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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
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Articles 9 Documents
 1 
Search results for , issue "Vol. 6 No. 1 (2023): August 2023" : 9 Documents clear
The Identification of Covid-19 Fake News Factors on Social Media in Indonesia Umi Chotijah; Nadya Husenti; Deni Sutaji; Angga Mahditya Indra Pratama
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.v6i1.6613

Abstract

Social media is a protocol for people’s interaction and disseminating new ideas. The spread of fake information can occur on social media because there is no control and verification from the legal account. During the COVID-19 corona virus outbreak, the government issued a self-isolation policy. However, people use social media to find information about COVID-19 and spread news about COVID-19 greedily, especially in Indonesia. Therefore, this study explores the factors influencing the spread of fake news related to COVID-19. The sampling used in this study was non-random/non-probability sampling with the Convenience Sampling technique, including two hundred and twenty-two respondences from several regions in Indonesia. These phenomenons are studied using the Uses and Gratification framework by eliminating entertainment variables, adding altruism motivation, and adding moderating variables for demographic factors of individual psychological well-being, including age, education, income, and gender. Data were analyzed using Smart Partial Least Squares (PLS) to determine the effect of five variables. The analysis results show that all the variables, e.g., altruism, socialization, time elapsed, information sharing, and information seeking, as well as moderating variables and demographic factors of individual psychological well-being have no positive and significant effect on the spread of fake COVID-19—news on social media in Indonesia.
The Essential Factors and Trend Development of IoT Smart Box Surjandy; Meyliana; Andreas Raharto Condrobimo; Henry Antonius Eka Widjaja; Wiedjaja Atmadja; Rudy Susanto; Bruno Sablan
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.v6i1.6794

Abstract

Boxes for drug storage are handy and essential and play a role in helping the healing process and support maintaining patient health regularly for a long time. SmartBox is not a new thing, but because of its importance, it, SmartBox continues to be developed to date according to the needs needed. In previous research, the formation of SmartBox was only for particular things. This study tries to unify the 17 papers obtained with the help of a publish and perish application which is then carried out a literature review and using the VosViewer application to get an overview of trend development and the essential factors or aspects in the formation of SmartBox and its development. In addition to getting the trend of SmartBox development, this research also finds seven essential factors that will be useful for Smartbox development. With this research, it hopes that it will facilitate the development of SmartBox in the future.
System Dynamic Analysis of the Fleet Availability and Reliability Influence on the Lead Time of the Delivery Order Process Theresia Liris Windyaningrum; Chatarina Dian Indrawati; Zalizah Awang Long; Vinsensius Widdy Tri Prasetyo; Lorensius Anang Setiyo Waloyo; Petrus Setya Murdapa
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.v6i1.7049

Abstract

The inventory replenishment process in the warehouse becomes difficult if there is uncertainty. It can cause warehouse performance not to be as expected. The warehouse is an important part of the supply chain subsystem, which smooths the flow of goods from upstream to downstream throughout the system. This paper uses system dynamics modeling to analyze the replenishment of raw materials where there is randomness in availability and reliability and their effects on the delivery lead time of the fleet. The model obtained is much simpler but more robust when compared to the analytical-mathematical model or the discrete-events simulation. Tests on the model show that the model can behave as it should logically. Several experiments were conducted to see how fleet availability's reliability can affect the delay in receiving or delivery lead time. One interesting thing revealed is that reliability does not have to be 100%, but there is a certain minimum threshold for the system to perform well. This is different from availability, which must be 100%.
An Examination of the Human Factors in Cybersecurity: Future Direction for Nigerian Banks George Ajufo; Abubaker Qutieshat
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.v6i1.7278

Abstract

Information and communication technology has become necessary for conducting business operations and ensuring business survival in Nigerian banks. However, this has come with some encumbrances, as this technology is vulnerable to attacks due to technical or human factors. These human factors have been very challenging for organizations due to their multi-dimensional nature and the fact that humans have been responsible for most cybersecurity incidents. Resolving issues arising from cybersecurity incidents is expensive and time-consuming. Therefore, this study is crucial as it will enable Nigerian banks witnessing increased attacks to take preventive measures and reduce the enormous expenditure required for remediation. This study adopts a literature review approach, reviewing previous studies on human factors in cybersecurity to determine the factors responsible for successful cyber-attacks and their suggested mitigations. The findings categorize these human factors into social engineering, poor information security culture, risky password practices, stress, burnout, and security fatigue. The study presents mitigations but notes that training and cybersecurity awareness are the most common reoccurring pre-emptive actions recommended. This research is significant as very little prior research has been conducted in this area targeted at the Nigerian banking sector. Practically, the findings of this study are expected to point Nigerian banks toward the critical human factors that they need to concentrate on to minimize the success rate of cyber-attacks and reduce the associated costs of recovering from these attacks.
Mobile Payment Adoption in Generation Z Using Extended Unified Technology Acceptance and Use of Technology Erick Ahmad Fahmi Alfa'izy; Edwin Pramana; Gunawan
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.v6i1.7340

Abstract

This study investigates the possible factors determining the success of m-payment adoption in Generation Z using the basic Unified Technology Acceptance and Use of Technology (UTAUT) model based on previous research. A theoretical model derived from previous research that combines factors from the acceptance model of UTAUT with relevant m-payment factors (Trust, Perceived Security, Network Externalities). The sample includes 735 participants from three cities in Indonesia. Structural equation models are used to analyze and develop theoretical models. Only four hypotheses can be accepted based on the analysis of the seven hypotheses proposed. Trust, Perceived Security, Performance Expectancy, and Social Influence positively and significantly impact Behavioral Intention. Meanwhile, Facilitating Conditions, Effort Expectancy, and Network Externalities are insignificant to Behavioral Intention. There are many research models for adopting m-payments, but in developing countries, including Indonesia, the cellular penetration rate is already very high. However, the acceptance of m-payments in various trade transactions is still embryonic, especially in Generation Z. Therefore, this research presents a comprehensive investigation of the factors that influence the adoption of m-payments in Generation Z in Indonesia.
User Acceptance for Multitask IoT Monitoring and Controlling System for Salt Ponds Tri Raharjo Yudantoro; Busra Nur Hamida; Eka Febriyanti; Wiktasari Wiktasari; Suko Tyas Pernanda; Anton Satria Prabuwono
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.v6i1.7479

Abstract

The process of making salt is still done manually by filling water into reservoirs and plots which require salt farmers to visit their farms periodically. This is mainly because the speed of the salt crystalization process is always inconsistent due to salt concentration in seawater and the weather. This study aims to build a new prototype of a water level monitoring system in reservoirs and plots in salt ponds then measure the water's salinity value, which will be reported to the farmers. The method used in this research is prototyping, which includes system requirement analysis, rapid design, prototype building, system evaluation, and system  improvement. The system was tested using the black box method, namely testing all system functionality and determining user satisfaction with questionnaires. The functionality test results, including monitoring the water level and the pump control, show that the prototype functions correctly. The designed system can send information in the form of water level values in reservoirs, water levels in plots, and salinity values with linear sensor accuracy with measurement results with conventional measuring instruments with standard error values of 0.485, 0.44, and 0.72, respectively. Applying this system will ease farmers’ monitoring of water levels and controlling irrigation in reservoirs and plots.
Heart Rate and Body Temperature Tracking Application Based on Fuzzy Logic Afandi Nur Aziz Thohari; Angga Wahyu Wibowo; Aisyatul Karima; Idhawati Hestiningsih; Kuwat Santoso; Faizal Abdollah
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.v6i1.7481

Abstract

Temperature and heart rate are indicators of health. It is necessary to monitor heart rate and body temperature to prevent the spread of a virus or disease. In most cases, heart rate and body temperature are monitored independently, and the patient cannot view a record of previous examinations. This study uses fuzzy logic to develop an application for monitoring heart rate and body temperature. It can monitor heart rate and body temperature in real-time, store a history of previous examinations, and use fuzzy logic to diagnose body conditions based on heart rate and body temperature data. Based on test results, the sensor reading error rate for heart rate is minimal at 0.68 and for body temperature at 0.18. The accuracy of fuzzy diagnosis of the patient's body condition is one hundred percent. The performance indicator for the application is excellent, the completion rate is 100 percent, and the time-based efficiency is 93%. The results of the user satisfaction test indicate that most users are pleased with the application's usability. The average value for measuring user satisfaction is 80%, with the highest result of the five measurement criteria being 89.6% for the ease-of-use criterion.
SVM-PSO Algorithm for Tweet Sentiment Analysis #BesokSenin Anggita Dewi Novia Wardhani Susanto; 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.
Intelligent Prediction and Detection of Diabetes Mellitus Using Machine Learning Slamet Handoko; Sukamto; Liliek Triyono; Idhawati Hestiningsih; Eri Sato-Shimokarawa; Eri Eli Lavindi
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

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