{"title":"Integration of Design Sprint Method into Mobile Development Application Life Cycle to Create MobilePQI Application Prototype","authors":"Fenty Eka Muzayyana Agustin, Nuriyah Thahir, Ade Rina Farida, Kania Mayastika","doi":"10.15408/jti.v17i1.37818","DOIUrl":"https://doi.org/10.15408/jti.v17i1.37818","url":null,"abstract":"This study aims to create a mobile-based learning application that can be used to support blended learning. Blended Learning is carried out synchronously, either online using Zoom or Google Meet, or offline in the classroom. asynchronous learning is implemented using MobilePQI Apps. MobilePQI Apps was developed using the Kotlin programming tool and MADLC methodology (Mobile Application Development Life Cycle). MADLC consists of seven stages: Identification; Design; Development; Prototyping; Testing; Deployment; and Maintenance. We use design sprint method and figma to create design prototype, and Kotlin development kit. The testing method used heuristics evaluation which tests 10 usability principles. The number of questions asked was 115, with 5 respondents consisting of 3 students and 3 lecturers. The results of the heuristics evaluation score were 89% of respondents answered YES. That it can be concluded that the 10 usability principles of the prototype was acceptable. The SUS results show a score of 74, which means the application's user interface is in the Good and acceptable category.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"49 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"SVM Optimization with Grid Search Cross Validation for Improving Accuracy of Schizophrenia Classification Based on EEG Signal","authors":"Masdar Desiawan, Achmad Solichin","doi":"10.15408/jti.v17i1.37422","DOIUrl":"https://doi.org/10.15408/jti.v17i1.37422","url":null,"abstract":"The advantage of the Support Vector Machine (SVM) is that it can solve classification and regression problems both linearly and non-linearly. SVM also has high accuracy and a relatively low error rate. However, SVM also has weaknesses, namely the difficulty of determining optimal parameter values, even though setting exact parameter values affects the accuracy of SVM classification. Therefore, to overcome the weaknesses of SVM, optimizing and finding optimal parameter values is necessary. The aim of this research is SVM optimization to find optimal parameter values using the Grid Search Cross-Validation method to increase accuracy in schizophrenia classification. Experiments show that optimization parameters always find a nearly optimal combination of parameters within a specific range. The results of this study show that the level of accuracy obtained by SVM with the grid search cross-validation method in the schizophrenia classification increased by 9.5% with the best parameters, namely C = 1000, gamma = scale, and kernel = RBF, the best parameters were applied to the SVM algorithm and obtained an accuracy of 99.75%, previously without optimizing the accuracy reached 90.25%. The optimal parameters of the SVM obtained by the grid search cross-validation method with a high degree of accuracy can be used as a model to overcome the classification of schizophrenia.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"22 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141120030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analyzing User Satisfaction of a Study Abroad Guidance Company Website Using the Customer Satisfaction Index (CSI) Method","authors":"Fajrian Nispi, Ana Kurniawati, Lily Wulandari","doi":"10.15408/jti.v17i1.34612","DOIUrl":"https://doi.org/10.15408/jti.v17i1.34612","url":null,"abstract":"XYZ is an education technology company dedicated to assisting Indonesian students in gaining acceptance to universities worldwide through full scholarship, partial, or self-funding. Until 2024, XYZ has a thousand alumni accepted in 46 countries and many universities worldwide. One of the marketing trackers that XYZ has is the website. With this website, the company will deliver the service to customers and receive user feedback to run and improve their services. The measurement of user satisfaction level can be used to improve the quality of service in digital media. The method used in this study to measure user satisfaction level is the Customer Satisfaction Index (CSI), which evaluates satisfaction across five (5) dimensions: usability, information quality, assurance, reliability, and data accessibility. This method's result shows a value of 83.64%, which means the XYZ website performance is in the \"Very Satisfied\" category. These findings suggest that XYZ Company's website is highly effective and has a \"Very Satisfied\" result category in meeting user needs, paving the way for continued success in their mission to assist Indonesian students in pursuing global education opportunities","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"15 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141119228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Machine Learning for the Model Prediction of Final Semester Assessment (FSA) using the Multiple Linear Regression Method","authors":"Fitria Rachmawati, Jejen Jaenudin, Novita Br Ginting, Panji Laksono","doi":"10.15408/jti.v17i1.28652","DOIUrl":"https://doi.org/10.15408/jti.v17i1.28652","url":null,"abstract":"Corona virus (COVID-19) is the reason behind the collapse of the National Assembly. The first is the Final Semester Assessment (FSA) , which is a component of the student's graduation. The aforementioned evaluation process is a crucial consideration for the teacher since it uses several intricate surveys and mark components. A prediction model is employed to assist teachers in providing suitable results for student learning. The method that is used is called the multiple linear regression. This multiple linear regression algorithm yields an accuracy level of approximately 92%. The analysis results using the method are used as a guide to understanding student’s index. This index is a rating that appears based on the Minimum Credit Count (MCC). Therefore, the goal of this study is to determine students' understanding of the FSA prediction value, which will be taken into consideration through the results of the MCC weights in the form of a range in the form of \"Grade.\" Additionally, the research aims to determine the accuracy of the results from the model obtained using multiple linear regression algorithms in predicting students' FSA.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"11 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141119813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Utilization of the FP-Growth Algorithm on MSME Transaction Data:Recommendations for Small Gifts from The Padang Region","authors":"Firman Noor Hasan, Riyan Ariyansah","doi":"10.15408/jti.v17i1.37966","DOIUrl":"https://doi.org/10.15408/jti.v17i1.37966","url":null,"abstract":"The existence of adequate transaction data turns out to have a similar sales transaction pattern for MSMEs, so it would be a shame if it were left like that. Moreover, this data can be used to increase efficiency in MSMEs in the culinary sector, one of which is as a recommendation for small gifts. The study uses the Association Rules technique, whereas fp-growth is used to obtain a combination of elements. The goal is to facilitate MSMEs' ability to suggest small gifts to clients. The fp-growth algorithm calculation was implemented to process 2043 data originating from transaction data in MSMEs, with the specified minimum support value being 15%, while the minimum confidence value determined was 55%. The results of the trial obtained the two best rules, namely, \"If a customer buys a list of small gifts from Balado Sanjai Chips, then the customer will buy Jangek Crackers\" and \"If a customer buys Jangek Crackers, then the customer will buy Sanjai Balado Chips\".","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"100 43","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141122614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The Comparison of the Effectiveness and Efficiency of Fine-Tuning Models on Stable Diffusion in Creating Concept Art","authors":"Abdul Bilal Qowy, Ahmad Nur Ihsan, Sri Hartati","doi":"10.15408/jti.v17i1.37942","DOIUrl":"https://doi.org/10.15408/jti.v17i1.37942","url":null,"abstract":"This research aims to overcome the limitations of the Stable Diffusion model in creating conceptual works of art, focusing on problem identification, research objectives, methodology and research results. Even though Stable Diffusion has been recognized as the best model, especially in the context of creating conceptual artwork, there is still a need to simplify the process of creating concept art and find the most suitable generative model. This research used three methods: Latent Diffusion Model, Dreambooth: fine-tuning Model, and Stable Diffusion. The research results show that the Dreambooth model produces a more real and realistic painting style, while Textual Inversion tends towards a fantasy and cartoonist style. Although the effectiveness of both is relatively high, with minimal differences, the Dreambooth model is proven to be more effective based on the consistency of FID, PSNR, and visual perception scores. The Dreambooth model is more efficient in training time, even though it requires more memory, while the inference time for both is relatively similar. This research makes a significant contribution to the development of artificial intelligence in the creative industries, opens up opportunities to improve the use of generative models in creating conceptual works of art, and can potentially drive positive change in the use of artificial intelligence in the creative industries more broadly. ","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"34 24","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nenny Anggraini, S. Putra, Luh Kesuma Wardhani, Farid Dhiya Ul Arif, Nashrul Hakiem, I. Shofi
{"title":"A Comparative Analysis of Random Forest, XGBoost, and LightGBM Algorithms for Emotion Classification in Reddit Comments","authors":"Nenny Anggraini, S. Putra, Luh Kesuma Wardhani, Farid Dhiya Ul Arif, Nashrul Hakiem, I. Shofi","doi":"10.15408/jti.v17i1.38651","DOIUrl":"https://doi.org/10.15408/jti.v17i1.38651","url":null,"abstract":"This research aims to compare the performance of three classification algorithms, namely Random Forest, XGBoost, and LightGBM, in classifying emotions in Reddit comments. Emotion classification in Reddit comments is a complex classification problem due to its numerous variations and ambiguities. This research utilizes the GoEmotions Fine-Grained dataset, filtered down to 7,325 Reddit comments with 5 different basic emotion labels. In this study, data preprocessing steps, feature extraction using CountVectorizer and TF-IDF, and hyperparameter tuning using GridSearchCV for each algorithm are conducted. Subsequently, model evaluation is performed using Cross-Validation and confusion matrix. The results of the study indicate that Random Forest outperforms the XGBoost and LightGBM algorithm with an accuracy of 75.38% compared to XGBoost with 69.05% accuracy and LightGBM with 66.63% accuracy.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"32 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141118906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Comparative Study of Students Graduation Analysis Using Classification Methods in Undergraduate Electrical Engineering Tidar University","authors":"Damar Wicaksono, Sapto Nisworo, Imam Adi Nata","doi":"10.15408/jti.v17i1.32132","DOIUrl":"https://doi.org/10.15408/jti.v17i1.32132","url":null,"abstract":"This research aimed to classify achievement factors for electrical engineering students at Tidar University using K-Means and Agglomerative Clustering classification algorithms. The goal was to understand if any parameters influence high-achieving student performance. The Indonesian government and private sector for university students provide significant education funds. Student scholarships are awarded based primarily on GPA and entry path, overburdening staff and causing confusion during distribution to eligible recipients. A system was needed to accommodate additional eligible criteria. The researcher selected factors to identify engineering student performance, including school origin, entry path, tuition fees, and GPA. These inputs could determine graduation status. The results compared calculation methods based on collected data accuracy, processing times, and characterizing clustered data to determine the best classification method. Agglomerative Hierarchical Clustering performed better. Accuracy testing on 600 training data points yielded 73.94% for improved K-means and 90.42% for AHC. The Average processing time was 674.92 seconds for improved K-means and 554.35 seconds for AHC. Silhouette testing also characterized calculation methods, with improved K-means scoring best at 0.654 and AHC at 0.787 using two clusters.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"13 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141119674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. S. Sitanggang, Novrini Hasti, R. F. Syafariani, Lusi Melian, Bondan Rachmat Santoso, Muhammad Daffa Shidiq, Jurnal Informatika
{"title":"Use of Ticketing System in Freelancing Platform to Maintaining Client Trust in Product Development Process","authors":"A. S. Sitanggang, Novrini Hasti, R. F. Syafariani, Lusi Melian, Bondan Rachmat Santoso, Muhammad Daffa Shidiq, Jurnal Informatika","doi":"10.15408/jti.v17i1.32228","DOIUrl":"https://doi.org/10.15408/jti.v17i1.32228","url":null,"abstract":"Micro, small, and medium enterprises (MSMEs) are considered to be one of the important components in the economic development of a country, especially Indonesia. However, it has been found that MSMEs are lagging in digitalization, the adoption of information technology, and digital marketing. An information system where MSMEs can have easy access to IT and digital marketing professionals can be a solution to boost and encourage digitalization among local MSMEs. Developing such an information system requires the project to be able to quickly adapt and change based on the user’s needs and current trends. This study proposes an incremental solution to building an accessible information system catered for MSMEs by incorporating the ADDIE model into the development cycle. To understand the feasibility of the system, several group meetings are arranged to demonstrate and try out the system’s capability to the target users. The results indicate that the system is generally able to fit the needs of MSMEs and is quite effective at connecting the MSESs to IT and Digital marketing resources and experts.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"71 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141121788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Teknologi Ground Plane Augmented Reality Pengenalan Daur Ulang Limbah","authors":"Erick Merpati, Virginia Tulenan, H. V. Kainde","doi":"10.35793/jti.v19i01.52037","DOIUrl":"https://doi.org/10.35793/jti.v19i01.52037","url":null,"abstract":"Waste is leftover material in an activity and/or production process. Excessive and unmanaged waste will cause environmental pollution. We can also feel environmental pollution in the environment around us. The government of course has tried to minimize the problem of waste which is the cause of environmental pollution. However, public awareness plays an important role in protecting the environment. Of the various ways that can be done to overcome the problem of accumulated waste, one of the things we can do is recycling. This research was made to introduce recycling. With the help of augmented reality technology, people can learn about waste recycling in a more efficient and interesting way. This Waste Recycling Introduction Application will be made using Unity and the Vuforia SDK, where one of Vuforia's features, namely the Ground Plane, allows users to place digital content on a horizontal surface in the surrounding environment, such as a floor or table. The development method that I use is the Multimedia Development Life Cycle. This research will produce an Augmented Reality application that introduces waste recycling which is expected to increase public awareness of recycling which can be done to reduce the impact of environmental pollution.","PeriodicalId":506287,"journal":{"name":"JURNAL TEKNIK INFORMATIKA","volume":"12 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139531127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}