiency (TBE) value of 0.07 sec/goals was obtained. For the satisfaction aspect, a value of 83 is obtained, which is included in the grade B and acceptable category. From the test results it can be concluded that web design using the design thinking method can improve the user experience when using the website
SOSIALISASI PROFESI AKUNTAN DAN KELAS INTERNASIONAL AKUNTANSI PADA SEKOLAH MENENGAH ATAS DI LOMBOK TIMUR

Accounting is a science that studies the preparation of financial reports and various types of financial analysis, while an accountant is a profession that carries out accounting. The accounting profession is very diverse, ranging from public accountants, corporate accountants, educator accountants, to government accountants. Each type of accounting profession has different qualifications, duties and responsibilities. For high school students, knowledge about the accounting profession is still very minimal, so socialization is needed regarding this matter. This community service activity is in the form of socialization which aims to better understand the various accounting professions so that they can strengthen them to continue studying in the accounting department.In addition to this socialization, material about international accounting classes was added, especially at the University of Mataram. The methods for implementing these service activities include preparation, preparation of materials and media, socialization, and post-socialization by evaluating activities. A positive response was given by socialization participants who were students majoring in Social Sciences who were in class XII.
EVOLUTION OF ARCHITECTURAL AND ARTISTIC EXPRESSION OF LIBRARIES

The article traces the path of the emergence and development of libraries in different historical periods. From ancient times, when it was customary to create libraries at the palaces of kings, to libraries that were located at monasteries; from the period of cultural and educational development, when libraries were part of universities, to libraries as independent institutions. Examples of global experience in designing modern library buildings are given. On the basis of the researched material, a number of factors that influenced the formation of architecture and the transformation of the internal space were determined, with the primary function of preservation to a multifunctional urban center as convenient as possible for the realization of cultural, social needs and ideas. A building with open spaces and areas for communication. Spirituality is the main goal of architecture. Architects and designers, when designing modern library buildings and spaces, often deviate from the strict standards of the volume-planning structure, including recreation areas, exhibition areas, cafes, conference halls, areas with access to electronic media, halls with access to open funds, etc., which are not typical for libraries. A modern library project begins with a concept. The architectural concept of a modern library is a combination of knowledge, architecture, landscape and the wider public environment. The article shows how the evolution of the forms and functions of library buildings under the influence of technical, cultural, social, and economic development of society directly affects the aesthetic and functional renewal of their architectural and artistic diversity and volumetric and spatial environment.
Nutrition Education Using E-Booklet Against Hemoglobin Levels of Young Women

Anemia in adolescent girls is characterized by Hb levels &lt; 12 g / dl. Anemia is influenced by various factors including nutritional intake, and knowledge. Anemia results in learning concentration, fatigue, to decreased learning achievement. One of them overcomes this problem by giving Fe supplements and nutrition education. The purpose of this study was to determine the relationship between nutrition education using e-booklets on hemoglobin levels in adolescent girls. The design of this study was a Quasi-Experiment with a comparison group. The study was divided into the treatment group and the comparison group. Providing nutrition education using e-booklets and Fe supplements for 3 weeks in the treatment group. The number of respondents was 36 in the treatment group and the comparison in the comparison group. The results of the t-dependent test showed an average difference in the two groups with a p-value of  0.05. The average hemoglobin level of the treatment group was 0.411 g / dl and the comparison group was 0.2 g / dl. The results of the t-independent test showed no difference in the average hemoglobin levels of the treatment group with a comparison group with a p-value of  0.05. The average difference in hemoglobin levels in the treatment group with the comparison group was 0.211 g / dl. Fe supplements and nutrition education with e-booklets can increase Hb levels.
Methods for Extracting Opinion Trends to Promote the Experience in Determining the Authenticity of SNS Articles

There are various articles on social media that are factually incorrect mixed in with factual and informative articles. Therefore, it is important to identify fake articles when browsing the numerous posts on social media. Although unskilled people need to gain a lot of experiences in examining the authenticity of articles in order to obtain the ability to distinguish it, it is often difficult for novices to stack up enough meaningful experience to do so. We therefore aim to develop methods that promote the experience of examining the authenticity of articles by presenting users with articles whose authenticity should be questioned along with other people's opinions on those articles. In this paper, we mainly describe methods for collecting candidates of social media articles that may include incorrect descriptions and others' opinions, along with methods for classifying the collected articles in accordance with opinion trends. Finally, we describe an experiment utilizing the proposed methods for classifying opinion trends and discuss their effectiveness of our methods based on its results.
Embedded Systems and their Vulnerabilities to Hardware Attacks

The article describes the types of hardware attacks targeting embedded systems,countermeasures, and methods of modelling security threats. In currently used electronic devices, thesoftware usually ensures very high level of security. On the other hand, hardware implementations, oftenleave vulnerabilities that attackers can use to extract information or disrupt the operation of the device.Being a user of embedded systems, critical for safety, you should be aware of what dangers they maybe exposed to from the hardware side and to know the analysis of the side channel and fault injection.Keywords: hardware attacks, side channel analysis, vulnerabilities of embedded systems, protectionof devices against hardware attacks.
Image Retrieval Based on ConvNets and Hashing Algorithm

Image retrieval is a prominent subject of study in the fields of image processing and computer vision. With its application in various domains, such as logo search, product search or general image search in Google, Bing, etc., image retrieval has received significant attention for many years. In this work, we study and investigate a framework that leverages visual transferring fea-tures and hashing algorithms for the purpose of finding similar images in a dataset. The key idea of our solution is to find the answer to the following question: “How can we convert an image into binary code and search it more efficiently in a large-scale dataset?”. To achieve this pur-pose, we use pretrained CNN models from ImageNet for image representation and then convert them into binary code by using hashing algorithms. These images in the dataset are represented by binary codes, and the Hamming distance is used to find the images in the dataset that are in-dexed. To demonstrate the robustness of the system, we systematically tested the performance of the system based on speed with raw indexing and hashing indexing on 4 datasets: CIFAR-10, Caltech-101, Oxford-102-Flowers, and MS-COCO 2017. The experimental results show that lo-cal sensitive hashing (LSH) algorithms with 2,048 bits in binary code demonstrate the same or greater precision than raw indexing. Furthermore, the findings show that the MobileNet architec-ture consistently outperforms other architectures across these datasets, effectively balancing speed and precision.