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Website based classification of karo uis types in north sumatra using convolutional neural network (CNN) algorithm
Full text linkIndonesia is one of the largest archipelagic countries in the world. It has abundant cultural diversity including nature, tribes. One of the tribes in Indonesia is the Batak Karo tribe. Batak Karo is a tribe that inhabits the Karo plateau area, North Sumatra, Indonesia. Batak Karo has various cultures, one of which is a traditional cloth known as uis. Unfortunately, the Karo Batak community, especially the younger generation, has insufficient knowledge of the types of uis. Thus, a solution that is easily accessible both in terms of time, cost and experts in recognizing Uis is needed. This research aims to build a website-based application that can classify the types of Karo Uis. This research uses Convolution neural network (CNN) using Alex Net architecture, to get the best model this research compares several hyper parameters, namely learning rate of 10-1 to 10-4, and data division with a ratio of 70:30 and 80:20. The best model falls on a ratio of 70:30 and a learning rate of 10-4 with an accuracy of 98%, and a validation accuracy of 99%, then the model is stored in h5 format in this study successfully builds and implements the model into a web-based application
Design internet of things for smart waste bin management with wemos based and firebase application
Full text linkThe communication process for notifications involves sending alerts to users through a combination of automation and telecommunications technologies. The design smart trash, utilizing the Wemos microcontroller, performs various automated tasks such as opening and closing, compacting the garbage, and providing status notifications. These notifications are transmitted through the Firebase web server communication and an Android application on smartphones. Following successful testing, the system functions according to the programmed specifications. It achieves automatic opening and closing within a proximity range of ≤ 10 cm, demonstrates an average waste compaction rate of 45%, and delivers notifications to users indicating the trash status—whether it's empty, halfway full, or completely full
Building new hotel brand reputation to attract guest in Semarang city
No full textThe hotel industry is an industry that plays an important role in the development of the economy and tourism in Indonesia. The research aims to elaborate brand reputation for new hotels in Semarang. This article uses descriptive research using descriptive qualitative research methods assisted by data collection through documentation and literature study. The research will be conducted using AIDA theory on the 5 newest hotels built in the last 3 years in the city of Semarang. The results show that an increasing of guests in numbers. with the help of AIDA theory, and comparison, it shows that we can still be able to save the hotel industry so that it will not perish that the Room Occupancy Rate (ROR) of star-rated hotels in semarang city for the November 2021 period was recorded at 60.25 percent or an increase of 4.12 points compared to October 2022, which was influenced by the increase in ROR that occurred in the class of 2-star, 3-star, 4-star and 5-star hotels (BPS, 2023). It can be concluded that the ratings that guests give to hotels have good feedback such as good and friendly service, comfortable rooms, strategic hotel location. New hotel gain market awareness due to the needs of customer especially in this recent time. Due to an increasing of numbers in covid cases, and with many new hotels, it shows the interest of hospitality industry. Hotel must do more to promote and get more customers
Service Level Agreement Enforcement Model with Human Factor for Electronic Health Record
Full text linkService Level Agreement (SLA) is a document contract between the service provider and service recipient which is the expected services to be delivered and received. SLA includes all the information about the services provided and their performance. The SLA identified the level of services performance such as penalties, priorities, compensation and resolution time. If the quality of service does not meet the SLA usage then the service provider need to pay penalties also known as SLA violation. SLA violation occurred might be from software or hardware but another factor such as human factor also involved. The performance of the system and the quality of services requires a human interference to enforce the SLA. In this research work, the human factor such as user willingness, skill/knowledge, information sharing, Staff adequacy was being investigated. The method survey was implemented to find the relationship between human factor and SLA usage. Respondents in IT department are selected to fill in survey form. 11 respondents are used for pilot study to find the reliability of instrument and 24 respondents are used for actual data. The result show there is positive significant value in relationship between human factor and SLA usage
Narrative literature review: Efficiency enhancement - user trust in chatbots as a tool for improving service quality by humans
Full text linkChatbots have become efficient and reliable tools for instant and real-time information dissemination. Despite their effectiveness, user trust in chatbot systems remains relatively low. A holistic approach is necessary, integrating user emotional experiences, trust-building strategies, and continuous technological refinement to maximize chatbot benefits across various sectors. This research explores the potential for selective information dissemination based on user preferences using chatbots combined with artificial intelligence. Through a narrative approach, the study reviews literature and analyzes eight articles related to chatbots' application in information dissemination. The results indicate that chatbots are efficient in providing information and can be customized for various needs, such as population services, reminder notifications, and book processing. Chatbots have the potential to enhance services and can be integrated into information systems to improve service quality. However, challenges such as reliance on high-quality data and machine learning, difficulties in understanding non-formal language or slang, and limitations in handling complex questions need to be addressed for chatbots to reach their full potential
Breast tumor classification using adam and optuna model optimization based on CNN architecture
Full text linkBreast cancer presents a significant challenge due to its complexity and the urgency of the intervention required to prevent metastasis and potential fatality. This article highlights the innovative application of Convolutional Neural Networks (CNN) in breast tumor classification, marking substantial progress in the field. The key to this advancement is the collaboration among medical professionals, scientists, and artificial intelligence experts, which maximizes the potential of technology. The research involved three phases of training with varying proportions of training data. The first training phase achieved the highest accuracy rate of 99.72%, with an average accuracy of 99.05% in all three phases. Metrics such as precision, recall, and F1 score were also highly satisfactory, underscoring the model's efficacy in accurately classifying breast tumors. Future research aims to develop more complex and precise predictive models by incorporating larger and more representative datasets. This progression promises to improve understanding, prevention, and management of breast cancer, offering hope for significant advances in 2024 and beyond
Gabor wavelet and multiclass support vector machine for braille image classification
Full text linkBraille is a letter designed for the visually impaired. As a family with normal vision who have a visually impaired child find it difficult to Teach their child how to learn and understand the process of learning from home. Learning braille requires good finger sensitivity and memory to memorize each letterform, making it difficult to learn. With this study, braille letters can be detected from the image using the Gabor Wavelet method to extract braille images and combined with the Multiclass Support Vector Machine (Multiclass SVM) algorithm as a classification method for extracted braille images. Data testing was performed using a confusion matrix to determine the level of precision, accuracy, and recall. According to the results of tests performed on 910 braille data using confusion matrix, the highest recognition accuracy was 98,02%. The accuracy of these results is impacted by the parameters of the training process, the training data, and the test data used. This research has the opportunity to be developed in voice-based card recognition to help the visually impaired in the future research
Reconstruction of "berkah jaya bake house" marketing strategy for consumer visiting interest
No full textThe fact that marketing continues to evolve towards digital dynamics, E-WoM is present as a key element in the latest marketing strategies. This study will provide a brief overview of E-WoM as a natural form of marketing carried out by consumers and how optimized marketing strategies can benefit from it. The study focuses on studying the impact of the spread of E-WoM on consumer visiting interest and aims to examine the role and impact of E-WoM management on consumers. The qualitative approach is carried out by the author with case studies, field studies, to literature studies assisted by documentation and interview methods. The data analysis model is drawn conclusions with a data triangulation model. In the process of using social media, berkah jaya bake house seems to rarely post pictures, but still has high polularity due to the influence of E-WoM. Planning for the reconstruction of the E-WoM marketing strategy is carried out at the locus of "Berkah Jaya Bake House", especially through social media accounts
Study of the cooperation relationship between the front office and housekeeping departments through communication at hotel tentrem semarang
No full textThis research aims to explain the effectiveness of cooperation relationship between the Front Office and the Housekeeping Departments and to improve the communication patterns of cooperative relations between the Front Office and Housekeeping. This study uses a qualitative method with a descriptive type. Data collection techniques use observation and documentation in order to obtain accurate data regarding cooperation and communication. The observations made were conducting on the job training for 6 months in the Front Office Department Hotel Tentrem Semarang. The results obtained from this study is that there are still need improvements in communication between the front office and housekeeping departments at the Tentrem Semarang hotel. To improve cooperative relations between front office and housekeeping departments is carried out through a combination of verbal and non-verbal communication. The communication must also be reinforced with clear instruction from the department heads to ensure that operations run effectively and smoothly
Online payment fraud prediction with machine learning approach using naive bayes algorithm
No full textThe increase in e-commerce has provided easy access for the public, but it also opens up opportunities for fraud in online transactions. Payment fraud is also a problem that often arises in transactions through electronic media. This research aims to analyze payment fraud in e-commerce transactions. This research uses a machine learning approach using the Naive Bayes algorithm. This research uses online transaction datasets involving various attributes such as payment and shipping methods. The developed Naive Bayes model achieved an accuracy of 61.03% with K = 7. The evaluation shows a balance between precision (59.46%) and recall (62.05%), although this study is limited by data quality and basic assumptions of Naive Bayes. In future research, it is worth considering the use of additional features or more complex data processing to improve the performance of fraud detection in online transactions. This research provides important insights in the fight against financial crime in the context of electronic commerce