Stages Of Data Processing Research Articles

Graphene nanomechanical vibrations measured with a phase-coherent software-defined radio

Software-defined radios (SDRs) are radio frequency transceivers designed to facilitate digital signal processing through the use of vast libraries of open-source software. Here, we assemble a simple data acquisition system whose architecture, based on SDR, allows us to develop a comprehensive suite of tools to study the vibrations of a few-layer graphene nanomechanical resonator. Namely, we measure the cross-spectrum of vibrations in the frequency domain, we measure their energy decay rate in the time domain, we perform vector measurements of their in-phase and quadrature components, and we control their phase using a time-dependent strain field –all with a single measurement platform. Our approach allows us to tailor our experiments at will and gives us control over every stage of data processing. Overall, our versatile system enables measuring a wide range of nanomechanical properties of graphene by customizing the signal acquisition and replacing some analog electrical circuits, such as filters, mixers, and demodulators, by blocks of code.

A dataset of 1 km grid drainage density in China (2019)

Drainage density is an outcome of the combined influence of watershed landform, climate, soil, and vegetation. As a comprehensive characterization index, the measurement and monitoring of drainage density is of great significance to environmental protection and water resources allocation in regional watersheds. This paper uses river water surface vector data from the third National Land Survey, extracting the river center line. Then, the kilometer grid network production software is employed to generate the dataset of 1 km grid drainage density in China. Rigorous quality control and quality inspection measures throughout all stages of data processing have been implemented, including river surface vector extraction, river skeleton line extraction, and kilometer grid density calculation, to ensure the correctness, integrity and consistency of the data. This dataset can be used for national and regional hydrogeological analysis, soil erosion estimation, planning and layout of basic monitoring station network, etc.

The Influence of Socio-Economic Facilities and Population Density on Landuse Changes in Gunungpati District, Semarang City

Land use still serves as a guide for urban development decisions, even though they are typically independent. Establishing important corporate hubs has made economic considerations a key driver in determining how the city’s land-use structure will be governed. The study investigates the influence of socio-economic facilities and population density on land use changes in Gunungpati district, Semarang City. The data processing technique used in this study was to make a map of the administrative area of Gunungpati District. The following data processing stage digitizes Gunungpati District images in 2011 and 2019 to determine land use. Then carry out the overlay process on the two land use maps of the Gunungpati District to find out changes in land use in 2011 and 2019. Qualitative data analysis was used in this study. The findings of land change map overlays between 2011 and 2019 were used for qualitative data map analysis. The findings demonstrate that settlements, which account for 2,255 hectares of land in Gunung Pati District, dominate land use, with Pakintelan Village having the highest residential land use. At the same time, the most minor land use is in the service sector, namely as much as 590 Ha. Land use in Gunungpati District in 2019 was dominated by residential land, namely 2,388 Ha, where the highest residential land use was in Sekaran Village, namely 250.76 Ha. The slightest use of land is on service land, which is 442.51 Ha, with the highest use of service land in Sekaran Village, which is 58.24 Ha. The dominant factors influencing changes in land use are the increase in social facilities and population density, which encourage land conversion and make it a more productive resource.

Interpretable corn future price forecasting with multivariate time series

AbstractEfforts in corn future price forecasting and early warning play a vital role in guiding the high‐quality development of the agricultural economy. However, recent years have witnessed significant fluctuations in global corn future prices due to the impact of COVID‐19 and the escalating risks associated with geopolitical conflicts. Therefore, there is an urgent need for accurate and efficient methods to forecast corn future prices. To address this challenge, a novel and comprehensive framework for explainable corn future price forecasting is designed. This framework takes into account multiple factors contributing to corn price volatility, including supply and demand dynamics, policy adjustments, international market shocks, global geopolitical risks, and investor concerns within the corn market. During the data processing stage, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) is utilized to thoroughly explore the volatility characteristics of historical corn future prices. Additionally, a convolutional neural network (CNN) is employed to extract essential forecasting information from corn news data. To enhance interpretability, a novel JADE–TFT interpretable corn future price prediction model is proposed. This model combines adaptive differential evolution with optional external archiving (JADE) to intelligently and efficiently optimize the parameters of the temporal fusion transformers (TFTs). Furthermore, in the empirical study, the introduction of a global geopolitical risk coefficient, Baidu indices such as “corn” and “corn price,” and quantized corn news text features is shown to improve the accuracy of corn future price predictions. The proposed corn future price prediction framework contributes to the healthy development of the global grain futures market, thereby fostering the growth and well‐being of enterprises involved in the grain industry.

Sentiment Classification of Over-Tourism Issues in Responsible Tourism Content using Naïve Bayes Classifier

The research problem addressed in this study is the analysis of public sentiment regarding over-tourism issues. Utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology and the Naive Bayes Classifier (NBC) algorithm, the study navigates through stages of business understanding, data processing, modeling, evaluation, and deployment. The central focus lies in understanding and classifying public sentiments surrounding the challenges associated with over-tourism. The findings reveal that the NBC algorithm, particularly when augmented with Synthetic Minority Over-sampling Technique (SMOTE), demonstrates superior performance metrics, showcasing an accuracy of 84.82%, precision of 91.69%, recall of 76.75%, f-measure of 83.47%, and AUC of 0.838. The comparison with NBC without SMOTE, which registers an accuracy of 78.16%, precision of 87.61%, recall of 74.56%, f-measure of 80.51%, and AUC of 0.745, underscores the significance of addressing class imbalance for improved predictive performance. Integrating CRISP-DM with the NBC algorithm and SMOTE proves instrumental in advancing sentiment analysis methodologies, providing nuanced insights into public perceptions and attitudes concerning the critical issue of over-tourism.

Microarray Images Contrast Enhancement and Gridding Using Genetic Algorithm.

Microarray is a sophisticated tool that concurrently analyzes the expression levels of thousands of genes, giving scientists an overview of DNA and RNA study. This procedure is divided into three stages: contact with biological samples, data extraction, and data analysis. Because expression levels are disclosed by the interplay of light with fluorescent markers, the data extraction stage relies on image processing methods. To extract quantitative information from the microarray image (MAI), four steps of preprocessing, gridding, segmentation, and intensity quantification are required. During the generation of MAIs, a large number of error-prone processes occur, leading to structural problems and reduced quality in the resulting data, affecting the identification of expressed genes. In this article, the first stage has been examined. In the preprocessing stage, the contrast of the images is first enhanced using the genetic algorithm, then the source noises that appear as small artifacts are removed using morphology, and finally, to confirm the effect of the contrast enhancement (CE) on the main stages of microarray data processing, gridding is checked on complementary deoxyribonucleic acid MAIs. The comparison of the obtained results with an adaptive histogram equalization (AHE) and multi-decomposition histogram equalization (M-DHE) methods shows the superiority and efficiency of the proposed method. For example, the image contrast of the Genomic Medicine Research Center Laboratory dataset is 3.24, which is 42.91 with the proposed method and 13.48 and 32.40 with the AHE and M-DHE methods, respectively. The performance of the proposed methods for CE is evaluated on 3 databases and a general conclusion is obtained as to which CE method is more suitable for each dataset.

IMPROVING THE PERFORMANCE OF SUSTAINABLE HUMAN RESOURCES IN COFFEE BEAN SUPPLY IN THE SATAK COFFEE AGROINDUSTRY, KEDIRI DISTRICT

The supply of coffee beans in Indonesia involves several stakeholders, namely farmers, collectors and KUB (Joint Business Group). Sustainable supply activities are human, economic, social, environmental and technological resource management activities. The aim of this research is to analyze the sustainability performance of human resources in the supply of coffee beans in Indonesia. The data processing stage is identifying the supply of coffee beans in Indonesia. Analysis of identifying the supply of coffee beans in Indonesia, analysis of added value, measurement and assessment of the sustainable supply performance index for coffee beans. The added value of coffee bean supply was analyzed using the Hayami modification. SCOR-AHP (Supply Chain Operations Reference-Analytical Hierarchy Process) is used to measure the sustainability performance of human resources. The supply status of coffee beans is calculated using the Multi-Dimensional Scaling (MDS) technique with R software. The value added ratio for coffee farmers is low (46.58%) compared to collectors with (71.31%) and KUB (86.35% ). Farmers' supply performance is 71.99% lower than collectors with a value of 88.15% and KUB 86.77%. The economic dimension of sustainability is almost sustainable (78.39), the social dimension is sustainable (89.25), the environmental dimension is almost sustainable (79.63) and the technological dimension is almost sustainable (67.68). The aggregate value of sustainable supply shows 78.72% which means almost sustainable. This research recommends a strategy for building partnerships between coffee farmers and coffee cafes to improve performance and sustainability of the supply of coffee beans.

Potential application of GBIF platform for flora inventory of Karaganda region

The current biodiversity inventory has important scientific and practical implications for the country. In Kazakhstan, data on the flora of spore and vascular plants are outdated; there is a significant gap in assessing the current species composition of certain regions of Kazakhstan, including Central Kazakhstan (Karaganda and Ulytau regions). The problems of formation of a modern flora abstract are determined by the need to use the entire volume of accumulated information, both for individual findings of naturalists and multi-year collections in domestic and international herbarium collections. When carrying out research to analyze the current state of the flora of Karaganda region, the GBIF platform resources containing information on the biological diversity of flora and fauna were used. Data analysis showed that the platform has more than 130 thousand records of vascular plant finds for the territory of Kazakhstan, including 2241 records for Karaganda region with geo-referencing. The main funds containing the largest number of collections made on the territory of our region were determined. The stages of data processing and geo-linking of herbarium collections are defined. In general, a high potential for supplementing field collections with GBIF data to clarify the distribution of individual taxa and make range maps was determined.

РАЗРАБОТКА МОДЕЛЕЙ МАШИННОГО ОБУЧЕНИЯ ДЛЯ ПРОГНОЗИРОВАНИЯ ЭКОНОМИЧЕСКОЙ ЭФФЕКТИВНОСТИ БИЗНЕС-ПРОЦЕССОВ

The article discusses the development of machine learning models for predicting the economic efficiency of business processes in a rapidly changing economic environment and increasing competition in the market. The author pays special attention to machine learning models, such as linear regression, random forest, gradient boosting and neural networks, and the rationale for their selection and use in the context of economic efficiency forecasting. The stages of data processing, training models and assessing their quality using various metrics are described. The selection of key business processes for testing machine learning models, such as the production process, sales process, logistics process and financial process, is considered. The author analyzes the results and presents conclusions and recommendations based on the analysis of specific business processes.

Intelligent crop yield prediction system using neural networks and databases

Machine learning plays an important role in decision support and yield forecasting. This is an effective tool for determining strategies during the growing season of plants. The article proposes a method for predicting yield using a complex system consisting of a convolutional neural network (CNN), a feedforward neural network (FNN), and a SQLiteStudio database. The system includes several stages of data processing, starting with the collection and analysis of images and digital data obtained from various sources, and ending with yield forecasting based on this data. A convolutional neural network (CNN) is used to analyze images and video streams to recognize and count fruits on trees, providing accurate data about the status of the crop. Feedforward neural network (FNN) is used to analyze digital data, such as weather station data and long-term crop yield data, to subsequently predict crop yields. The received data is stored in a relational database, which ensures their structured storage and access for subsequent processing. Used SQL language to perform various database operations. To automate the process of counting fruits on trees, the YOLOv8 convolutional neural network model is used, which allows recognizing objects in real time. A Python script has been developed to process images using YOLOv8 and save the results to a database. An integrated system combines various methods and technologies to predict yields and automate data collection and analysis processes. The developed model showed a mean square error (MSE) of 7.33 and a mean absolute percentage error (MAPE) of 6.27%.

Теоретико-методичні засади вебкартографування постмілітарних об'єктів

Purpose of the research objective is to develop and substantiate the theoretical and methodological foundations of web mapping of post-military facilities, taking into account the most effective approaches and techniques for collecting, analyzing, processing, and visualizing spatial data. The methodology includes using modern technologies to create accurate and informative interactive maps that provide not only the physical location of the objects but also detailed information, including textual, illustrative materials, graphical data, and 3D models. Results. Based on a comprehensive approach to researching, documenting, and presenting post-military facilities, the article elaborates the theoretical and methodological foundations of their web mapping. The relevance of using innovative digital technologies for creating interactive maps is discussed. The research methodology based on the collection, analysis and visualization of spatial data is considered in detail. The main principles and approaches to web mapping are highlighted, including historicity, systemic integrity, reliability, modernity, coherence, informativeness, presentability, accessibility, technological sophistication, variability of geographic bases, and partnership for effective project implementation. A technological scheme of web mapping is proposed, covering the stages of data collection, processing, and actual web mapping, ensuring a multidisciplinary and integrative approach to solving the set task. Designing and implementing web maps considering historical, cultural, technical data, and the current state of post-military facilities requires the interaction of specialists from various fields of knowledge. Scientific novelty and practical significance. The theoretical and methodological principles of interdisciplinary web mapping of post-military objects were developed for the first time. The principles and approaches to it have been defined, a technological scheme for web mapping of post-military objects has been developed. The proposed methodology and technology determine the practical significance of the research. Based on them, interactive maps of post-military facilities of any territory will be used in various fields of activity: education, science, preservation of historical and cultural heritage, tourism, promotion of the region.

ANALISIS KEMAMPUAN LAHAN PADA SATUAN WILAYAH PENGEMBANGAN DI KOTA AMBON

Optimizing land use plans is carried out for land capabilities that are useful for conserving land resources so that they can reduce the problem of land degradation. This study aimed to assess the level of land capacity and determine the function of both protected and cultivated areas in Development Area Units (SWP). The method used in the research is quantitative descriptive, consisting of data collection and processing stages. Data collection was carried out through literature studies from several related agencies. Meanwhile, spatial data analysis was carried out using Geographic Information System (GIS) software. The results of the research showed that the analysis of land capacity, especially for determining the function of areas for settlement, reached 3,687.35 ha and the buffer area was around 11,755.27 ha. This indicates that only a small portion of suitable areas can be developed for urban development. This is due to the physical limiting factors of the land where the characteristics of the Ambon City area are dominated by hilly areas.

Penggunaan Kobotoolbox sebagai Prosesor Data Surveilans Terpadu Penyakit (STP) Puskesmas Guntung Manggis

The Integrated Disease Surveillance (IDS) Program at the Guntung Manggis Public Health Center has a problem: the data processing stage only changes tabulation. Data processing is not continued in the form of diagrams, graphs, and mapping, so it will not describe disease trends based on epidemiological characteristics. This will complicate the next stage, namely analyzing the data to produce follow-up recommendations that are not on target. This problem is solved by using the kobotoolbox application for processing IDS data. The use of the kobotoolbox application in processing IDS data was monitored from October to November 2022. The evaluation results used the TAM evaluation model with a score of 95%, and all variables were declared good to very good with a score of (?68,01%), indicating that the kobotoolbox application was very effective in processing IDS data both through questionnaires and interviews. Then the supporting media used, both modules and tutorial videos, are feasible to use with a score of (>61%) in understanding data processing using the kobotoolbox application. It’s hoped that the Surveillance Unit of the Guntung Manggis Public Health Center will continue to use the kobotoolbox application in processing IDS data so that the resulting recommendations are more targeted.

Indonesian Muslim Society's Reception of Sensation Language and Invitation to Polygamy on Social Media

Poligami Asyik Channel is one of the media used by Ustad Awan (UA) to socialize polygamy invitations. The language on this polygamous YouTube uses sensational language. Even though this invitation to polygamy is packaged in sensational language, it is still defeated by personal and interpersonal experiences that are discussed on social media and represented in stories from films and soap operas. This paper aims to map the forms of reception, the factors behind the reception and their impact on public discourse on polygamy law.This research is qualitative and based on primary and secondary data. Primary data was obtained from distributing questionnaires to participants in the Daurah Poligami online training (December 2022) and studies on the Poligami Asyik Channel (from December 1 to December 23, 2022). Data are sorted and classified based on Stuart Hall's reception theory. The stages of data processing started with the reduction of netizens' expressions /receptions in the comments column. The observation of data display is carried out in the form of a summary and synopsis based on reception expression patterns. The analysis follows an interpretation technique that starts with a restatement of the data followed by a description, ends with an interpretation of the dataThe results of the study show that invitations to polygamy using sensational language increase public rejection of polygamy. The public reception is through personal and interpersonal expressions that are discussed on social media and then represented in public entertainment media (soap operas and films). The difference in the reception then becomes a hybrid reception that further dramatizes polygamy law, so that it is not in line with Islamic law.

МЕТОД ТА ЗАСІБ МОНІТОРИНГУ БЕЗПЕКИ В КОМП'ЮТЕРНІЙ МЕРЕЖІ ЗАСОБАМИ SIEM

This work focuses on researching, analyzing, and enhancing methods and tools for security monitoring in computer networks. The study develops security monitoring tools and methods based on SIEM agents, improving the data normalization process from security logs. The research explores SIEM's role in the SIEM-EDR-NDR triad perspective to accelerate responses to network security threats. The investigation is grounded in the experiences of foreign companies and domestic banking networks. The interaction of SIEM-EDR-NDR components, forming a SOC triad, is examined. SIEM is utilized for centralized data analysis, including EDR and NDR, providing a comprehensive security overview. EDR detects and responds to threats on endpoints, complemented by NDR, extending SIEM analysis. This combination ensures effective response to cyberattacks, reducing "dwell time" until detection. The formulation of tasks for EDR components in the SIEM-EDR-NDR triad is discussed. Emphasis is placed on the importance of protecting endpoints at all stages of an attack, and effective strategies, such as traffic analysis, application control, and centralized cybersecurity management, are identified. Integration of EDR with existing security tools to create a comprehensive system is highlighted. Within the SIEM context, data processing stages, from log collection and normalization to event classification and correlation, are illuminated. The role of correlation in incident formation and investigation is underscored. An enhanced normalization scheme with an expanded agent deployment and key data processing stages within the SIEM system is proposed. The work addresses the improvement of event log processing in SIEM for effective network security monitoring and timely threat mitigation. The achieved goal accelerates threat response processes through SIEM agent integration, facilitating the organization and classification of information flows for prompt threat mitigation.

Dose-response technique combined with stable isotope tracing for drug metabolite profiling by using high-resolution mass spectrometry.

Background: Mass spectrometry metabolomics-based data-processing approaches have been developed for drug metabolite profiling. However, existing approaches cannot be used to comprehensively identify drug metabolites with high efficacy. Methods: Herein, we propose a two-stage data-processing approach for effective and comprehensive drug metabolite identification. The approach combines dose-response experiments with stable isotope tracing (SIT). Rosiglitazone (ROS), commonly used to treat type 2 diabetes, was employed as a model drug. Results: In the first stage of data processing, 1,071 features exhibited a dose-response relationship among 22,597 features investigated. In the second stage, these 1,071 features were screened for isotope pairs, and 200 features with isotope pairs were identified. In time-course experiments, a large proportion of the identified features (69.5%: 137 out of 200 features) were confirmed to be possible ROS metabolites. We compared the validated features identified using our approach with those identified using a previously reported approach [the mass defect filter (MDF) combined with SIT] and discovered that most of the validated features (37 out of 42) identified using the MDF-SIT combination were also successfully identified using our approach. Of the 143 validated features identified by both approaches, 74 had a proposed structure of an ROS-structure-related metabolite; the other 34 features that contained a specific fragment of ROS metabolites were considered possible ROS metabolites. Interestingly, numerous ROS-structure-related metabolites were identified in this study, most of which were novel. Conclusion: The results reveal that the proposed approach can effectively and comprehensively identify ROS metabolites.

BENTUK DAN FUNGSI DRAMA TARI GANDRUNG TERAKOTA DI KABUPATEN BANYUWANGI

This study aims to describe the formulation of the problems related to the Gandrung Terakota Dance drama, including: (1) how is the form of the Gandrung Terakota Dance drama; and (2) how is the function of the Gandrung Terakota Dance drama. Both of these problems use qualitative research methods that examine textual and contextual performing arts. There are two stages that must be carried out in qualitative research, namely the data collection stage which consists of observation, interviews and research. The second stage is the data processing stage which is carried out by analyzing the data according to the Gandrung Terakota Dance drama.The research results show that the Gandrung Terakota Dance drama is a form of performance which has 5 scenes packaged into the Gandrung Terakota Dance drama performance. The function of this drama is classified as a function of ritual, entertainment, and spectacle. Keywords: Gandrung, Form, Function.

Flood Control Rule in Bintang Bano Reservoir

Flood is a disaster that occur since ancient times until now, and even in the future. Flood can be caused by nature, humans, or both. Constructing new dams are a good method to reduce flood and losses caused by floods, one of them is Bintang Bano Dam. The purpose of this study is to analyze the capacity of the gated spillway and ungated spillway, so that the allowable return period of discharge can be estimated through the both spillways. This research activity divided into 4 (four) stages are: the identification and data processing stage, the rainfall-runoff modeling stage, the reservoir flood routing, and the simulation of the operation of opening gates on both spillways. The gated spillway can be operated at all return periods (2 years to PMF). Ungated spillway can only overflow discharge with ≥ 100 years return period. During the return period 2 years to 50 years, no runoff occurs through the ungated spillway. For the return period of 100 years to 1000 years there is runoff through the ungated spillway without any gate openings. It is recommended for floods with a return period of 2 years to 50 years, with upstream and downstream conditions of rainfall, the gate can be closed. But for floods with 100 years to 1000 years return periods, the discharge automatically overflows through the ungated spillway cannot be opened/damaged.

ANALISIS KONSEP HOSPITAL WITHOUT WALLS PADA PELAYANAN KELAINAN REFRAKSI DI UPTD RUMAH SAKIT MATA PROVINSI SULAWESI UTARA

A hospital without walls or known as a hospital without walls is very useful for patients who come to the hospital for treatment with referrals from the public health center as the entry point for referral diagnosis, this is to minimize the risk of infection transmission and other disease problems. The purpose of this study is to analyze the concept of a hospital without walls and the obstacles and challenges in providing refractive errors. The research was conducted at the UPTD Eye Hospital in North Sulawesi Province, from January to December 2022 using in-depth interviews with five research informants, namely the director, head of medical services, ophthalmologist, family doctor and patient. Instruments in the form of in-depth interview guidelines and a list of questions that have been provided. The stages of data processing are narrating, inferring, reducing, recording, sampling, unitizing. Data analysis is content analysis. The validity of the research results using triangulation of data sources and methods. The results of this study were obtained from the summary of the answers of the research informants that the concept of a hospital without walls all understand and know this concept to mitigate the accumulation of services in hospitals, but this concept has not been implemented because there are several factors such as standard operating procedures, human resources and infrastructure which is not yet possible for some FKTPs to be able to complete services at the community health center or family doctor, the obstacle presented by the informant is that there are still many patients who want to carry out direct services to the hospital without going to the health center or family doctor, another obstacle is the lack of tools for examining refractive errors and competence general practitioners to be able to make referrals in the diagnosis of disease. Hospital income will also increase if implementing this concept, if there is collaboration with related stakeholders such as BPJS Health, the Health Service, and other private parties, so that this will also have a good impact on the quality of service when hospital accreditation is carried out. The sophistication of information technology needs to be implemented as much as possible from the hospital so that it is easier so that patients do not pile up during services by registering online. The conclusion of this study is that the concept of a hospital without walls has not been implemented in the Eye Hospital of North Sulawesi Province because it has not followed standard operating procedures, quality competent resources and adequate infrastructure. FKTP Puskesmas in providing refractive error services have not provided complete supporting tools and the skills of FKTP doctors are still lacking, this will have an impact on assessing hospital accreditation in the quality of health services.
 Keywords: hospitals without walls, eye refractive error, family doctors

Perbandingan Metode ARAS dan EDAS dalam Menghasilkan Rekomendasi Layanan Akomodasi Hotel

This study compares the decision support model Additive Ratio Assessment (ARAS) and Evaluation based on Distance from Average Solution (EDAS) in selecting hotels in Semarang City. Meanwhile, the criterion-setting method adopts the Ranking of Centroid (ROC) to set criteria, determine the priority of criteria, and determine the weight of the criteria values. Comparison of the two algorithms needs to be done to compare the results and test the performance of the two algorithms, when developed into a decision support application to generate hotel service recommendations. Meanwhile, the stages in this research are as follows: data collection stage, using TripAdvisor; data processing stage, using ARAS and EDAS models; and data analysis stage. The results of this study show that the ranking results based on the EDAS method show that A1 occupies the first position with an NSP value of 1,000 and an NSN of 0,983. Furthermore, A3 occupies the second position with an NSP value of 0.707 and an NSN of 0.983. Meanwhile, A2 occupies the third position with an NSP value of 0.311 and an NSN of 0.983. Furthermore, the ARAS method ranking results show that A1 occupies the first position with a Si value of 0.171 and a Ki value of 0.994. Furthermore, A3 occupies the second position with a Si value of 0.169 and a Ki value of 0.984. Meanwhile, A2 occupies the third position with a Si value of 0.167 and a Ki value of 0.970. Based on the comparison of EDAS and ARAS methods, it can be seen that both produce the same alternative ranking where Padma Hotel Semarang ranks first, Aruss Hotel Semarang ranks second, and Tentrem Hotel Semarang ranks third. Thus, it can be seen that EDAS and ARAS methods can produce the best hotel recommendations for travelers by considering ratings and reviews on the TripAdvisor platform.