cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Hapnes Toba
Contact Email
hapnestoba@it.maranatha.edu
Phone
+6222-2012186
Journal Mail Official
hapnestoba@it.maranatha.edu
Editorial Address
Fakultas Teknologi dan Rekayasa Cerdas Universitas Kristen Maranatha Jl. Prof. Drg. Suria Sumantri No. 65 Bandung
Location
Kota bandung,
Jawa barat
INDONESIA
JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Published by Universitas Kristen Maranatha
ISSN : 24432210     EISSN : 24432229     DOI : https://doi.org/10.28932/jutisi
Core Subject : Science,
Computer Science & IT
Paper topics that can be included in JuTISI are as follows, but are not limited to: • Artificial Intelligence • Business Intelligence • Cloud & Grid Computing • Computer Networking & Security • Data Analytics • Datawarehouse & Datamining • Decision Support System • E-Systems (E-Gov, E-Health, E-Commerce, etc.) • Enterprise System (SCM, ERP, CRM) • Human-Computer Interaction • Image Processing • Information Retrieval • Information System • Information System Audit • Enterprise Architecture • Knowledge Management • Machine Learning • Mobile Computing & Application • Multimedia System • Open Source System & Technology • Semantic Web & Web 2.0
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 479 Documents
 36   37   38   39   40 
Perancangan User Interface dan User Experience Sistem Informasi E-learning Menggunakan Design Thinking Devi Karlina; Dwi Rosa Indah
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5412

Abstract

The COVID-19 pandemic has caused various activities to be shifted online, one of which is learning activities at school. Because they don't have their own e-learning information system, online learning activities at SMA Tunas Bangsa Palembang utilize various media such as Classrooms to create classes, Google Forms to fill absences, and YouTube to deliver material. Lots of media and there are still perceived shortcomings related to the features of the media used cause the implementation of learning activities become less effective and efficient. Thus, to provide comfort and convenience in these learning activities, an e-learning information system user interface and user experience (UI/UX) design is required. This study uses design thinking as a method that has 5 stages, starting with problem exploration (empathize) to testing the solution design prototype (test). Prototype testing is carried out using the usability testing method, using task scenarios and the System Usability Scale (SUS) and User Experience Questionnaire (UEQ) questionnaires. The results of usability testing using SUS task scenarios and questionnaires include aspects of learnability and efficiency of teacher and student user groups, namely 100% and 0.04 goals/sec, for teacher user satisfaction aspects is 93 with grade scale "A" and for student users is 85 with a grade scale of “B”, the UEQ assessment scores for the two user groups were above 2.0 in all rating categories namely “Attractives”, “Perspicuity”, “Efficiency”, “Dependability”, “Stimulation”, “Novelty”. So, it can be concluded that the e-learning prototype design has had a good user experience.
Serverless Named Entity Recognition untuk Teks Instruksional Pertanian Kota Trisna Gelar; Aprianti Nanda; Akhmad Bakhrun
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5447

Abstract

The evolution of document documentation, classification, and information retrieval includes named entity recognition (NER). The implementation of NER in the agricultural domain, in particular instructional texts or transcriptions of tutorial videos, will make it easier for the general public to understand the specific concepts and terms of urban agricultural activities such as crop production processes and procedures, agricultural methods and tools, harvest cycles, and handling plant pests or diseases. Spacy is an NLP tool, has two methods of developing NER models, namely with Toc2Vec and Transformer. Both methods have advantages and disadvantages, namely different sizes, performance and prediction speeds according to needs. The NER model can be implemented into a Serverless application, using the Functional as Services (FaaS) and Backend as Services (BaaS) approaches. For the subtopic of cultivating fruit crops in agricultural instructional literature, three NER models have been built in this study. First, the IndoBERT-based model, the Toc2Vec-based model with efficiency optimization, and the Toc2Vec-based model with accuracy optimization. The most efficient toc2vec model, with a f1-score of 0.71, is followed by the effective toc2vec model, with a f1-score of 0.60. The COUNT, PERIOD, and VERIETAS entities are consistently predicted incorrectly by the Toc2Vec model, which is unable to forecast numeric entities well. In addition, the Toc2Vec Model's better efficiency optimization directly relates the size of the model to the speed of word prediction per second, and the model is simple to integrate into a FaaS- and BaaS-based Serverless. The capabilities of Serverless M have been successfully tested using the black box method.
Optimasi Prakiraan Cuaca Menggunakan Metode Ensemble pada Naïve Bayes dan C4.5 Vini Indri Yani; Aradea Aradea; Husni Mubarok
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5455

Abstract

Weather forecasting is important for the survival of the wider community. Therefore, the accuracy of the weather forecast must be high. Based on this, a study was conducted to improve the accuracy of weather forecasting with the naïve Bayes and C4.5 models and then performed an optimization using the ensemble method. The dataset used is weather data observed from BMKG Bandung for 10 years. Accuracy in the pretest process shows that the naïve Bayes algorithm has an accuracy of 49.45% and the C4.5 algorithm produces 41.24% accuracy, while in the posttest process the accuracy obtained is 49.76% for bagging naïve Bayes, 46.47% for boosting naïve Bayes, 45.76 for bagging C4.5 and 38.82% for C4.5.
Optimasi Konten Pemasaran dan Platform Online dengan Teknik Search Engine Optimization Mahadir Muhamad Erfin; Rifqi Mufiddin; Syahiduz Zaman
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5468

Abstract

Running a business just doing production is not enough but must do optimal product marketing. Business actors who market their products through conventional marketing will be unable to compete with other entrepreneurs who market their products through online platforms because online platforms are now widely found via the internet. Conventional product marketing is done because they do not understand the right optimization techniques in product marketing, especially in marketing content optimization strategies and the use of online platforms. Optimization of content marketing and online platforms requires a technique known as SEO or Search Engine Optimization. This technique is used to help optimize marketing precisely in determining content and showing product content in internet searches through online platforms. Product content and optimized online platforms will provide a great help in product marketing. This study aims to explain marketing content optimization strategies and online platform settings so that they can display shrimp cracker product content posts on the search page. The results of this study are able to optimize the marketing content of the right shrimp cracker products and display product keyword search results on internet search pages through the online platforms Tumblr, TribunJualBeli, and Carousell.
Implementasi Algoritma $P Point Cloud Recognizer pada Pengenalan Angka Berbasis Game Muhammad Farid Athar; Yohannes Yohannes; Yoannita Yoannita
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5472

Abstract

More devices use gestures as their input method. Recognizing these gestures becomes more important for app development. One of the methods used for gesture recognition is Point Cloud Recognizer or $P. Gesture recognition can be used to recognize written characters like numbers or letters. Result of this recognition can be used for education involving apps, like games. This study is done by implementing $P in games to show that $P can be used as one of the methods for gesture recognition when developing games that need such features. In this study $P is implemented with the help of the game engine Unity with C# programming language. 3 sets of numerals 1 to 10 are used as data with $P configured to use 32 points. Total of 100 tests are done in the game resulting in 99% accuracy, showing $P is able to recognize the gesture well.
Analisis Klasifikasi Sentimen Terhadap Isu Kebocoran Data Kartu Identitas Ponsel di Twitter Muh Ichlasul Amal; Elsa Syafira Rahmasita; Edward Suryaputra; Nur Aini Rakhmawati
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5483

Abstract

Technology developments bring great threats related to privacy and security of personal data. In September 2022, a data leak incident of 1.3 billion SIM card registration data containing user's personal data was uploaded on dark web. Indonesian people voice their opinion regarding this issue on Twitter. This study aims to find out the word distribution and sentiment classification analysis of public opinion on Twitter related to the issue. Sentiment classification analysis was carried out using a machine learning approach with four methods, namely Random Forest, Logistic Regression, Support-Vector Machine, and IndoBERT model. The four methods will be compared to see which model produces the best performance. From the crawling process, 957 tweets were obtained, of which 609 were labeled and trained using the four methods. From the data obtained, there is an imbalance between classes, where positive sentiment has a much smaller number than the rest. Some words that are often used in the tweet are SIM card, data SIM, bocor data, miliar data, and kominfo. The results of the model show that the Support-Vector Machine has the best performance with an f1-score of 0.81, followed by Random Forest of 0.78, IndoBERT of 0.76, and Logistic Regression of 0.74. Class imbalance and lack of training data make IndoBERT's performance lower when compared to other algorithms. The results of this study can be used by the authorities to evaluate policies in dealing with data security issues by listening to opinions from the Indonesian people.
Model Convolutional Neural Network untuk Mengukur Kepuasan Pelanggan Berdasarkan Ekspresi Wajah Daru Prasetyawan; Rahmadhan Gatra
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5493

Abstract

Customer satisfaction shows how well the product or service of an organization meets customer expectations. Customers' facial expressions can show their satisfaction with the services provided. Convolution Neural Network (CNN) is a type of neural network algorithm that can be used to recognize an object in an image. CNN utilizes the convolution process to determine and distinguish an object in the image from other objects such as to recognize various facial expressions. This study aims to measure customer satisfaction by utilizing the CNN model by recognizing any changes in facial expressions. From the results of the CNN model training, an accuracy of 90.57% was obtained. Furthermore, the formed model is implemented into a web-based system that records facial expressions and performs a classification (satisfied or dissatisfied) on any detected facial changes. The most dominant expression is the result of measuring customer satisfaction.
Pengembangan Sistem Alumni dengan Informasi Lowongan Pekerjaan Daniel Jahja Surjawan; Meliana Christianti Johan; Dinda Ayu Febriani
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5554

Abstract

The Faculty of Information Technology, Maranatha Christian University or known as FIT-UK Maranatha has produced many alumni since its establishment in 2002. The recording of alumni data is currently not well managed where the data collected by the faculty is based on the latest information provided by alumni before final presentation or graduate briefing events. It is the hope of the faculty to have a special website-based application that can accommodate alumni data so that the faculty can still communicate with alumni and fellow alumni, while also getting the latest information related to current industry needs. This research will create a web-based application where the application can record alumni data, friendships between alumni, record the data of open job vacancies at the company where alumni work that can be seen by other alumni. The website will be made using the PHP programming language and the Laravel framework, for data storage will use mySQL.  
Pengukuran Layanan Sistem Informasi Akademik menggunakan Service Intelligence dan Control the Processing of Information Adelia Adelia; Diana Trivena Yulianti; Tiur Gantini; Remaydo Timothy Gultom
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5579

Abstract

The development and use of information technology today cannot be avoided by most organizations, including one of the universities in Bandung. Universities have utilized information technology to support processes and activities that occur within universities, especially academic processes. Processes related to academics are supported by a new academic information system that has just been implemented, to complement the previous academic information system. In addition to the use of information technology at the university, information technology services are also an important part so that information technology can be provided according to user needs and affect user satisfaction. Analysis of the management of academic information system services needs to be done to find out services related to academic information systems and information systems according to user needs and can provide satisfaction to users, especially in the academic field. The analysis was carried out using the criteria on service intelligence and COBIT 5.0 DSS06.02 control the processing of information.
Visualisasi Skyline Query untuk Distribusi Tenaga Kesehatan COVID-19 Vega Purwayoga; Muhammad Al Husaini; Hen Hen Lukmana
Jurnal Teknik Informatika dan Sistem Informasi Vol 9 No 1 (2023): JuTISI (in progress)
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v9i1.5624

Abstract

The use of health workers in areas with minimal risk can be a solution to help areas with a high risk of spreading COVID-19. Selection of low risk areas can be done by measuring the level of risk in an area. One solution is to use the skyline query algorithm. Skyline query is able to recommend which areas are potential to serve as supporting areas for health workers. Skyline query is able to produce a recommendation model for determining the supporting area for health workers, however, in the process of reading the information, it is necessary to extract the information. Extraction is carried out by developing a system for visualizing the skyline query as a recommendation system for health personnel assistance. This study develops a visualization system using a hybrid approach, which combines the Rapid GIS Development Cycle (RGDC) and Navigational Development Techniques (NDT) methods. The system was developed using R and the shiny library, ggplot2, rpref and leaflets. The system can work as expected, such as displaying a map of the recommended area to become a supporting area, visualizing data with ggplots and visualizing dominance testing on the skyline query.

Page 38 of 48 | Total Record : 479

 36   37   38   39   40 

Filter by Year

2015 2025


Reset
Filter By Issues
All Issue Vol 11 No 3 (2025): JuTISI Vol 11 No 2 (2025): JuTISI Vol 11 No 1 (2025): JuTISI Vol 10 No 3 (2024): JuTISI Vol 10 No 2 (2024): JuTISI Vol 10 No 1 (2024): JuTISI Vol 9 No 3 (2023): JuTISI Vol 9 No 2 (2023): JuTISI Vol 9 No 1 (2023): JuTISI (in progress) Vol 8 No 3 (2022): JuTISI Vol 8 No 2 (2022): JuTISI Vol 8 No 1 (2022): JuTISI Vol 7 No 3 (2021): JuTISI Vol 7 No 2 (2021): JuTISI Vol 7 No 1 (2021): JuTISI Vol 6 No 3 (2020): JuTISI Vol 6 No 2 (2020): JuTISI Vol 6 No 1 (2020): JuTISI Vol 5 No 3 (2019): JuTISI Vol 5 No 2 (2019): JuTISI Vol 5 No 1 (2019): JuTISI Vol 4 No 3 (2018): JuTISI Vol 4 No 2 (2018): JuTISI Vol 4 No 1 (2018): JuTISI Vol 3 No 3 (2017): JuTISI Vol 3 No 2 (2017): JuTISI Vol 3 No 1 (2017): JuTISI Vol 2 No 3 (2016): JuTISI Vol 2 No 2 (2016): JuTISI Vol 2 No 1 (2016): JuTISI Vol 1 No 3 (2015): JuTISI Vol 1 No 2 (2015): JuTISI Vol 1 No 1 (2015): JuTISI More Issue