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Journal : International Journal of Applied Information Systems and Informatics

Implementation of the Naive Bayes Classifier for Sentiment Analysis of Shopee E-Commerce Application Review Data on the Google Play Store Rizkya, Adilia Tri; Rianto, Rianto; Gufroni, Acep Irham
Journal of Applied Information System and Informatic (JAISI) Vol 1, No 1 (2023): November 2023
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v1i1.8993

Abstract

E-commerce in Indonesia is growing very quickly every year. The Ministry of Communication and Information (KEMKOMINFO) stated that Indonesia is the 10th largest e-commerce growth country with score 78%. One of the effects from increasing number of internet users in Indonesia is the mushrooming of shopping activities through internet media. This causes internet users want everything that instant and easy. Knowing this, most business people use it to market their products, especially in the field of goods and services. As it grows, e-commerce becomes easier to use and download. One example of an e-commerce application that is in great demand is Shopee and can be downloaded via the Google Play Store. Google Play Store has a review feature which contains user comments about the downloaded apps. Sentiment analysis is carried out to extract information related to Shopee E-commerce. The Naïve Bayes Classifier algorithm is suitable for use in sentiment analysis because this algorithm is purposeful as a classification method into positive and negative categories. The data was used from November 2022 to January 2023. From a total of 4902 review data obtained, after going through preprocessing, translation and then classification, the total data is obtained that is 4849 review data. From the data obtained it is classified 2348 positive reviews, 1259 neutral reviews, and 1242 negative reviews. Based on the results of the naive Bayes classifier method and testing with the confusion matrix, an accuracy value of 79% has been obtainednprecision 77%, recall 86%, and f1-score 81% on positive sentiment with support 2127. For neutral sentiment with an accuracy value of 83%, precision 87%, and recall 85% with support 1209, while for negative sentiment is with an accuracy value of 78%, precision 64%, and recall 70% with support 1513. From this data it is obtained micro AVG values for precision 80%, recall 79%, f1-score 79%, and support 4849, then for weighted average for precision 79%, recall 79%, f1- score 79%, and support 4849.
Analysis of Information Technology Governance in the SaData-Ku Application at the Kuningan Regency Regional Development Planning, Research and Development Agency (BAPPEDA) Using the COBIT 2019 Framework Pratama, Eneng Kurnia Dewi; Gufroni, Acep Irham
Journal of Applied Information System and Informatic (JAISI) Vol 2, No 1 (2024): Mei 2024
Publisher : Deparment Information System, Siliwangi University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37058/jaisi.v2i1.11008

Abstract

Currently, the success and continuity of a company or organization is very much based on IT, in terms of speed and results that can help increase the effectiveness and efficiency of business processes to achieve goals. In its implementation, the Regional Development Planning, Research and Development Agency (BAPPEDA) of Kuningan Regency encountered problems with the SaData-Ku application, errors occurred when inputting data (system failure to operate), there was a risk that when collecting data there was a delay from the predetermined schedule, the operation of the application was limited in time. for data input, resulting in bugs in the application. This problem has a negative impact on the continuity of the development planning process and can reduce the quality performance of information technology. To overcome this, application users need learning and growth to become more proficient in the field of information technology, thereby reducing difficulties in dealing with sudden changes or disruptions to applications. These problems can be identified thoroughly with governance using the COBIT 2019 framework. The form and content of the COBIT 2019 model are updated from the previous COBIT method and many new functions are added, including enabling improvements to the IT governance system. By conducting analysis, you can provide recommendations to improve the organization's capabilities to meet the agency's expectations and goals regarding IT governance in supporting its performance. The COBIT 2019 domains used are APO and DSS with details of the APO07, APO12, APO14 and DSS01 processes. The results of measuring the capability level of the APO07 domain at the Kuningan Regency Regional Development Planning, Research and Development Agency (BAPPEDA) got a capability level 4 value, the APO12, APO14 and DSS01 domains got a capability level 5 value.