Lukas Chrisantyo, Argo Wibowo, Maria Nila Anggiarini, Antonius Rachmat Chrismanto
{"title":"Blackbox Testing on the ReVAMP Results of The DutaTani Agricultural Information System","authors":"Lukas Chrisantyo, Argo Wibowo, Maria Nila Anggiarini, Antonius Rachmat Chrismanto","doi":"10.29007/1sx8","DOIUrl":null,"url":null,"abstract":"Information technology continues to evolve unceasingly. In line with the evolvement, agricultural sciences also transform the sense of technology utilization in its information systems to improve its quality and service. The Government of Indonesia strongly supports the use of information system technology in agriculture. DutaTani research team has consistently developed Agricultural Information System (AIS) technology since 2016 to achieve precision agriculture. These developments must be followed by continuous improvement of information systems carried out sustainably following changes and developments in the technology used. Testing is sorely needed in the system repair phase so that changes or improvements do not cause conflicts or problems in any pre-existing functions. The number of technologies that are tried to be applied in the repair phase tends to cause high system failures when they are tested on users. Based on these problems, this study aims to implement Blackbox testing to increase the system's success rate before general users utilize it. Blackbox testing is considered capable of bridging the development team and random respondents representing general users later. This research also added iterations to increase the success rate of the system. Respondents are invited to use the system through several main scenarios, but they have to fill in the input with variables that they have never filled in before. Through several iterations and following a test scenario created by an independent test team with ten random respondents, this study increased the system's success rate by 11.79%.","PeriodicalId":93549,"journal":{"name":"EPiC series in computing","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"EPiC series in computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29007/1sx8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Information technology continues to evolve unceasingly. In line with the evolvement, agricultural sciences also transform the sense of technology utilization in its information systems to improve its quality and service. The Government of Indonesia strongly supports the use of information system technology in agriculture. DutaTani research team has consistently developed Agricultural Information System (AIS) technology since 2016 to achieve precision agriculture. These developments must be followed by continuous improvement of information systems carried out sustainably following changes and developments in the technology used. Testing is sorely needed in the system repair phase so that changes or improvements do not cause conflicts or problems in any pre-existing functions. The number of technologies that are tried to be applied in the repair phase tends to cause high system failures when they are tested on users. Based on these problems, this study aims to implement Blackbox testing to increase the system's success rate before general users utilize it. Blackbox testing is considered capable of bridging the development team and random respondents representing general users later. This research also added iterations to increase the success rate of the system. Respondents are invited to use the system through several main scenarios, but they have to fill in the input with variables that they have never filled in before. Through several iterations and following a test scenario created by an independent test team with ten random respondents, this study increased the system's success rate by 11.79%.