>把苦中作乐作为一种生活方式，这就是让力不从心者摆脱困境、积极向上的途径有人曾问过我这样的问题：“看你工作时间超长或是遇到难题时也很疲惫，但总能很快到恢复精力充沛的状态，但很多人面对困难的工作或是长时间工作后总感到很累，无法恢复元气，工作也没了激情。如何让自己激情永驻、活力长存呢?”
In the era of Industry 4.0, advanced assistance technologies have permeated manufacturing processes, yet the absence of systematic implementation methods remains a challenge. This research presents a multidimensional framework developed through inductive reasoning, encompassing technological capabilities and instructional considerations. Its primary objective is to guide the development of context-specific assistance solutions, shifting the focus from automated solutions to thoughtful technology selection and implementation. The framework's application has the potential to elevate stakeholder design processes through interactive visualizations and experiential anchoring. Notably, the adoption of cognitive assistance systems within manufacturing is on the rise, driven by the maturation of virtual and augmented reality solutions. However, a notable gap exists in systematic approaches for selecting and designing these technologies. This paper addresses this gap by proposing a comprehensive framework grounded in an inductive approach. This research seeks to enhance awareness among decision-makers in companies regarding essential selection and decision criteria. Furthermore, it offers guidance for a systematic and participatory implementation process. The research results underscore the importance of adopting such a framework in the industry 4.0 landscape, shedding light on the need for strategic technology integration. This study suggests that the proposed framework can serve as a valuable tool to facilitate informed decision-making and drive the successful implementation of assistance technologies in manufacturing processes.
The use of technology in learning is used as a means of learning. Learning media is anything that is used in the process of learning activities and can stimulate students' thoughts, feelings, interests and attention when learning, so that the process of interaction, communication and education between teachers and students can take place in accordance with the learning objectives. This research aims to produce a product in the form of a web-based interactive multimedia learning application, which is of good quality and highly suitable for use as a learning medium for students in English subjects. The research location was conducted at UPT SMP Negeri. 35 Medan. This multimedia learning product has gone through a strict review and revision process, based on suggestions from teachers and supervisors. This product was tested in a class with 31 students. The results show that learning management at UPT SMP Negeri 35 Medan using this interactive application has achieved learning management well, this can be seen from the acquisition section to the retrieval system of existing information/learning. Thus, this product can be used in the learning process to provide new, more meaningful experiences to students. In addition to this multimedia product, the teaching materials can be studied anywhere and at any time, which can increase students' learning motivation.
The efficacy of machine learning models in speaker recognition tasks is critical for advancements in security systems, biometric authentication, and personalized user interfaces. This study provides a comparative analysis of three prominent machine learning models: Naive Bayes, Logistic Regression, and Gradient Boosting, using the LibriSpeech test-clean dataset—a corpus of read English speech from audiobooks designed for training and evaluating speech recognition systems. Mel-Frequency Cepstral Coefficients (MFCCs) were extracted as features from the audio samples to represent the power spectrum of the speakers’ voices. The models were evaluated based on precision, recall, F1-score, and accuracy to determine their performance in correctly identifying speakers. Results indicate that Logistic Regression outperformed the other models, achieving nearly perfect scores across all metrics, suggesting its superior capability for linear classification in high-dimensional spaces. Naive Bayes also demonstrated high efficiency and robustness, despite the inherent assumption of feature independence, while Gradient Boosting showed slightly lower performance, potentially due to model complexity and overfitting. The study underscores the potential of simpler machine learning models to achieve high accuracy in speaker recognition tasks, particularly where computational resources are limited. However, limitations such as the controlled nature of the dataset and the focus on a single feature type were noted, with recommendations for future research to include more diverse environmental conditions and feature sets.
This study delves into the application of machine learning (ML) and deep learning (DL) techniques for the analysis of seismic data, aiming to identify and categorize patterns and anomalies within seismic events. Using a robust dataset, we applied three distinct clustering approaches: K-Means, DBSCAN, and an Autoencoder-based method, each offering unique perspectives on the data. K-Means clustering provided a fundamental partitioning of the data into five predefined clusters, facilitating the identification of broad seismic patterns. DBSCAN, a density-based clustering algorithm, offered insights into the spatial distribution and density of seismic events, adeptly pinpointing anomalies and outliers that signify unusual seismic activity. The Autoencoder, leveraging deep learning, excelled in capturing complex and non-linear relationships within the data, revealing subtle patterns not immediately apparent through traditional methods. The effectiveness of these clustering techniques was quantitatively evaluated using the Silhouette Score and the Davies-Bouldin Score, alongside visual assessments through PCA and t-SNE for dimensionality reduction. The results indicated that while K-Means provided clear partitioning, DBSCAN excelled in outlier detection, and the Autoencoder offered a balanced approach with its nuanced analysis capabilities. Our comprehensive analysis underscores the significance of employing a multi-methodological approach in seismic data analysis, as each method contributes uniquely to the understanding of seismic events. The insights gained from this study are valuable for enhancing predictive models and improving disaster risk management strategies in seismology. Future research directions include the integration of additional seismic features, validation against larger datasets, and the development of hybrid models to further refine the predictive accuracy of seismic event analysis.
This research focuses on the design and implementation of a rainfall monitoring system for chili pepper farms using Internet of Things (IoT) technology. The rainfall monitoring system consists of a transmitter system, a receiver system, the Thingspeak platform as a database, and a weather station application that can be accessed via a mobile device. The weather station application is built using the MIT App Inventor platform. In the testing phase, the system successfully collected data from two sensors used, namely the rainfall intensity sensor and the raindrop sensor. The test results showed that the data obtained from the rainfall intensity sensor was 0.25 inches and the raindrop sensor was 1. This result shows that there was no rain during the test. This rain intensity and raindrop data can provide farmers with an overview of the weather conditions in the chili pepper farm. So, with this rainfall monitoring system, farmers can monitor the condition of their agricultural land in real-time. The collected data can help farmers to care for chili pepper plants more effectively and adapt to environmental changes. In addition, this system is expected to increase the productivity of chili pepper farming because it uses a more precise and responsive approach to changes in environmental conditions on the chili pepper farm.
This research aims to develop an artificial intelligence-based chatbot as a support tool for the New Student Admission (PMB) process at Cokroaminoto University Palopo. The system development method applied is the waterfall method, which consists of analysis, design, implementation, testing, and maintenance stages. The main focus of this research is to design and implement a chatbot that is able to provide information and support to prospective new students throughout the admission process. In the analysis stage, user needs and scenarios were identified to guide the development of the chatbot. System design includes the selection of artificial intelligence algorithms and a friendly user interface. Implementation involves developing a chatbot prototype that utilizes artificial intelligence technology. The expected results can improve the efficiency and quality of new student admission services at Universitas Cokroaminoto Palopo.
This research aims to design and build a tourism system in Sumbawa Regency. In this research is using a qualitative approach that used model of rapid application development (RAD) for system development life circle (SDLC) method. Overall the first stage is system planning, next stage is analyzing tourism data and information that would be presented on web and android technology based. In addition, for users interface display is the attractive database design. The final stage is coding the system and produce a prototype for the implementation which is presenting on the web pages and google play store for android smartphones. The system presented could be used for evaluation, monitoring and facilitating of tourism transaction and promotion processes in Sumbawa Regency.
The learning method used in learning the subjects of the Qur'an and Hadith in Schools is a common teaching method, which uses books as a source of knowledge and teachers as teachers. In this problem, the author uses a learning method using Augmented Reality (AR) as the basic law of reading aloud so that students don't get bored. Augmented Reality (AR) is a combination of real and virtual objects displayed simultaneously on a screen. Augmented Reality is created with Unity 3D, Vuforia and Android software. The application of new learning methods should increase students' interest in serious and straightforward learning. This research aims to build a recitation science learning application for children 5-10 years old using an Android-based device "so that with this application it is hoped that it will have an attractive design, as well as complete features and have materials and examples of legal reading and pronunciation." easy for children to understand and can make children understand the science of recitation from a young age. The results of this research are applications for learning the science of Tajweed for children 5-10 years old which can display the hijaiyah letters accompanied by their pronunciation and how to pronounce them, the laws of the science of Tajweed which consist of the law of nun mati/tanwin, qalqalah and the law of mad, games as material for evaluating children. The Tajwid science learning application succeeded in increasing children's understanding of Tajweed science by 57.9%. Application feasibility testing uses white box and black box methods with several test requirements. Based on the test results, functionally the application is appropriate, feasible, and can be used as a learning medium for Tajwid science and is in the "Very Good" category.
Digitalization of education is a logical consequence of developments over time, a response to educational services that are experiencing changes in both the learning system and learning culture. Developments in the field of education are closely related to the term innovation. Innovation in the realm of education is an obligation for all educational actors. Moreover, the development of science and technology is growing rapidly. The parenting pattern that has been implemented in most vocational schools within the Ministry of Transportation is still more of a manual system that cannot be connected directly to digitalization. The aim of the process of developing digitalization of parenting patterns is expected to increase efficiency and optimization in many ways, including efficiency and optimization of parenting activities, connectivity between institutions or units involved in parenting, access to data related to parenting patterns, personal data of cadets and caregivers, as well as ease of use. information in accessing rules relating to parenting patterns. The research method used is a mixed type of research. Mixed research is the use of two types of research, namely qualitative and quantitative in one study. The research location is planned to be carried out at a vocational school under the Ministry of Transportation (Poltekpel Sorong). This research then produced an online-based digitalization development desktop software and was then named the see cadet application website. This development and research uses the ADDIE Development Model, namely the analysis stage, design stage, development stage, implementation stage and evaluation stage.
The availability of drugs is one of the needs that supports the presence of health in the community. Patient certainty regarding the availability of drugs becomes increasingly important for patients who use psychotropic drugs. This type is a dangerous drug and needs to be controlled. Control is carried out to avoid drug abuse outside of medical purposes. Two conflicting sides between the importance of ensuring the availability and controlling their use can be resolved, one of which is by measuring supply and demand. The availability of psychotropic drugs should be adjusted to demand. The problem is that we cannot know demand that has not yet occurred, drugs have an expiration date, and procuring drugs takes time. One way is to predict the demand when supplying drugs so that the order quantity is appropriate. The prediction method used is the Monte Carlo Simulation Method. One example of implementation is the Economic Order Quantity (EOQ) Method. As a result, the Monte Carlo method successfully made predictions based on existing data. In addition, it was found that the Monte Carlo Method tended to the distribution of the data used. The closer the distance between the data, the higher the prediction accuracy obtained. Uncertainty in actual demand is also a big challenge for producing accurate predictions based on patterns. Prediction results will be more accurate with more data patterns and variations. Implementation of prediction results with EOQ makes the number of drugs that should be ordered based on demand that is likely to occur.
Diabetic Retinopathy (DR) is a disease whose main cause is complications of diabetes mellitus. High levels of sugar in the blood (glucose) are caused by the pancreas' inability to produce insulin. Prevention of diabetic retinopathy and blindness by carrying out examinations at an early stage and doing them regularly. Currently, doctors still carry out examinations manually so they are prone to errors in examinations. This research aims to build an application to diagnose Diabetic Retinopathy in order to facilitate the work of the medical team and doctors at the eye clinic. In the application creation process, MATLAB is used, while feature extraction uses GLCM and for classification, SVM is used. The results of the research are that doctors and medical teams are helped in carrying out manual patient diagnoses and reduce the occurrence of human error.
Communication and Internet technology are developing very rapidly, one of which is in the field of telecommunications technology and is directly proportional to the public's need for its use and also with the increasing need for fast and efficient services both in agencies, commercial, academic worlds and in the homes of residents who need internet access. Thus making telecommunications technology an inseparable technology to support human work. The Penyaring Village Office is located in North Moyo District, Sumbawa Regency, which is the center for all activities in the Village, both in the fields of government, empowerment, development, and coaching, all of which are centered at the Penyaring Village office. This research aims to analyze and design the internet network in the Penyaring Village office and prevent slow wifi so that the network stability in the Penyaring Village office becomes more stable/smooth when used, and the work in the Penyaring Village office becomes better and optimal. This research uses Router, Mikrotik, Access Point network devices, Winbox software, and other supporting devices. The network development method uses the NDLC (Network Development Life Cycle) method, which begins with the Analysis, Design, Simulation Prototype, Implemetation, Monitoring and Management. The research method uses qualitative consisting of observation, interviews, and documentation. The results of this research are building network infrastructure, network security, and bandwidth distribution in each sector which can stabilize the process of using WiFi at the Penyaring Village Office.
Catfish is a type of freshwater fish that is in great demand among people because it has high nutritional value. The high demand for catfish on the market is a promising business opportunity. The relatively fast maintenance period makes this cultivation much in demand. Management of a catfish farming business requires good strategy and planning so that the business process can provide optimal profits. Appropriate management practices, good planning can predict crop yields with minimal error rates. Based on past data from catfish farming businesses, catfish pond production results are influenced by several factors including pond area, number of seeds, and amount of feed. The catfish cultivation management system produces predictions of catfish harvest but ignores weather conditions, natural disasters and infectious diseases. The method used in crop yield prediction management is the Tsukamoto Fuzzy inference system. The Tsukamoto method applies monotonous reasoning and rules are built using expert knowledge, enabling the system to be able to conclude and manage predictions of catfish harvest based on data regarding pond size, number of seeds and amount of feed. System testing using 10 data shows prediction results obtained through manual calculations and system calculations, resulting in identical results. Further testing uses the white box method to ensure that the data implemented in the Tsukamoto fuzzy management system accurately produces logical decisions. Hence, it can be concluded that the management system using the Tsukamoto method is able to show effective performance in predicting harvest results based on data on pond area, number of seeds and amount of feed consumption. This management system is expected to be able to provide recommendations for catfish cultivation business planning for the community.
Recently, photovoltaic (PV) technology has significantly contributed to the utilization of renewable energy sources. It plays a crucial role in addressing the challenges posed by climate change, enhancing energy affordability, ensuring power supply stability, and facilitating energy accessibility. PV technology represents a significant opportunity for addressing the issue of energy access among distant areas that now lack reliable access to electricity. Using a traditional grid is limited due to cost and feasibility constraints. These difficulties are to be addressed in the appropriate timeframe to improve the dependability of the supply. The expansion of the grid into these regions diminishes the overall resilience of the grid system. This leads to a situation where PV systems are integrated into an AC grid with low power quality (PQ) or limited capacity. Nevertheless, the integration of solar power into an AC grid with low capacity. The presence of PQ problems imposes limitations on the levels of penetration. Other factors impose limitations and penetration levels encompass several factors such as non-linear loads, dynamic loads, fluctuating irradiations, and partial shade, among others. This article aims to address the PQ difficulties that arise from a weak electrical infrastructure. The purpose of this compilation is to provide engineers with a readily accessible resource, offering them a distinct advantage in their professional endeavors and scholars engaged in this field of investigation. In this context, the photovoltaic (PV) array is methodically organized into 86 parallel strings. The aforementioned strings are meticulously constructed, consisting of a sequence of seven SunPower SPR-415E solar modules that are intentionally interconnected.
企业对于未来保持乐观预期,随着各项扩内需、稳外贸政策逐步生效,经济内生动能将稳步增强 10月份,官方制造业PMI指数回落至荣枯线以下,录得49.5％,比上月下降0.7个百分点;官方非制造业PMI指数较上月下滑1.1个百分点至50.6％.PMI多项指标回落,一方面是季节性波动,另一方面是当前需求偏弱,经济修复成果还需稳固.
