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INDONESIA
Indonesian Journal of Information System
Published by Universitas Atma Jaya Yogyakarta
ISSN : 26230119     EISSN : 26232308     DOI : -
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 192 Documents
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SVM-PSO Algorithm for Tweet Sentiment Analysis #BesokSenin Susanto, Anggita Dewi Novia Wardhani; Hari Suparwito
Indonesian Journal of Information Systems Vol. 6 No. 1 (2023): August 2023
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i1.7551

Abstract

The hashtag #BesokSenin is a hashtag that is often trending on Indonesian Twitter on Sunday evenings. Many Indonesian Twitter users expressed their feelings about welcoming Monday using the hashtag #BesokSenin. The tweet containing #BesokSenin is known to be a motivational sentence to welcome Monday full of joy or a disappointed sentence because you have to return to your routine after taking a holiday on Saturday and Sunday. This study conducts sentiment analysis to find out the opinions of netizens on welcoming Mondays. The tweet data used is tweet data with the hashtag #BesokSenin and the keywords school, work, assignments, and college. The classification method used is the Support Vector Machine algorithm, which is optimized using the Particle Swarm Optimization method to optimize the performance of the Support Vector Machine algorithm. Results of 80% accuracy were obtained by applying the Support Vector Machine model based on Particle Swarm Optimization. This accuracy is superior to 1% compared to the results of accuracy using the usual Support Vector Machine model, which equals 79%. This shows that Particle Swarm  Optimization can optimize the accuracy of the Support Vector Machine algorithm.
The Addition of Adaboost to The Use of The C4.5 Algorithm to Improve The Accuracy of Classification of Study Interests Fahriah, Sirli; Nur Diyana Kamarudin; Liliek Triyono; Adhy Rizaldy
Indonesian Journal of Information Systems Vol. 6 No. 2 (2024): February 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i2.7588

Abstract

Specialization is one of the important things in focusing the student's field of study. At one university that has a faculty of computer science, there is an Informatics Engineering undergraduate study program which is divided into two specializations, namely intelligent systems and software engineering design. At one university that has a faculty of computer science, there is a bachelor's program in Informatics Engineering which is divided into two specializations, namely intelligent systems and software engineering design. students find it difficult to choose one of the specializations in the informatics engineering study program. To overcome these problems, the authors provide solutions in the form of ideas that can recommend students in determining specialization. In this problem, the algorithm that will be used is the C4.5 algorithm based on forward selection plus adaboost. The results of the specialization classification use the selected attributes and iterate over the cross-validation so as to produce the right accuracy. Testing the C4.5 algorithm produces an accuracy of 93.89% and the C4.5 algorithm based on forward selection produces an accuracy of 94.44% while using the C4.5 algorithm based on forward selection with the addition of adaboost produces an accuracy of 94.63%. Based on these tests, it proves that there is an increase in accuracy by adding selection and adaboost features to the C4.5 algorithm.
Intelligent Prediction and Detection of Diabetes Mellitus Using Machine Learning Handoko, Slamet; Sukamto; Triyono, Liliek; Hestiningsih, Idhawati; Sato-Shimokarawa, Eri; Lavindi, Eri Eli
Indonesian Journal of Information Systems Vol. 6 No. 1 (2023): August 2023
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i1.7602

Abstract

One of the diseases with a fairly high number of sufferers today is Diabetes Mellitus. The increase in the number of people with diabetes is caused by delays in diagnosis and also difficulties in monitoring the blood sugar level. Therefore, a solution is needed to overcome this problem, namely a blood sugar level monitoring system to predict and detect. The blood sugar level monitoring system is an intelligent system that can monitor blood sugar levels in Diabetes Mellitus patients. This system aims to make it easier for patients to check blood sugar levels regularly, to minimize the occurrence of increased blood sugar levels that aggravate the disease. Moreover, machine learning algorithms are a viable method used in recent studies for analyzing, predicting, and classifying health data while improving the health conditions of telemonitoring and telediagnosis. The main purpose of this article is to employ machine learning algorithms for blood sugar level classification in real time. The results of this study indicate that the system can be used to monitor blood sugar levels. The results of the implementation of the system that can be used by users include monitoring the results of measuring blood sugar levels. Keywords: Monitoring Machine Learning, Prediction, Diabetes Mellitus, Data Mining
Clinician Acceptance and Adoption of PACS in Radiology Services: An Exploratory Study Alhur, Anas
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.7614

Abstract

This exploratory study explores the acceptance and adoption of Picture Archiving and Communication Systems (PACS) among clinicians practicing radiology services in Hail City, Kingdom of Saudi Arabia. A survey was conducted with 142 clinicians from various specialties from four public hospitals located there and focused on clinician satisfaction with inpatient and outpatient services as well as perceptions about PACS usage as well as the overall impression of radiology services; data analysis included descriptive statistics. Findings show high levels of patient satisfaction with waiting times for investigations in both inpatient and outpatient settings; Radiology staff were perceived as approachable and willing to discuss clinical information with participants, PACS usage was highly rated by clinicians for viewing reports and images, participants reported high satisfaction with image quality, reliability and ease of use; and PACS was seen to shorten reporting speeds as well as waiting times. Correlations were observed between clinician age, approachability of radiology staff, speed of reporting, wait time for investigations and overall satisfaction with PACS use in radiology practice, adoption rates and satisfaction levels of users; continuous improvements to efficiency and service awareness, as well as improvements to adoption rates, are key components to increasing adoption rates and satisfaction levels among healthcare institutions and radiology practitioners alike. Future research could include patient perspectives to gain a holistic view of its impact on overall healthcare experiences.
Academic Factors Influencing Students Career Choices in the IT Field: Insights from South African IT Students Ndovela, Sithembile; Mutanga, Bethel
Indonesian Journal of Information Systems Vol. 6 No. 2 (2024): February 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i2.8293

Abstract

Effective career decision-making is pivotal for students, influencing their prospects and employability. This study delves into the nuanced relationship between academic factors and career choices among Information Technology (IT) students. While existing literature acknowledges the broad impact of academic performance on career decisions, limited research explores this dynamic within the context of South African universities. This research employs a comprehensive mixed-methods approach, examining the influence of educational experience, mentorship, access to resources, and institutional support on students' academic performance and subsequent career choices. Through statistical analysis and qualitative interviews, the study unveils unique insights into the interconnected effects of these factors on IT career pursuits. The findings bear significance for educators, career counselors, policymakers, and industry stakeholders. By understanding the multifaceted elements shaping academic performance and career decisions, institutions can tailor support programs, refine curricula, and nurture holistic student development. Employers stand to gain insights into the attributes of high-performing individuals, aiding talent management and recruitment. For IT students, this research provides a profound exploration of the intricate links between academic performance, career choices, and outcomes, contributing to the broader discourse on workforce development and the future of the IT sector.
Preserving Meher and Woirata Corpus Languages using Neural Machine Translation Prabowo, Yulius; Gabriel, Marthen; Nazarudin; Ratumanan, Tanwey; Maslim, Martinus
Indonesian Journal of Information Systems Vol. 6 No. 2 (2024): February 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i2.8542

Abstract

Research on languages, particularly regional languages, is extremely challenging to conduct because there is very little or no language corpus available, particularly for Indonesia's regional languages. This project seeks to construct a translation machine for Indonesian in Meher and Woirata languages, and vice versa. However, to be able to achieve this, a corpus of Meher and Woirata languages must first be developed. The production of this corpus was carried out through field studies, the researcher requested various speakers of this language to translate manually and then compared the results from several translators through focus group talks to identify the appropriate use of words. The outcomes of this translation process are then written in the form of a database of Indonesian-Meher and Indonesian-Woirata language pairings which will subsequently be utilized as a learning database for the translation machine that will be created. This research succeeded in collecting 714.000 words in the Meher language and 805.000 words in the Woirata language. These results were then employed as a machine translation learning corpus, the output of the translation carried out by this machine was then validated through direct assessment by speakers of the two languages. The results of this testing indicated an accuracy above 80% for both translation into the Meher language and translation into the Woirata language. From the research carried out, it can be concluded that the construction of the Meher language corpus and the Woirata language corpus which was carried out through field research was successful in gathering and establishing a language corpus for these two languages. Apart from that, the experimental results suggest that the employment of translation algorithms to convert Indonesian into regional languages and vice versa may be carried out and provide translations with acceptable accuracy. The contribution of this research is in the establishment of the Meher and Woirata language corpus so that it can be generally accessed by anyone who requires it.
Business Process Reengineering to Improve Supply Chain Management at Batik Semarang 16 Through Implementation of ERP Odoo Bayu Setyo Nugroho; Sri Marhaeni Salsiyah; Sugiyanta; Anandike Cita Kumala; Idha Rizqi Pratiwi; Ranira Salma Edza Fabillah; Arumsari, Vita
Indonesian Journal of Information Systems Vol. 6 No. 2 (2024): February 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i2.8599

Abstract

This study aims to design an improvement in the Supply Chain Management using the ERP Odoo application. This research starts from conducting field studies on the research object, designing the required system, prototyping, testing, and implementation. The methodology used is RND Borg and Gall Method approach to reach the right model in making business models for reengineering ERP implementation in small and medium enterprises. As a result, the business processes create using Odoo, is way more efficient because all business activities can be integrated with each other so that there is an automation of changing the working status of the product so there is no need to check manually. Finally, testing has been done to see how well the system is.
Online Banking User Experience: A User Experience Questionnaire (UEQ) Assessment in South Africa Mujinga, Mathias
Indonesian Journal of Information Systems Vol. 6 No. 2 (2024): February 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v6i2.8606

Abstract

Online banking has seen tremendous growth driven by the emergence of the fourth industrial (4IR) and innovative technologies in every aspect of our daily activities. Hence, there is an emergence of areas of research around aspects of online banking, such as the need for user experience. This paper evaluates online banking user experience (UX) using the user experience questionnaire (UEQ). The study collected 725 survey responses from UEQ in South Africa, and the findings show a high quality of UX based on a comparison against the UEQ benchmark data set. More specifically, the hedonic quality scale aspect is at the highest level compared to the pragmatic quality aspects of UX. The findings provide practical contributions to online banking designers and developers in retail banks to optimise areas of strength and improve on those aspects that need improvements.
Handwritten Digital Signatures Accuracy Enhancement Comparison on Android-Based Mobile Application Systems Rohajawati, Siti; Ismail , Aditya; Gunawan, Irwan Prasetya; Sitorus, Brian Arnesto
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.8641

Abstract

The research reported in this paper aimed to improve the quality, size ratio, and storage size of Digital Signatures (DS) used in the e-form Fumida app, a mobile application employed by PT Fumida Pestindo Jaya (Fumida) pest control, termite control, and fumigation services for data collection and verification. The application was developed using MADLC method for research and development of mobile application and utilized as a replacement for paper media used to fill in data related to work with the DS feature (e-signature), from which verification/authentication of the work results carried out by Fumida to its clients is given. The original DS, while replacing paper forms, suffered quality and accuracy loss when resized for printing, prompting the investigation of three methods to enhance their integrity. This process was subsequently examined using a questionnaire with the help of 22 respondents and calculation of questionnaire data. The results of our study showed that our model 3 emerged as the most effective solution, maintaining high image quality and accuracy even when resized.
Sentiment Analysis of Customer Review Using Classification Algorithms and SMOTE for Handling Imbalanced Class Sediatmoko, Nur Siradj; Nataliani, Yessica; Suryady, Irwan
Indonesian Journal of Information Systems Vol. 7 No. 1 (2024): August 2024
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v7i1.8879

Abstract

Ralali.com is a B2B e-commerce platform that offers various brands across categories ranging from automotive to building materials. The Play Store is a tool for downloading applications used by many people. This research aims to compare and find the best model among Naïve Bayes (NB), Support Vector Machine (SVM), and k-Nearest Neighbor (k-NN) in classifying the sentiment reviews of Ralali.com's application on the Play Store, and analyze the negative labels to provide recommendations for Ralali.com developers. Based on the research results, the NB Algorithm stands out as the best choice compared to SVM and k-NN in addressing class imbalance. The use of SMOTE generally improves the model performance on minority classes for Precision, Recall, and F-Measure, although there are still challenges related to the lower Accuracy compared to the use of non-SMOTE.

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