INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
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174 research outputs found
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Trust and Perceived Risks in High School Students\u27 Online Learning Behaviour During Covid19 Pandemic
Full text linkThis study explores online learning by Indonesian high school students during the Covid19 Pandemic. Many high schools in Indonesia use online learning technology in Google Classroom and Google Meet. The sudden and forced switch from a conventional classroom to a fully online one caught many off guards. This study looks at the behavior of Indonesian high school students in facing sudden changes in study mode from offline or hybrid to full online due to the Covid19 Pandemic. Theory of Planned Behaviour is used and extended by adding Perceived Risks dan Trust to develop a questionnaire. Trust in this study is differentiated between Trust Toward Application and Trust Toward Organization. The survey was distributed to 1986 students from three private high schools in Yogyakarta, Indonesia. As many as 462 responses were received, representing a 23.26% response rate. Data were analyzed using PLS-SEM. The analysis of survey results confirms that TPB, Perceived Risks, and Trust could explain the use of Online Learning by Indonesian high school students. Furthermore, Trust is also influenced, albeit in a small percentage, Perceived Risks.This study explores online learning by Indonesian high school students during the Covid19 Pandemic. Many high schools in Indonesia use online learning technology in Google Classroom and Google Meet. The sudden and forced switch from a conventional classroom to a fully online one caught many off guards. This study looks at the behavior of Indonesian high school students in facing sudden changes in study mode from offline or hybrid to full online due to the Covid19 Pandemic. Theory of Planned Behaviour is used and extended by adding Perceived Risks dan Trust to develop a questionnaire. Trust in this study is differentiated between Trust Toward Application and Trust Toward Organization. The survey was distributed to 1986 students from three private high schools in Yogyakarta, Indonesia. As many as 462 responses were received, representing a 23.26% response rate. Data were analyzed using PLS-SEM. The analysis of survey results confirms that TPB, Perceived Risks, and Trust could explain the use of Online Learning by Indonesian high school students. Furthermore, Trust is also influenced, albeit in a small percentage, Perceived Risks
Android-Based Claim System for Electricity Network Customers of PLN Padang Branch
Full text linkThe Padang branch of the State Electricity Company (PLN) is a BUMN responsible for the electricity aspect. Complaints about various electricity problems are difficult for customers, so it is necessary to have a system that can be used as a place for protests and increase PLN\u27s loyalty to customers. The Android-based Claim System is a new application developed to be used by customers as a forum for complaints about electrical problems to the Padang branch of PLN. The Claim System is made into two parts: a Website-based System for PLN and an Android-based Claim Application for customers. Application development using the OOP concept uses UML (Unified Modeling Language) diagrams with the PHP MySql and Android programming languages. The test results were carried out using black box testing with the relevant results. The data of 35 respondents from the assessment questionnaire on the claims system obtained results with an Excellent rating of 78%, a Good rating of 21%, and a Bad rating of 2%. From the analysis results, the Claim System supported by this Android-based Client application can help customers complain about electrical problems quickly and easily.The Padang branch of the State Electricity Company (PLN) is a BUMN responsible for the electricity aspect. Complaints about various electricity problems are difficult for customers, so it is necessary to have a system that can be used as a place for protests and increase PLN\u27s loyalty to customers. The Android-based Claim System is a new application developed to be used by customers as a forum for complaints about electrical problems to the Padang branch of PLN. The Claim System is made into two parts: a Website-based System for PLN and an Android-based Claim Application for customers. Application development using the OOP concept uses UML (Unified Modeling Language) diagrams with the PHP MySql and Android programming languages. The test results were carried out using black box testing with the relevant results. The data of 35 respondents from the assessment questionnaire on the claims system obtained results with an Excellent rating of 78%, a Good rating of 21%, and a Bad rating of 2%. From the analysis results, the Claim System supported by this Android-based Client application can help customers complain about electrical problems quickly and easily
Development of Web-based Geographic Information System for Water Quality Monitoring of Watershed in Malang
Full text linkHuman activity and climate change significantly impact water quality, especially in Malang\u27s watershed. This research aims to develop a web-based Geographic Information System (Web- GIS) for water quality monitoring in that watershed. The water quality data had been collected from Enviromental Office of Malang District and Malang City. Water quality in this application was determined using the STORET method, comparing water quality data to water quality standards according to Government regulation so that the water quality status at each monitoring point will be known. The total 57 monitoring points are visualized spatially in this application based on the sampling location plotted by Global Positioning System (GPS). The longitude and latitude coordinates of the monitoring location had been converted in GeoJSON using Quantum GIS (QGIS) software. Google Map API key was used to display a sampling location map on the website. Web-GIS application was tested functionally using a black box, compatibility, and usability testing. Based on the testing results, it worked correctly on Chrome, Edge, Mozilla, and Opera browsers for PC/Laptops and also for browsers on Android smartphones version 4 and above. The application could be appropriately used and efficiently based on usability testing results.Human activity and climate change significantly impact water quality, especially in Malang\u27s watershed. This research aims to develop a web-based Geographic Information System (Web- GIS) for water quality monitoring in that watershed. The water quality data had been collected from Enviromental Office of Malang District and Malang City. Water quality in this application was determined using the STORET method, comparing water quality data to water quality standards according to Government regulation so that the water quality status at each monitoring point will be known. The total 57 monitoring points are visualized spatially in this application based on the sampling location plotted by Global Positioning System (GPS). The longitude and latitude coordinates of the monitoring location had been converted in GeoJSON using Quantum GIS (QGIS) software. Google Map API key was used to display a sampling location map on the website. Web-GIS application was tested functionally using a black box, compatibility, and usability testing. Based on the testing results, it worked correctly on Chrome, Edge, Mozilla, and Opera browsers for PC/Laptops and also for browsers on Android smartphones version 4 and above. The application could be appropriately used and efficiently based on usability testing results
Ontology Data Modeling of Indonesian Medicinal Plants and Efficacy
Full text linkPeople use medicinal plants for as early prevention and treating disease. Medicinal plants must be careful not to cause side effects, so knowledge is needed. Medicinal plant knowledge is stored using an ontology data model. In some ontology studies, there are still shortcomings in managing information, namely the absence of a relationship between scientific terms related to medicinal plants and phrases already known to the public. Hence, it is necessary to have this relationship. In other studies, there is no information related to disease protein, so this research also develops ontologies to enrich knowledge about medicinal plants and their efficacy. Based on the results, the developed ontology test can build a relationship between scientific terms of therapeutic pants and phrases that are known to the public. The public also knows which proteins affect a disease, so public knowledge about medicinal plants is getting wider.People use medicinal plants for as early prevention and treating disease. Medicinal plants must be careful not to cause side effects, so knowledge is needed. Medicinal plant knowledge is stored using an ontology data model. In some ontology studies, there are still shortcomings in managing information, namely the absence of a relationship between scientific terms related to medicinal plants and phrases already known to the public. Hence, it is necessary to have this relationship. In other studies, there is no information related to disease protein, so this research also develops ontologies to enrich knowledge about medicinal plants and their efficacy. Based on the results, the developed ontology test can build a relationship between scientific terms of therapeutic pants and phrases that are known to the public. The public also knows which proteins affect a disease, so public knowledge about medicinal plants is getting wider
Similarity Identification Based on Word Trigrams Using Exact String Matching Algorithms
Full text linkSeveral studies regarding excellent exact string matching algorithms can be used to identify similarity, including the Rabin-Karp, Winnowing, and Horspool Boyer-Moore algorithms. In determining similarities, the Rabin-Karp and Winnowing algorithms use fingerprints, while the Horspool Boyer-Moore algorithm uses a bad-character table. However, previous research focused on identifying similarities using these algorithms based on character n-gram. In contrast, identification based on the word n-gram to determine the similarity based on its linguistic meaning, especially for longer strings, had not been covered yet. Therefore, a word-level trigram was proposed to identify similarities based on the word trigrams using the three algorithms and compare each performance. Based on precision, recall, and running time comparison, the Rabin-Karp algorithm results were 100%, 100%, and 0.19 ms, respectively; the Winnowing algorithm results with the smallest window were 100%, 56%, and 0.18 ms, respectively; and the Horspool algorithm results were 100%, 100%, and 0.06 ms. From these results, it can be concluded that the performance of the Horspool Boyer-Moore algorithm is better in terms of precision, recall, and running time.Several studies regarding excellent exact string matching algorithms can be used to identify similarity, including the Rabin-Karp, Winnowing, and Horspool Boyer-Moore algorithms. In determining similarities, the Rabin-Karp and Winnowing algorithms use fingerprints, while the Horspool Boyer-Moore algorithm uses a bad-character table. However, previous research focused on identifying similarities using these algorithms based on character n-gram. In contrast, identification based on the word n-gram to determine the similarity based on its linguistic meaning, especially for longer strings, had not been covered yet. Therefore, a word-level trigram was proposed to identify similarities based on the word trigrams using the three algorithms and compare each performance. Based on precision, recall, and running time comparison, the Rabin-Karp algorithm results were 100%, 100%, and 0.19 ms, respectively; the Winnowing algorithm results with the smallest window were 100%, 56%, and 0.18 ms, respectively; and the Horspool algorithm results were 100%, 100%, and 0.06 ms. From these results, it can be concluded that the performance of the Horspool Boyer-Moore algorithm is better in terms of precision, recall, and running time
Implementation of Dijkstra\u27s Algorithm to Find a School Shortest Distance Based on The Zoning System in South Tangerang
Full text linkSchool is an essential thing for education quality. This time, the South Tangerang government is implementing a new student admission process using a zoning system; all prospective students must choose a school that has the shortest distance from their residence. However, many parents and prospective students do not understand this zoning system. The limited access to information is a problem for them, so they do not know where the schools are included in their zoning area. For this reason, the need to efforts the problem-solve to use Dijkstra\u27s algorithm as a consideration to find the results more accurate for the shortest distance. So the exact solution that should implement the information technology this time is "Implementation of Dijkstra\u27s Algorithm to Find a School Shortest Distance Based on The Zoning System In South Tangerang." It is a solution for parents and prospective students to get information about school choices included in their zoning.School is an essential thing for education quality. This time, the South Tangerang government is implementing a new student admission process using a zoning system; all prospective students must choose a school that has the shortest distance from their residence. However, many parents and prospective students do not understand this zoning system. The limited access to information is a problem for them, so they do not know where the schools are included in their zoning area. For this reason, the need to efforts the problem-solve to use Dijkstra\u27s algorithm as a consideration to find the results more accurate for the shortest distance. So the exact solution that should implement the information technology this time is "Implementation of Dijkstra\u27s Algorithm to Find a School Shortest Distance Based on The Zoning System In South Tangerang." It is a solution for parents and prospective students to get information about school choices included in their zoning
Analysis of CART and Random Forest on Statistics Student Status at Universitas Terbuka
Full text linkCART and Random Forest are part of machine learning which is an essential part of the purpose of this research. CART is used to determine student status indicators, and Random Forest improves classification accuracy results. Based on the results of CART, three parameters can affect student status, namely the year of initial registration, number of rolls, and credits. Meanwhile, based on the classification accuracy results, RF can improve the accuracy performance on student status data with a difference in the percentage of CART by 1.44% in training data and testing data by 2.24%.CART and Random Forest are part of machine learning which is an essential part of the purpose of this research. CART is used to determine student status indicators, and Random Forest improves classification accuracy results. Based on the results of CART, three parameters can affect student status, namely the year of initial registration, number of rolls, and credits. Meanwhile, based on the classification accuracy results, RF can improve the accuracy performance on student status data with a difference in the percentage of CART by 1.44% in training data and testing data by 2.24%
Design and Build Monitoring System for Pregnant Mothers and Newborns using the Waterfall Model
Full text linkIn Indonesia, the problems of pregnant women and newborns have not been resolved. The reason is that there is no monitoring system for pregnant women and newborns. This study aims to build a monitoring system for pregnant women and newborns. The monitoring system that will be made is mobile-based that can monitor and provide information about the health of pregnant women and children. The model used to create an information system uses the waterfall model. Meanwhile, to test the system built using the Blackbox test model. The plan that was created was tested directly to the user. As a result, the sequence in the waterfall model is proven to build a monitoring system for pregnant women and newborns. The black box model also showed if the built system did not have errors and was ready to be used. Combining the waterfall and BlackBox models results in a monitoring system for pregnant women and newborns whose entire menu can be used properly. The test was carried out on 25 pregnant women users, and it was found that the accumulated ratings were 89, 87, 88, and 89%. In this case, it is classified as Very Eligible.In Indonesia, the problems of pregnant women and newborns have not been resolved. The reason is that there is no monitoring system for pregnant women and newborns. This study aims to build a monitoring system for pregnant women and newborns. The monitoring system that will be made is mobile-based that can monitor and provide information about the health of pregnant women and children. The model used to create an information system uses the waterfall model. Meanwhile, to test the system built using the Blackbox test model. The plan that was created was tested directly to the user. As a result, the sequence in the waterfall model is proven to build a monitoring system for pregnant women and newborns. The black box model also showed if the built system did not have errors and was ready to be used. Combining the waterfall and BlackBox models results in a monitoring system for pregnant women and newborns whose entire menu can be used properly. The test was carried out on 25 pregnant women users, and it was found that the accumulated ratings were 89, 87, 88, and 89%. In this case, it is classified as Very Eligible
Analysis of A Pieces Framework of A Localhost Web-Based Income Statement EPOSAL Application
Full text linkMeasuring the quality of a system must be conducted. This is useful for repairing the damage that may be in the system that has been created. One thing that can be measured in a system is to measure the level of satisfaction of a system. Many methods can be used to measure the level of satisfaction, one of which is the PIECES framework method. PIECES framework is a series of activities that measure the level of happiness based on six variables: performance, information, economics, control and security, efficiency, and service. One of the systems that can be analyzed is the system contained in the EPOSAL application. EPOSAL is a localhost web-based application that can be used to create an income statement. The sample in this study was respondents who used this EPOSAL application. The instrument used was a questionnaire. Data analysis was carried out by following the PIECES calculation provisions. After analyzing the data, it is known that for the variables Performance, Economics, Control, and Security and Service, the satisfaction level is at the "Very Satisfied" level. As for the Efficiency, Information, and Efficiency variables, the level of satisfaction is at the "Satisfied" level.Measuring the quality of a system must be conducted. This is useful for repairing the damage that may be in the system that has been created. One thing that can be measured in a system is to measure the level of satisfaction of a system. Many methods can be used to measure the level of satisfaction, one of which is the PIECES framework method. PIECES framework is a series of activities that measure the level of happiness based on six variables: performance, information, economics, control and security, efficiency, and service. One of the systems that can be analyzed is the system contained in the EPOSAL application. EPOSAL is a localhost web-based application that can be used to create an income statement. The sample in this study was respondents who used this EPOSAL application. The instrument used was a questionnaire. Data analysis was carried out by following the PIECES calculation provisions. After analyzing the data, it is known that for the variables Performance, Economics, Control, and Security and Service, the satisfaction level is at the "Very Satisfied" level. As for the Efficiency, Information, and Efficiency variables, the level of satisfaction is at the "Satisfied" level
Framework for Analyzing Netizen Opinions on BPJS Using Sentiment Analysis and Social Network Analysis (SNA)
Full text linkThe Social Security Administrative Body is a legal entity established to administer social security programs. News about BPJS policies is often found online and social media that has received responses from netizens as a form of public opinion on the policy. One of them is the opinion of netizens on social media Twitter. Ideas can be positive, neutral, or negative. These opinions are processed using the Support Vector Machine (SVM) method, in some SVM studies still getting unsatisfactory results, with rates below 60%. For this reason, it is necessary to have feature selection or a combination with the other methods to obtain higher accuracy. To see the actors who influence the opinion of netizens on the topic of BPJS, the Social Network Analysis (SNA) method is used. Based on the SVM Method\u27s test results, the best accuracy results are obtained in combining the SVM Method with Adaboost, with an accuracy rate of 92%. Compared to the pure SVM method by 91%, the Combination of SVM Particle Swarm Optimization (PSO) by 87% and SVM using Feature Selection Genetic Algorithm (GA) by 86%.The Social Security Administrative Body is a legal entity established to administer social security programs. News about BPJS policies is often found online and social media that has received responses from netizens as a form of public opinion on the policy. One of them is the opinion of netizens on social media Twitter. Ideas can be positive, neutral, or negative. These opinions are processed using the Support Vector Machine (SVM) method, in some SVM studies still getting unsatisfactory results, with rates below 60%. For this reason, it is necessary to have feature selection or a combination with the other methods to obtain higher accuracy. To see the actors who influence the opinion of netizens on the topic of BPJS, the Social Network Analysis (SNA) method is used. Based on the SVM Method\u27s test results, the best accuracy results are obtained in combining the SVM Method with Adaboost, with an accuracy rate of 92%. Compared to the pure SVM method by 91%, the Combination of SVM Particle Swarm Optimization (PSO) by 87% and SVM using Feature Selection Genetic Algorithm (GA) by 86%