Jurnal Ilmiah Informatika

Journal Information
ISSN / EISSN : 2549-7480 / 2549-6301
Published by: LP2M Universitas Ibrahimy (10.35316)
Total articles ≅ 96
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Annisaa Sri Indrawanti, Muchammad Husni, Khakim Ghozali
Published: 30 June 2022
Abstract:
Patients who contract the disease should avoid contact with other people. One way to do this is to self-isolate at home. The family of the patient who cares for the activities that are carried out in self-isolation to find out the condition of the patient's condition, his condition is improving or deteriorating. To avoid direct contact, the patient's activity, independently, can be monitored by remotely predicting changes in patient activity using an Internet of Things-based remote monitoring system for self-isolating patient activities. This cellular-based monitoring system uses an accelerometer sensor to retrieve data on changes in patient activity and analyzes the effect of several variations in the number of data samples and sliding-windows on the accuracy of the system in predicting changes in patient activity. Variations in the number of N samples tested were 4,6,8,10,20,30,40,50,60,70,80,90 and 100 samples, while the sliding-window N variation tested was 1 ,2,3,4,5,6,7,8,9 and 10 samples where there is a change in activity every 30 seconds for 330 seconds (10 changes in activity) for each number of N samples and N sliding windows. The results shown are N sample data = 6 providing the highest activity change prediction accuracy, amounting to 90.15%, while N sliding window data = 6 providing the highest activity change prediction accuracy, amounting to 92.72%.
Sukirman Sukirman
Published: 30 June 2022
Abstract:
Obstacles in the learning process carried out by subject teachers and students of SMA Chandra Kusuma School, North Jakarta, because document storage is still low and internet access is still slow. Multiple linear regression algorithm to determine the relationship between cloud computing variables and the learning process on document storage variables. Simultaneously the F test results are 15.387 and the coefficient of determination is 36.30% so that there is a significant relationship between cloud computing and the learning process for document storage. Partially, cloud computing for document storage has a significant relationship because it has a t-value of 3.211 which is greater than t-table. And partially the learning process for document storage there is a significant relationship because it has a t-count value of 3.824 which is greater than t-table.
Annisa Nurba Iffah’Da, Anita Desiani
Published: 30 June 2022
Abstract:
Primary biliary cirrhosis is a chronic cholestatic liver disease that can lead to liver failure. The majority of individuals who suffer from this disease are women. Primary biliary cirrhosis is recorded as contributing to mortality worldwide with a percentage of 0.6% to 2.0%. However, so far, randomized trials have shown that some immunosuppressant or immunosuppressive drugs do not play a major role in patients with primary biliary cirrhosis. Therefore, early detection is important to start treatment and planning for appropriate medical needs. The results of the processing accuracy with the K-NN algorithm of 76.2% and the SLP algorithm of 63% using the Percentage Split method show that the K-NN algorithm is better for early detection of primary biliary cirrhosis. The K-Nearest Neighbor algorithm is able to perform early detection of primary biliary cirrhosis with a precision of 77% and recall of 75% with the hope that the percentage of mortality worldwide can decrease. However, the K-NN algorithm is not superior in retrieving information in patients with primary biliary cirrhosis. On the other hand, the SLP algorithm is superior in retrieving information in patients with primary biliary cirrhosis with a recall value of 65%.
Bella Putri Hapsari, Saifur Rohman Cholil
Published: 30 June 2022
Abstract:
In the current era of technology, computers are used to help facilitate human work. Among them by making a Decision Support System, by using a computerized system, the decision-making process can be right on target and more efficient. This research was conducted against the background of the need to give bonuses to employees, this bonus is given so that employees feel valued by giving rewards or additions for their good performance. In addition, the provision of employee bonuses also aims to increase employee morale so that employees provide better performance results, which can have a good impact on customer satisfaction. This study uses the MOORA method with the results obtained in the form of ranking the calculation of the value of employees who meet the criteria will receive bonuses. By using this decision support system, it is hoped that it will facilitate the decision making of employee bonus recipients.
Kurniyatul Ainiyah, Khadijah Fahmi Hayati Holle
Published: 30 June 2022
Abstract:
Regulation of the Minister of Education, Culture, Research, and Technology (Permendikbud Ristek) Number 30 of 2021 was launched as a form of government efforts in the context of preventing and handling sexual violence in universities. However, it turns out that this regulation has generated various reactions from the community, most of them support it while others reject the ratification of this regulation. Technological developments that occur today encourage people to write their opinions on social media, one of which is Twitter. Tweets discussing this rule can be used to gauge public sentiment. However, considering the number of tweets, the classification process will be difficult to do manually, so it requires a computational system that can automatically classify the sentiments of the existing tweets. From these problems, a system is designed to perform sentiment analysis using the lexicon-based method and Multinomial Naïve Bayes. The results of this sentiment measurement can be useful as data analysis material for the Ministry of Education and Culture, Research and Technology in making decisions regarding this rule. The purpose of this research is to measure the value of accuracy, precision, recall, and f-measure in sentiment analysis using lexicon-based and Multinomial Naïve Bayes methods. The measurement results obtained using a dataset of 470 data are the accuracy value of 71.28%, precision of 70.10%, recall of 78%, and f-measure value of 74.29%.
Lailatul Fadilah, Fadillah Siva, Muhammad Zaim Maulana, Muhammad Ainul Yaqin
Published: 30 June 2022
Abstract:
Laying hens are all activities related to the production of laying hens from the chick stage to the adult stage. The business process of laying hens in general starts from the activities of the biosecurity system, breeding, rearing, housing, and the animal feed and health system. Based on three studies that have been carried out in the period 2017-2021, the business process of laying hens is still minimally modeled. The problem that arises when the laying hen's farm business process is not modeled is that many business activities are repeated and missed. Therefore, business process modeling needs to be done to improve coordination between process units. This research aims to model the business process of laying hens, which refers to Porter's value chain analysis. This study uses data taken from observations and interviews with local laying hens in Malang. The data used is related to details of business activities, the parties involved, and SOPs in the laying hens business. The method in this study uses the BPMN approach. This research begins with data collection, analysis of porter's value chains, analysis of the relationship between business processes, then denotes the process obtained with BPMN notation. This research produces a business process model for laying hens which BPMN denotes. This business process model can solve coordination problems in the laying hens business.
Mohammad Malik Fajar, Annisa Rizkiana Putri, Khadijah Fahmi Hayati Holle
Published: 30 June 2022
Abstract:
The COVID-19 pandemic has resulted in more and more people losing their jobs. Due to layoffs or bankrupt companies. This has resulted in many people looking for job vacancies. Job vacancies are circulating on social media but there are real and fake ones. Irresponsible people create job vacancies on social media with fraudulent purposes or for personal gain. So, a comparison of data mining classification methods was made for the detection of authenticity of job vacancies on social media. The method used is naive bayes, KNN, and decision tree. In order to find out which method has the highest accuracy value and can be used to classify the authenticity of job vacancies, and fraud on social media can be prevented. Based on this research, the method that has the highest accuracy value is the KNN method. The accuracy value is 94.93%, while the Decision Tree model has an accuracy value of 91.57% and the Naive Bayes model has an accuracy of 84.35%. The KNN method is the best method for classifying the authenticity of job vacancies.
Hairatunnisa Hairatunnisa, Hapsoro Agung Nugroho, Relly Margiono
Published: 31 December 2021
Abstract:
One of the determinants of the quality of magnetic data is continuous data, so we need a data transmission system that can continuously transmit observational data. In this research, a magnetometer communication system design was carried out with the concept of the Internet of Things (IoT) using the MQTT and HTTP protocol, where measurement data in the form of the x-axis, y-axis, z-axis, horizontal components, and total magnetic field components are displayed on the dashboard in real time and continuously. Testing the performance of sending data is done using the Wireshark, it is known that the MQTT protocol has a better delivery quality compared to the HTPP protocol with an average delay value of 0.0120 seconds, an average value of packet length of 54 bytes and a packet loss value of 0.11%, while the HTTP protocol has an average delay value of 0.0257 seconds, an average packet length value of 268.1 bytes and a packet loss value of 0.5%.
Pungkas Subarkah, Ali Nur Ikhsan
Published: 31 December 2021
Abstract:
With the increase in internet users and the development of technology, the threats to its security are increasingly diverse. One of them is phishing which is the most important issue in cyberspace. Phishing is a threatening and trapping activity someone by luring the target to indirectly provide information to the trapper. The number of phishing crimes, this has the potential to cause several losses, one of which is namely about the loss of privacy of a person or company. This study aims to identify phishing websites. The Classification And Regression Trees (CART) algorithm is one of the classification algorithms, and the dataset in this research taken from the UCI Repository Learning obtained from the University of Huddersfield. The method used in this research is problem identification, data collection, pre-processing stage, use of the CART algorithm, validation and evaluation and withdrawal conclusion. Based on the test results obtained the value of accuracy of 95.28%. Thus the value of the accuracy obtained using the CART algorithm of 95.28% categorized very good classification.
Febry Purnomo Aji, Arip Solehudin, Chaerur Rozikin
Published: 31 December 2021
Abstract:
In the process of monitoring the capacity of the B3 waste storage facility at PT Fadira Teknik, the manual method is still used to determine whether the waste load is full (ready to be disposed) or not. Where in the process, workers must come and look directly at the B3 waste storage area. This will increase jobs for factory workers because they must always monitor the level of B3 waste before or after carrying out work. Apart from being harmful to humans, the B3 waste disposed of from the factory is in the form of small particles such as invisible dust which can be accidentally inhaled by the nose or into the eyes of the workers. Therefore the aim of this research is to create a smart trash can system that can monitor the volume of B3 waste in the trash, where the trash uses the IoT (Internet of Things) system by utilizing the Arduino Uno component as a microcontroller and ultrasonic sensor to detect the volume of waste then sends waste volume data to the Blynk application via the internet network to display information on the capacity of the trash. The research method used is the experimental method starting from system analysis, system design, system implementation, testing and evaluation. Testing on this smart trash system uses black box testing with the results of these tests being quite good where each test case is as expected.
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