TIERS Information Technology Journal
TIERS Information Technology Journal memuat artikel Hasil Penelitian dan Studi Kepustakaan dari cabang Teknologi Informasi dengan bidang Sistem Informasi, Artificial Intelligence, Internet of Things, Big Data, e-commerce, Financial Technology, Business Digital
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<![CDATA[Java and Bali Shoreline Change Detection Based on Structural Similarity Index Measurement of Multispectral Images ]]>
<![CDATA[I Gede Wahyu Surya Dharma]]>;
<![CDATA[I Gede Karang Komala Putra]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.4468
<![CDATA[The abstract effectively delineates the pertinent issues addressed in the research, presenting a clear exposition of the challenges associated with coastline monitoring in Indonesia. The methodology is well-defined, incorporating the utilization of Landsat images, Structural Similarity Index Measurement (SSIM), and the application of Hidden Markov Random Field for segmentation. Moreover, the influence of Indonesia's equatorial positioning on cloud cover and the subsequent application of morphological operations are appropriately highlighted. However, it is crucial to provide explicit details regarding the research findings. Specifically, the abstract should elucidate the specific outcomes or results obtained from the conducted experiments or analyses. This addition would enhance the clarity and scientific robustness of the abstract, ensuring that it accurately reflects the research objectives and their corresponding achievements. Inclusion of quantitative data or statistical analyses would be particularly valuable in this regard. This would not only bolster the abstract but also furnish a more comprehensive overview of the study's empirical contributions.]]>
<![CDATA[Analysis and Design of PT KDA Langling Cooperative System Through Web-based Savings and Loan Transformation Technology ]]>
<![CDATA[Ade Agung]]>;
<![CDATA[Widja Yanto]]>;
<![CDATA[Dafit Afianto]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.4582
<![CDATA[PT KDA Langling Cooperative, as an economic enterprise dedicated to the interests of villagers and employees, is located in Langling Village RT 15, PT KDA Langling Sinarmas Housing. In order to manage savings and loans, the current system faces significant obstacles because it has not used computer technology. Recording is still done manually in books, causing delays in data collection and the potential for loss or damage to data in the archive. This research aims to analyze the current system, with a focus on fixing these problems. The solution is to design a web-based savings and loan information system that will optimize the efficiency and accuracy of data. The method that will be used by the author is literature review, data collection and using the waterfall model with the stages of the process of analyzing needs, design, implementation, testing and maintenance, using the PHP programming language and MySQL DBMS, UML and Usecase diagram. So that this research produces an integrated system that provides convenience for users in savings and loan activities and presents web-based financial information.]]>
<![CDATA[Resampling Techniques in Rainfall Classification of Banjarbaru using Decision Tree Method ]]>
<![CDATA[Selvi Annisa]]>;
<![CDATA[Yeni Rahkmawati]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.5069
<![CDATA[Continuous heavy rains, such as in 2021, can cause flood emergencies in various areas of Banjarbaru. Therefore, classification modeling is needed to predict rainfall classes based on climate parameters. The problem faced in the classification case is the unbalanced class distribution. Class imbalance occurs when the minority class is much smaller than the majority class. This research aims to compare three resampling techniques in handling imbalanced rainfall data in Banjarbaru using the Decision Tree model. The comparison methods used were sensitivity, specificity, and G-Mean values. In this research, the method used is a decision tree model with Random undersampling, Random Oversampling, and SMOTE. The result shows that the best model is the Decision tree model with the Random Undersampling technique because it provides the highest G-Mean value and sensitivity and specificity values above 70%. Based on this model, the variables that can separate the Rainy and Cloudy classes are Minimum temperature, Maximum temperature, and Sunshine duration, with the best separator being Maximum Temperature.]]>
<![CDATA[Clustering Time Series Using Dynamic Time Warping Distance in Provinces in Indonesia Based on Rice Prices ]]>
<![CDATA[Yeni Rahkmawati]]>;
<![CDATA[Selvi Annisa]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.5081
<![CDATA[Rice is a food commodity that is a basic need for Indonesian people. Since the end of 2022, average rice prices in Indonesia have been increasing, breaking the record for the highest price from August to October 2023. The price of rice in each province in Indonesia is different. This can happen because rice center provinces will distribute their rice production to other regions to meet rice needs. The grouping of provinces in Indonesia based on rice prices over time is an interesting thing to research. The analysis method used to group similar objects into groups for time series data is called clustering time series. The distance that can be used to measure the closeness of two-time series is the Dynamic Time Warping (DTW) distance. The clustering analysis used is the single, complete, average, Ward, and median linkage method. The results of the analysis show that time series clustering in provinces in Indonesia based on rice prices is best using median linkage hierarchical clustering. The median linkage method has a cophenetic correlation coefficient value of 0.899064, meaning that clustering using the DTW distance with the median difference is very good. The resulting clusters contained 3 clusters which had different characteristics between the clusters. There are 2 clusters that can be of concern to the government, because there are clusters that have rice prices that have always been high in the last period and there are provincial clusters that have rice prices that are very diverse or can be said to be unstable.]]>
<![CDATA[A Review of Diverse Diabetic Prediction Models: A Literature Study ]]>
<![CDATA[Amina Zafar]]>;
<![CDATA[Areeg Tahir]]>;
<![CDATA[Umer Asgher]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.3617
<![CDATA[Diabetes is a disease described by extreme glucose measurement in the blood and can trigger an excessive number of problems likewise in the body, like the failure of internal organs, retinopathy, and neuropathy. As per the forecasts made by World Health Organization, the figure might reach roughly 642 million by 2040, and that implies one in ten might experience diabetic diseases due to various reasons such as low activity levels, unhealthy routines, and schedules, rising tension levels and so on. Many researchers in the past have explored widely on diabetes disease through AI calculations and ML algorithms. The possibility that had persuaded us to introduce a survey of different prediction models of diabetic disease is to address the diabetes issue by recognizing and coordinating the discoveries of all-important, individual examinations. In this research, we have analyzed the different prediction algorithms and techniques by different researchers that how they predict diabetic disease. Also, we have analyzed the PIMA and symptom and other datasets and how they reach their resultant accuracy by applying different classifiers. Because of non-linear, correlated, and complex structured data in the medical field, diabetic data analysis is very difficult. That’s why Ml-based algorithms have been utilized for the prediction of diabetic disease and handle a large amount of data and it needs a different approach from others at the initial stage. We emphatically suggest our review since it involves articles from different sources that will assist different specialists with different models of prediction for diabetes.]]>
<![CDATA[Data Mining Rough Set Method In Analyzing Communities Disposing of Garbage in Rivers ]]>
<![CDATA[Sanny Edinov]]>;
<![CDATA[Rezki Fauzi]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.4478
<![CDATA[The waste management approach is a worldwide problem and is often neglected. The situation in urban areas is worse than in rural areas. It is a big challenge to deal with this dilemma, therefore, the management of a better management system is inevitable. The input data used in this study included the community's last educational data and social stratification, both through questionnaires and interviews with the community. Furthermore, the data that has been presented in the decision system is collected or eliminated for each object that has the same attributes, then summed and collected into the same class so that the cleaning technique process becomes simple (equivalent class). The Advanced Discernibility Matrix and the Discernibility Modulo D Matrix will compare a collection of attributes based on the equivalence class that will be modeled with the last Education modeled "A", the social stratification of society is modeled "B". The reduction results obtained reveal that there are several reasons why people throw garbage in the river. This provides information, the latest differences in social stratification and education can influence people's mindset and habits of disposing of garbage. The social stratification of people who are not from the wealthy class and have the last elementary-junior high school education contributes more negatively to the fullness of the river flow with garbage.]]>
<![CDATA[The Effect of User Experience and Usability on User Satisfaction and Continuance Intention in the JConnect Mobile Application ]]>
<![CDATA[Novita Khasanah]]>;
<![CDATA[Faris Mushlihul Amin]]>;
<![CDATA[Andhy Permadi]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.4566
<![CDATA[Technological innovation has developed in several sectors of society, such as banking. Banking digitalization in Indonesia has increased by 46.72% in 2022. With this increase, every bank will continue to strive for the quality of its mobile banking services in order to improve optimal and effective service for its customers. PT BPD East Java made similar efforts to improve digital banking branding services by launching JConnect Mobile. However, based on data, the JConnect Mobile application received a low rating, namely 3.2. From this data, it is necessary to evaluate the user experience and usability, there is user satisfaction and sustainable intentions to support the projection and direction of user satisfaction or sustainable intentions. Therefore, the aim of this research is to measure the level of evaluation of user experience and usability and its influence on user satisfaction and continuance intention. The indicators used to measure user experience and usability are the UEQ and SUS methods. This research uses a quantitative approach with linear regression analysis. Of the 8 hypotheses proposed, 3 hypotheses were rejected and 5 hypotheses were accepted. So it can be concluded that the aspects that influence user satisfaction and continuance intention are perspicuity, efficiency, novelty and usability.]]>
<![CDATA[Meta-Analysis Of Genetic Algorithm Implementation For Optimization Of Artificial Neural Network Methods ]]>
<![CDATA[Komang Nova Artawan]]>;
<![CDATA[Agus Dharma]]>;
<![CDATA[I Made Ardi Sudestra]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.5515
<![CDATA[One of artificial intelligence methods, which is artificial neural networks, have been widely used in data analysis to make predictions, forecasting, and data classification. The artificial neural network method has convergence or local minimum problems because it requires randomly generated weight values. There is a lot of research that discusses optimization techniques for initiating this initial weight to solve that problem. In this study, a meta-analysis was carried out regarding the implementation of genetic algorithms for optimization of artificial neural network methods. Based on 10 journals that has reviewed in this study, it was concluded that optimization of the genetic algorithm can increase the output value of the artificial neural network by 3.44%, but this genetic algorithm optimization have no significant effect based on the sig (2-tailed) value is 0.595 and t count value is 0.551 that have been obtained and tested using paired samples t-test method with help of SPSS software.]]>
<![CDATA[Implementation Of The Simple Additive Weighting (SAW) Method On The Determination Of Scholarship Recipients ]]>
<![CDATA[Made Ary Sanjaya]]>;
<![CDATA[I Gusti Arya Sidhi Narendra]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.5518
<![CDATA[In recent years, technology and science have developed quite drastically. With advances in technology and science, we can create a system to help solve a problem such as granting scholarships. The purpose of this research is to build a decision support system to help and make it easier to determine who is entitled to get a scholarship. The method we use here is Simple Additive Weighting (SAW) which simplifies the process of awarding scholarships which is then carried out by a process of ranking and determining the weight values for each criterion attribute to get the best alternative and who is entitled to get the scholarship. The data used to determine scholarship recipients includes GPA data (Grade Point Average), parents income data, and parents dependents data. The results obtained in this study indicate that a decision support system can make it easier to determine who is entitled to get the scholarship without requiring more time than the manual method which will also make it easier for humans to make decisions.]]>
<![CDATA[Optimizing Scholarship Selection: A Decision Support System Approach Using the Analytical Hierarchy Process ]]>
<![CDATA[Agus Yusuf Novianto]]>
<![CDATA[ TIERS Information Technology Journal Vol. 4 No. 2 (2023) ]]>
Publisher : <![CDATA[Universitas Pendidikan Nasional ]]>
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DOI: 10.38043/tiers.v4i2.5519
<![CDATA[Scholarship is the provision of financial assistance to individuals, which aims to be used for the continuity of the education pursued. Per the scholarship provider's regulations, criteria are needed to determine who will be selected to receive the scholarship. Scholars are distributed by schools or other parties that organize scholarships to help someone who is underprivileged or who has achieved something during his studies. A decision support system is needed to help determine someone who deserves a scholarship. This system can analyze academic performance, financial needs, extracurricular activities, and personal statements to determine the most deserving candidates. By using a decision support system, scholarship providers can ensure that the scholarships are given to individuals who benefit the most from the financial assistance and are dedicated to their education. Ultimately, scholarships aim to help individuals overcome financial barriers and achieve their academic and career goals.]]>
