Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2469
Muhammad Innuddin, Hairani Hairani, Ida Putu Andika
Orchid is an ornamental plant that has high aesthetic value with a variety of attractive colors on its flowers and has high economic value. One of the problems in the cultivation of orchids is the problem of pests that can inhibit growth and reduce the aesthetics of orchid plants. Not only that, the shortage of orchid plant experts can be a trigger for delays in identifying the types of pests on orchids, resulting in poor growth quality and even crop failure. Early identification is needed so that handling is fast so that the quality of growth is good. The solution offered by this research is the implementation of the certainty factor method for identifying web-based types of pests on dendrobium orchids. The stages of this research consist of knowledge acquisition, knowledge modeling, implementation, and accuracy testing. Based on the test results of 32 data, the certainty factor method can identify exactly 29 data and the rest are identified incorrectly, resulting in an accuracy of 90.6%. Thus, the certainty factor method can be used to identify the type of pest on orchids because it has very good accuracy.
{"title":"Implementation of Certainty Factor Method for Identification of Pest Types on Dendrobium Based on Expert Systems","authors":"Muhammad Innuddin, Hairani Hairani, Ida Putu Andika","doi":"10.32520/stmsi.v12i2.2469","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2469","url":null,"abstract":"Orchid is an ornamental plant that has high aesthetic value with a variety of attractive colors on its flowers and has high economic value. One of the problems in the cultivation of orchids is the problem of pests that can inhibit growth and reduce the aesthetics of orchid plants. Not only that, the shortage of orchid plant experts can be a trigger for delays in identifying the types of pests on orchids, resulting in poor growth quality and even crop failure. Early identification is needed so that handling is fast so that the quality of growth is good. The solution offered by this research is the implementation of the certainty factor method for identifying web-based types of pests on dendrobium orchids. The stages of this research consist of knowledge acquisition, knowledge modeling, implementation, and accuracy testing. Based on the test results of 32 data, the certainty factor method can identify exactly 29 data and the rest are identified incorrectly, resulting in an accuracy of 90.6%. Thus, the certainty factor method can be used to identify the type of pest on orchids because it has very good accuracy.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135439701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2732
Heru Wijayanto Aripradono
The growth of startups in Indonesia Education Technology (EdTech) has increased significantly and related with the growth of EdTech globally. Related to the pandemic and the need for future skills, it is a moment for EdTech startups, to build a process, approach and strategy for teaching-learning activities to be able to produce someone with the skills needed in the future. The purpose of this research is to see how the technology-based learning process in EdTech startups can be used and adapted by users in improving their skills and needs in the future. This research uses the Technology Acceptance Model (TAM) framework by adding facilitating condition variables as extended factors to see how the user's environmental conditions help encourage and adapt the use of technology. This research uses a quantitative method where data collection is carried out to students who are still active in EdTech startups Indonesia in the period 2016 - 2022 and analyzed using structural equation modeling. The results illustrate that TAM has been able to explain the factors that predict the use of e-learning among users on the Edtech Startup platform in supporting the learning process. Then there is a significant relationship between facilitating condition variables with ease of use and perceived benefits. In addition, the results of this study illustrate a significant relationship between the core components TAM framework and will enrich the academic literature in understanding the conditions of learning platforms in the EdTech sector to support the needs of skills and competencies in the future.
{"title":"The Analysis of Extended Technology Acceptance Model to Understand use of Platform at Education Technology Startup","authors":"Heru Wijayanto Aripradono","doi":"10.32520/stmsi.v12i2.2732","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2732","url":null,"abstract":"The growth of startups in Indonesia Education Technology (EdTech) has increased significantly and related with the growth of EdTech globally. Related to the pandemic and the need for future skills, it is a moment for EdTech startups, to build a process, approach and strategy for teaching-learning activities to be able to produce someone with the skills needed in the future. The purpose of this research is to see how the technology-based learning process in EdTech startups can be used and adapted by users in improving their skills and needs in the future. This research uses the Technology Acceptance Model (TAM) framework by adding facilitating condition variables as extended factors to see how the user's environmental conditions help encourage and adapt the use of technology. This research uses a quantitative method where data collection is carried out to students who are still active in EdTech startups Indonesia in the period 2016 - 2022 and analyzed using structural equation modeling. The results illustrate that TAM has been able to explain the factors that predict the use of e-learning among users on the Edtech Startup platform in supporting the learning process. Then there is a significant relationship between facilitating condition variables with ease of use and perceived benefits. In addition, the results of this study illustrate a significant relationship between the core components TAM framework and will enrich the academic literature in understanding the conditions of learning platforms in the EdTech sector to support the needs of skills and competencies in the future.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438676","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2457
Nissa Shahadah Qur'ani, Arie Wahyu Wijayanto
Smart City is a city with an innovative development concept. However, not all Smart Cities in countries have the same standard because they are quite heterogeneous. Thus, a cluster analysis was carried out to classify Smart City. The result shows that Smart City is divided into two levels, those are high and low. k-means and hierarchical clustering is used for the method of this research. The grouping is based on the motion index, which consists of economic, environmental, mobilization and transportation indicators, and also international profiles represented by various variables. This research expects that Smart City at a certain level can be compared with other levels, in order to there are improvements and mutual learning about Smart City at a high level. This can also encourage other cities in the process towards Smart City.
{"title":"Implementation of K-Means and Hierarchical Clustering in Determining Levels of Smart City 2022 Based on Motion Index","authors":"Nissa Shahadah Qur'ani, Arie Wahyu Wijayanto","doi":"10.32520/stmsi.v12i2.2457","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2457","url":null,"abstract":"Smart City is a city with an innovative development concept. However, not all Smart Cities in countries have the same standard because they are quite heterogeneous. Thus, a cluster analysis was carried out to classify Smart City. The result shows that Smart City is divided into two levels, those are high and low. k-means and hierarchical clustering is used for the method of this research. The grouping is based on the motion index, which consists of economic, environmental, mobilization and transportation indicators, and also international profiles represented by various variables. This research expects that Smart City at a certain level can be compared with other levels, in order to there are improvements and mutual learning about Smart City at a high level. This can also encourage other cities in the process towards Smart City.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135439690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The N+2 Fashion store is engaged in selling trend shoes which is located in Air Batu City. Activities in the N+2 Fashion Store include ordering and selling trending shoes. Checking the supply of trending shoes is done by checking them one by one, of course this will make it very difficult for employees to estimate the number of trend shoes they want to order from each trending type of shoe. The large number of trend shoe brands is an obstacle in carrying out business processes which results in wrong prices for these trend shoes. In predicting trend shoes must ensure the sales process, minimize costs and time required. The problem faced by the N+2 Fashion Store is the difficulty in predicting the number of items that must be available for the next period in order to meet customer needs and not cause a buildup of goods in the long term. To overcome this problem, predictions are made using the trend moment method which is a forecasting method used to see trends (data that have increased) based on historical data from one variable using time series data. The results of the research obtained a prediction that in September 2022 there would be 9 pcs of Adidas shoes sold with a MAPE error rate of 16.33%.
{"title":"Application of the Trend Moment Method to Predict Shoes Sales","authors":"Gilang Nugroho Syahputra Jarod, Iqbal Kamil Siregar, Endra Saputra","doi":"10.32520/stmsi.v12i2.2781","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2781","url":null,"abstract":"The N+2 Fashion store is engaged in selling trend shoes which is located in Air Batu City. Activities in the N+2 Fashion Store include ordering and selling trending shoes. Checking the supply of trending shoes is done by checking them one by one, of course this will make it very difficult for employees to estimate the number of trend shoes they want to order from each trending type of shoe. The large number of trend shoe brands is an obstacle in carrying out business processes which results in wrong prices for these trend shoes. In predicting trend shoes must ensure the sales process, minimize costs and time required. The problem faced by the N+2 Fashion Store is the difficulty in predicting the number of items that must be available for the next period in order to meet customer needs and not cause a buildup of goods in the long term. To overcome this problem, predictions are made using the trend moment method which is a forecasting method used to see trends (data that have increased) based on historical data from one variable using time series data. The results of the research obtained a prediction that in September 2022 there would be 9 pcs of Adidas shoes sold with a MAPE error rate of 16.33%.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135439702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2791
Grace Desi Geoloni, Dewi Agushinta R.
The application of information technology is a crucial aspect of Human Resources (HR) activities in an organization (company) to manage its employees, such as attendance data, personal data, and performance appraisals. This data can produce information to make a decision. To assist HR in carrying out their duties, an IT company implements a Human Resources Information System (HRIS), but it has never been tested. The purpose of this research is to test the Human Resource system that has been implemented using the ISO 25010:2011 method with usability characteristics. The research stage starts with analyzing the employees' problems with using the system. Tests are divided into 2 types, namely on employees who often use the system and employees who rarely use the system, and determining the research method. Afterward, determine the characteristics and sub-characteristics and their weight, make assessment indicators of the sub-characteristics, assess the usability characteristic testing, and at the end, total calculation of them. The results showed that the lowest ratings were still obtained for the employee learnability sub-characteristics, namely 77.2% and 65.3% for both types. Therefore, it is recommended that the company should make a detailed user guide and prepare training for all employees. So they will understand the system well.
{"title":"Web-Based Human Resource System Quality Analysis Using ISO 25010:2011 Method Based on Usability Characteristics","authors":"Grace Desi Geoloni, Dewi Agushinta R.","doi":"10.32520/stmsi.v12i2.2791","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2791","url":null,"abstract":"The application of information technology is a crucial aspect of Human Resources (HR) activities in an organization (company) to manage its employees, such as attendance data, personal data, and performance appraisals. This data can produce information to make a decision. To assist HR in carrying out their duties, an IT company implements a Human Resources Information System (HRIS), but it has never been tested. The purpose of this research is to test the Human Resource system that has been implemented using the ISO 25010:2011 method with usability characteristics. The research stage starts with analyzing the employees' problems with using the system. Tests are divided into 2 types, namely on employees who often use the system and employees who rarely use the system, and determining the research method. Afterward, determine the characteristics and sub-characteristics and their weight, make assessment indicators of the sub-characteristics, assess the usability characteristic testing, and at the end, total calculation of them. The results showed that the lowest ratings were still obtained for the employee learnability sub-characteristics, namely 77.2% and 65.3% for both types. Therefore, it is recommended that the company should make a detailed user guide and prepare training for all employees. So they will understand the system well.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2499
Annisa Firnanda, Arie Wahyu Wijayanto
Differences in social, economic, demographic and resource conditions in each region can cause inequality, so it is necessary to encourage economic development according to the capabilities of the region. The importance of looking at socio-economic indicators that are development targets, especially in Eastern Indonesia (KTI). This study uses two non-hierarchical methods, namely K-Means and K-Medoids. In this study, Principal Component Analysis (PCA) was carried out to produce 3 factors. Determining the number of clusters using internal validity and stability shows that the K-Means method with a number of clusters of 2 produces the most optimal clusters. Cluster 1 consists of 152 regencies/municipalities, while cluster 2 consists of 80 regencies/municipalities. Cluster 1 has above average infrastructure and economic characteristics, while its human quality is still below average.
{"title":"Grouping of Regencies/Municipalities in Eastern Indonesia in 2021 Based on Socio-Economic Indicators","authors":"Annisa Firnanda, Arie Wahyu Wijayanto","doi":"10.32520/stmsi.v12i2.2499","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2499","url":null,"abstract":"Differences in social, economic, demographic and resource conditions in each region can cause inequality, so it is necessary to encourage economic development according to the capabilities of the region. The importance of looking at socio-economic indicators that are development targets, especially in Eastern Indonesia (KTI). This study uses two non-hierarchical methods, namely K-Means and K-Medoids. In this study, Principal Component Analysis (PCA) was carried out to produce 3 factors. Determining the number of clusters using internal validity and stability shows that the K-Means method with a number of clusters of 2 produces the most optimal clusters. Cluster 1 consists of 152 regencies/municipalities, while cluster 2 consists of 80 regencies/municipalities. Cluster 1 has above average infrastructure and economic characteristics, while its human quality is still below average.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2815
Sekar Ayu Diah Pitaloka, Evi Maria (SCOPUS ID: 57093633500)
This study aims to apply ISO 31000:2018 for risk management activities in the Libsys Interests of Students application. CV XYZ, an information technology consultant in Yogyakarta, developed this application. This application detects students' academic interests, so teachers can easily direct students according to their interests. So far, the company has never carried out risk management activities in the system development process, even though this activity plays a role in managing and mitigating risks so that the application can achieve its goals. Risk management activities start from the stages of communication and consultation, establishing context, risk assessment and treatment, and monitoring and review by ISO 31000:2018 standard. The study's results found the effectiveness of the ISO 31000:2018 standard for managing risk in information systems consulting companies. The risk management activity found 17 risk opportunities from the Student Interests Libsys application, with four high-level, eight medium-risk, and five low-level risk opportunities. This study also provides suggestions for handling risks in the Libsys Interests Students application and documents them to help management manage the risks in this application.
{"title":"Implementation of ISO 31000:2018 in Risk Management Activities of Libsys Application Student Interest","authors":"Sekar Ayu Diah Pitaloka, Evi Maria (SCOPUS ID: 57093633500)","doi":"10.32520/stmsi.v12i2.2815","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2815","url":null,"abstract":"This study aims to apply ISO 31000:2018 for risk management activities in the Libsys Interests of Students application. CV XYZ, an information technology consultant in Yogyakarta, developed this application. This application detects students' academic interests, so teachers can easily direct students according to their interests. So far, the company has never carried out risk management activities in the system development process, even though this activity plays a role in managing and mitigating risks so that the application can achieve its goals. Risk management activities start from the stages of communication and consultation, establishing context, risk assessment and treatment, and monitoring and review by ISO 31000:2018 standard. The study's results found the effectiveness of the ISO 31000:2018 standard for managing risk in information systems consulting companies. The risk management activity found 17 risk opportunities from the Student Interests Libsys application, with four high-level, eight medium-risk, and five low-level risk opportunities. This study also provides suggestions for handling risks in the Libsys Interests Students application and documents them to help management manage the risks in this application.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2259
Firman Yosep Tember, Ina Najiyah
The difference in the types of batik in West Java Province for the general public will not be seen significantly, because all the motifs at first glance look the same. Classification of batik motifs needs to be done to overcome the difficulties of different types of batik, in order to provide information and make it easier to distinguish the name of a batik motif and can tell the name of a batik motif for ordinary people who do not know the name of a batik motif with a fairly accurate level of accuracy. Classification of batik needs to be done to determine the type of batik from each region to make it easier to distinguish motifs from each region. The method used in this study is the classification of batik types in West Java Province using the Convolutional Neural Network (CNN) method. The results carried out for the classification of West Java batik image types using the Convolutional Neural Network (CNN) method that the feature extraction process can be carried out outside the process contained in the CNN algorithm or using feature learning depending on the needs of the research itself, and the results of the classification at 20 epochs and a learning rate value of 0.001 obtained an accuracy of 90% with a precision of 90% and a recall of 90%. This result is quite good considering the quality and amount of data obtained is not so good and the amount is not much.
{"title":"Classification of West Java Batik Motifs Using Convolutional Neural Network","authors":"Firman Yosep Tember, Ina Najiyah","doi":"10.32520/stmsi.v12i2.2259","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2259","url":null,"abstract":"The difference in the types of batik in West Java Province for the general public will not be seen significantly, because all the motifs at first glance look the same. Classification of batik motifs needs to be done to overcome the difficulties of different types of batik, in order to provide information and make it easier to distinguish the name of a batik motif and can tell the name of a batik motif for ordinary people who do not know the name of a batik motif with a fairly accurate level of accuracy. Classification of batik needs to be done to determine the type of batik from each region to make it easier to distinguish motifs from each region. The method used in this study is the classification of batik types in West Java Province using the Convolutional Neural Network (CNN) method. The results carried out for the classification of West Java batik image types using the Convolutional Neural Network (CNN) method that the feature extraction process can be carried out outside the process contained in the CNN algorithm or using feature learning depending on the needs of the research itself, and the results of the classification at 20 epochs and a learning rate value of 0.001 obtained an accuracy of 90% with a precision of 90% and a recall of 90%. This result is quite good considering the quality and amount of data obtained is not so good and the amount is not much.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135439564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2838
Wahyu Soataon Hasibuan, Heri Santoso
Today's technological developments make all aspects of life easier. One form of convenience that can be found in the world of lectures is a digital student graduation information system. In this study the authors designed an android-based new student admission classification system using the vikor method. In simple terms, the vikor method can be used to perform multicriteria ranking and weighting of each assessment criterion. In the implementation of the North Sumatra State Islamic University Independent Examination, there are several materials to be tested such as Religious Sciences, General Sciences, Arabic, English, and Interviews where the system still uses a passing grade where its application is considered less efficient. The use of the vikor method in this study is intended to carry out the process of ranking student grades based on predetermined weights based on the criteria of several materials tested. In this study, the creation of an android application using the app inventor platform. The results in this study indicate that the vikor method can be implemented in the new student admission classification system and perform ranking based on the exam results that have been carried out using an android smartphone.
{"title":"Design and Implementation of an Android based New Student Admissions Classification System using the Vikor Method","authors":"Wahyu Soataon Hasibuan, Heri Santoso","doi":"10.32520/stmsi.v12i2.2838","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2838","url":null,"abstract":"Today's technological developments make all aspects of life easier. One form of convenience that can be found in the world of lectures is a digital student graduation information system. In this study the authors designed an android-based new student admission classification system using the vikor method. In simple terms, the vikor method can be used to perform multicriteria ranking and weighting of each assessment criterion. In the implementation of the North Sumatra State Islamic University Independent Examination, there are several materials to be tested such as Religious Sciences, General Sciences, Arabic, English, and Interviews where the system still uses a passing grade where its application is considered less efficient. The use of the vikor method in this study is intended to carry out the process of ranking student grades based on predetermined weights based on the criteria of several materials tested. In this study, the creation of an android application using the app inventor platform. The results in this study indicate that the vikor method can be implemented in the new student admission classification system and perform ranking based on the exam results that have been carried out using an android smartphone.","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135438675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-31DOI: 10.32520/stmsi.v12i2.2282
Kusnawi Kusnawi, M Andika Fadhil Eka Putra, Joang Ipmawati
In the era of Industry 4.0, characterized by the abundance of data, there are many opportunities to carry out various data-related processes. One of these is the data forecasting process which has been widely used. By analyzing data, we can make predictions and make decisions automatically. For example, one of the problems that decision-makers, especially in Kabupaten Sumedang, must solve is the changes in the prices of basic commodities that are essential for society's consumption. The prices of these commodities in the market tend to fluctuate in the short or long term. By analyzing the available data, we can predict the direction of changes in the prices of basic commodities in the market. In this study, the ARIMA model is used, which is one of the time series models that can be used to predict the possibility of an increase or decrease in the prices of basic commodities in the market in Kabupaten Sumedang. The ARIMA model uses the previous day's price data as a benchmark to predict the prices of basic commodities in the future. After being analyzed, the results of the model will be in several ARIMA model forms. An efficient ARIMA model will be used to model the prices of basic food commodities. This research produced the three best ARIMA models, namely ARIMA(1-1-1) for broiler chicken meat, ARIMA(0-1-1) for shallots, and ARIMA(0-1-1) for garlic. The accuracy test results percentage error for the best model using MAPE show an average value below 10%. Keywords: Food staples, Forecasting, Time Series, ARIMA, MAPE
{"title":"Price Prediction Of Basic Material Using ARIMA Forecasting Method Through Open Data Sumedang District","authors":"Kusnawi Kusnawi, M Andika Fadhil Eka Putra, Joang Ipmawati","doi":"10.32520/stmsi.v12i2.2282","DOIUrl":"https://doi.org/10.32520/stmsi.v12i2.2282","url":null,"abstract":"In the era of Industry 4.0, characterized by the abundance of data, there are many opportunities to carry out various data-related processes. One of these is the data forecasting process which has been widely used. By analyzing data, we can make predictions and make decisions automatically. For example, one of the problems that decision-makers, especially in Kabupaten Sumedang, must solve is the changes in the prices of basic commodities that are essential for society's consumption. The prices of these commodities in the market tend to fluctuate in the short or long term. By analyzing the available data, we can predict the direction of changes in the prices of basic commodities in the market. In this study, the ARIMA model is used, which is one of the time series models that can be used to predict the possibility of an increase or decrease in the prices of basic commodities in the market in Kabupaten Sumedang. The ARIMA model uses the previous day's price data as a benchmark to predict the prices of basic commodities in the future. After being analyzed, the results of the model will be in several ARIMA model forms. An efficient ARIMA model will be used to model the prices of basic food commodities. This research produced the three best ARIMA models, namely ARIMA(1-1-1) for broiler chicken meat, ARIMA(0-1-1) for shallots, and ARIMA(0-1-1) for garlic. The accuracy test results percentage error for the best model using MAPE show an average value below 10%. Keywords: Food staples, Forecasting, Time Series, ARIMA, MAPE","PeriodicalId":32357,"journal":{"name":"Jurnal Sistem Informasi","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135439698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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