Telematika
Not a member yet
319 research outputs found
Sort by
Autoregressive Integrated Moving Average (ARIMA) Models For Forecasting Sales Of Jeans Products
Full text linkPurpose: To be able to compete with other companies, it is necessary to estimate and forecast jeans products that will be ordered according to consumer demand every month, so that there is no excess inventory and product shortage. If there is a shortage of goods, the consumer will be disappointed with the seller, and vice versa if the goods are overstocked, the quality will continue to decline to the detriment of the seller and the buyer, resulting in a shortage of materials.Methodology: To overcome the problem of selling jeans products, the ARIMA method is suitable to overcome the problem of forecasting the stock of jeans sales. ARIMA model is a model that completely ignores the independent variables in making forecasts. ARIMA uses past and present values of the dependent variable to produce accurate short-term forecasting.Results: The built forecasting has a MAPE accuracy rate of 17.05% so it can be said that predicting has good results according to the criteria. Forecasting results in the following year show that sales tend to increase from the previous year.Originality: This research was conducted using sales data of jeans products at company XYZ and using the ARIMA method which previous researchers have never done
Systematic Literature Review on Information Technology Governance in Government
Full text linkPurpose: This article aims to assist the government in developing better, more efficient, and sustainable public governance by utilizing information technology and artificial intelligence. The article provides insights on how information technology and artificial intelligence can be applied in public governance to improve the efficiency, effectiveness, and sustainability of public services, as well as to enhance public trust in the government.Design/Method/Approach: The method used in this article is a Systematic Literature Review (SLR), which is a systematic and methodological research method for collecting, evaluating, and synthesizing evidence from previous studies in the field under investigation, through search terms and searching for information in online databases and creating inclusion and exclusion criteria.Results: This article is expected to achieve more efficient, effective, and sustainable public governance and improve the quality of public services and public trust. The article also shows that information technology and artificial intelligence have become an integral part of public governance in various countries, with many countries taking a holistic and sustainable approach.Originality/State of the art: The state-of-the-art of this article is that information technology and artificial intelligence can be effectively used to improve public governance to achieve better, more efficient, and sustainable goals. The article also emphasizes the importance of considering data privacy, cyber security, and unwanted environmental impacts, as well as considering ethical and human rights aspects in the development of artificial intelligence. This will help the government to develop and implement information technology and artificial intelligence in public governance in a responsible and sustainable manner
Tweet Analysis of Mental Illness Using K-Means Clustering and Support Vector Machine
Full text linkPurpose: Social media, particularly Twitter, provides a venue for individuals to share their thoughts. The public\u27s perception of mental illnesses is often debated on Twitter. So yet, no evaluation of community tweets connected to data on mental health conditions has been performed. The purpose of this study is to examine tweets linked to mental illnesses in Indonesia in order to identify the themes of conversation and the polarity trends of these tweets.Design/methodology/approach: To address this issue, the K-Means Clustering algorithm is utilized to aggregate tweet data that is used to find themes of conversation. The emotion polarity value of each cluster result was then determined using the Support Vector Machine (SVM) approach.Findings/results: This study generated five topic clusters based on tweets about mental illness. While sentiment analysis revealed that all clusters had more negative sentiment classes than positive. Cluster 4 and Cluster 5 had the highest number of negative sentiment values. These clusters emphasize the necessity of consulting with psychiatrists and psychologists if people have mental health disorders, as well as financing for mental health disorder treatment through BPJS Kesehatan services.Originality/value/state of the art: The analysis was done in two stages: data grouping to find themes of conversation using K-Means clustering and SVM to look for positive and negative polarity values associated to twitter data about mental illness
User Experience Analysis on Student Services Website using User Experience Questionnaire (UEQ) KPI and Importance Performance Analysis (IPA) (Case Study: UPN "Veteran" Yogyakarta)
Full text linkPurpose: This study aims to obtain an end-user assessment of User Experience on the Student Services website so that it can be used as a priority material for improvement for the Bureau of Academic, Student Affairs, Planning, and Cooperation (AKPK) of the National Development University (UPN) "Veteran" Yogyakarta, when developing a website further.Design/methodology/approach: The User Experience Assessment on the Student Services website refers to 6 aspects of the assessment of the User Experience Questionnaire (UEQ) KPI method. The existing results will be mapped into an IPA (Importance Performance Analysis) diagram.Findings/result: The results of user experience testing on the Student Services website using the UEQ method, get the Good category for the Efficiency (1.56) and Dependability (1.57) aspects, the Above average category for the Attractiveness aspect (1.28), Perspicuity (1.57), and Stimulation (1.15) and the Bad category on Novelty (-0.27). Mapping the results of the UEQ KPI to the IPA quadrant, getting the results of the Attractiveness, Perspicuity, Efficiency, and Dependability aspects are in Quadrant 1, the Stimulation aspect is in Quadrant 2, the Novelty aspect is in Quadrant 3, and no aspect is in Quadrant 4. Based on the results of the study, it can be concluded that the user experience value of the end user is good. Recommendations for improvement priorities for the Student Services website can further prioritize Novelty aspels that are in Quadrant 3 and in Bad condition.Originality/value/state of the art: The focus of this research is the same as previous research, namely analyzing User Experience with reference to the assessment aspects of the KPI User Experience Questionnaire (UEQ) and IPA (Importance Performance Analysis) methods. The difference that can be seen in this study is from the implementation of the method into different case studies with the objectives and urgency and problems described in accordance with the existing research object
Social Media Analysis and Topic Modeling: Case Study of Stunting in Indonesia
Full text linkPurpose: Stunting is a problem that currently requires special attention in Indonesia. The stunting rate in 2022 will drop to 21.6%, and for the future, the government has set a target of up to 14% in 2024. Rapid technological developments and freedom of expression on the internet produce review text data that can be analyzed for evaluation. This study analyzes the text data of Twitter users\u27 reviews on stunting. The method used is a text-mining approach and topic modeling based on Latent Dirichlet Allocation.Design/methodology/approach: The methodology used in this study is Latent Dirichlet Allocation. The data was collected from twitter with the keyword \u27stunting\u27. After, the data was cleaned and then modeled using the Latent Dirichlet Allocation.Findings/results: The results show that negative sentiment dominates by 60.6%, positive sentiment by 31.5%, and neutral by 7.9%. In addition, this research shows that \u27children\u27, \u27decrease\u27, \u27number\u27, \u27prevention\u27, and \u27nutrition\u27 are among the words that often appear on stunting.Originality/value/state of the art: This study uses the keyword stunting and analyzes it. Social media analytics show that the people of Indonesia are primarily aware of stunting. Also, the Latent Dirichlet Analysis can be used to create the model
Analysis Of Factors Affecting Interest Kai Access Application Users Using Models Unified Theory Of Acceptance And Use Of Technology 2 (UTAUT 2)
Full text linkPurpose: This study aims to analyze the factors that influence user interest in the KAI Access application using the Unified Theory Of Acceptance And Use Of Technology 2 (UTAUT 2) model.Methodology: This study used the Structural Equation Modeling (SEM) method with two tests, namely the outer model and the inner model with the help of the SmartPLS Version 3 software. A total of 406 respondent data were used from the Special Region of Yogyakarta and also users of the KAI Access application.Results: The results of the study show that of the fourteen hypotheses proposed in the study, only seven were accepted, namely social influence, facilitating conditions, hedonic motivation, price value, and habit. The strongest factors that have a significant effect are hedonic motivation and habit.State of the art: based on previous research, this study has quite similar characteristics but different cases, variables, and research samples
Performance Analysis of XGBoost Algorithm to Determine the Most Optimal Parameters and Features in Predicting Stock Price Movement
Full text linkPurpose: The research aims to find the best parameters and features for predicting stock price movement using the XGBoost algorithm. The parameters are searched using the RMSE value, and the features are searched using the importance value.Design/methodology/approach: The research data is the stock data of Amazon.com company (AMZN). The dataset contains the Date, Low, Open, Volume, High, Close, and Adjusted Close features. The dataset is ensured to have no missing data by handling missing values. The input feature is selected using the Pearson Correlation feature selection method. To prevent the difference between the highest and lowest stock price from being too far apart, the data is scaled using the scaling method. To avoid bias that may appear in the prediction result, cross-validation is used with the Min Max Scaling method, which will devide the dataset into training data and testing data within a range of 30 days after the training data. The parameters to be tested include n_estimator = 500, early stopping round = 3, learning rate = 0.01, 0.05, 0.1, and max_depth (tree depth) = 3, 4, 5.Findings/result: The result of the research that a learning rate of 0.05 and a tree depth of 5 obtained the lowest RMSE result compared to other models, with an RMSE of 0.009437. The Low feature obtained the highest importance value among all the models built.Originality/value/state of the art: This study used testing data within a range of 30 days after the training data and used a combination of parameters, including n_estimator = 500, early stopping round = 3, learning rate = 0.01, 0.05, 0.1, amd max_depth (tree depth) = 3, 4, 5.
Retinal Vessel Segmentation to Support Foveal Avascular Zone Detection
Full text linkPurpose: This study aims to perform retinal vessel segmentation to support foveal avascular zone detection. Methodology: The proposed approach consists of a multi-stage image processing approach, including preprocessing, image quality enhancementt, and segmentation of retinal blood vessel using matched filter and length filter techniques.Findings: The proposed framework has achieved remarkable results with an average sensitivity, specificity, and accuracy of 77.99%, 86.43%, and 85.24%, respectively.Value: This achievement has the potential to significantly enhance the accuracy and efficiency of detecting and diagnosing medical conditions related to the retina, improving the quality of life for countless individuals
Quality Analysis of the Ahmad Dahlan University Digital Library Using the WebQual 4.0 and Importance Analysis Performance (IPA) Method.
Full text linkPurpose: This paper is the result of research which aims to obtain results of measuring the quality of web services from the Library Unit at Ahmad Dahlan University, especially from the perceptions of student users in order to prepare recommendations for improving services. This paper is the result of research which aims to obtain results of measuring the quality of web services, especially from perceptions student users in order to prepare recommendations for improving service mediaDesign/methodology/approach: Based on sampling data collected using a questionnaire and calculated using statistics. The next step is to measure the WebQuel 4.0 method, the results of which are combined with the Importance Performance Analysis (IPA) method to determine recommendations.Findings/result: The research results show that each independent variable, namely the usability variable and the information quality variable, partially has a relationship or is correlated with the dependent variable, namely user satisfaction, while the interaction service quality variable partially has no relationship or is uncorrelated with the dependent variable. The results of simultaneous hypothesis testing show that the independent variable has an effect on the dependent variable so that the hypothesis can be simultaneously accepted. Based on the analysis using the IPA method, there are three things in Quadrant 1 (Top Priority) which are not in accordance with user expectations and need to be improved, namely "the DIGILIB UAD web is easy to learn", "the DIGILIB UAD web has an attractive appearance", "the DIGILIB UAD web has the function of library web type”.Originality/value/state of the art: Based on previous research and the results of previous digilib web development, the research produced a new assessment of the quality measures of web services at UPT Libraries, and made it the main alternative for developing service media in a better direction
Framework Management to Minimize Risk in Protecting Enterprise Systems: Systematic Literature Review
Full text linkPurpose: This study aims to determine the efforts to minimize the occurrence of risks in enterprise systems and how far the framework is applied to an organization, as well as what steps must be applied in anticipation of it.Design/methodology/approach: This study uses a systematic review research method of literature published by international journals in the period 2016 to 2021 which is subscribed to by Diponegoro University.Findings/result: Most of the selected journals stated that in an effort to secure enterprise systems in an organization, they really consider several aspects in it, especially in terms of cost which is one of the biggest considerations in it, besides that support from policy makers must be needed to make guidelines in implementing framework (framework) regarding the limitations of Authentication access and interaction on a system.Originality/value/state of the art: the method applied will focus on discussing the realm of enterprise systems, specifically discussing framework management in an effort to minimize risks to enterprise systems.