Indonesian people's knowledge about the history of kingdoms in Indonesia was decreased. Now the existence of history books was shifted by the rapid development of technology. Realized this, many educational institutions were involved in technology to their learning media. To support that, the writer will use technology to create a learning media, named 3D short animated films. This kind of film turned out to attract the publics' attention, ranging from children to adolescents. The animated film will be designed with the theme of the first Islamic kingdom in Indonesia, named the Samudra Pasai kingdom with a duration of approximately 3 minutes. this animated film was made by Blender software version 2.79. The design of this animation aims to increase knowledge as well as learning media for students about the history of the Indonesian people, especially the history of Samudra Pasai kingdom.
Start-ups have a very important role in economic growth, the existence of a start-up can open up many new jobs. However, not all start-ups that are developing can become successful start-ups. This is because start-ups have a high failure rate, data shows that 75% of start-ups fail in their development. Therefore, it is important to classify the successful and failed start-ups, so that later it can be used to see the factors that most influence start-up success, and can also predict the success of a start-up. Among the many classifications in data mining, the Decision Tree, kNN, and Naïve Bayes algorithms are the algorithms that the authors chose to classify the 923 start-up data records that were previously obtained. The test results using cross-validation and T-test show that the Decision Tree Algorithm is the most appropriate algorithm for classifying in this case study. This is evidenced by the accuracy value obtained from the Decision Tree algorithm, which is greater than other algorithms, which is 79.29%, while the kNN algorithm has an accuracy value of 66.69%, and Naive Bayes is 64.21%.
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%.
Dalam manajemen proyek terdapat keputusan-keputusan yang akan diambil. Keputusan-keputusan ini harus ditentukan karena kurang tepatnya pengambilan keputusan yang dilakukan dapat berdampak negatif pada kelangsungan proses bisnis. Sehingga keputusan yang diambil harus sesuai dengan manajemen proyek. Oleh karena itu, permasalahan yang ingin diselesaikan pada penelitian ini adalah bagaimana cara mengidentifikasi titik-titik keputusan dalam manajemen proyek. Tujuan dilakukannya penelitian ini adalah untuk menganalisis keputusan apa saja yang ada di dalam proses bisnis manajemen proyek. Untuk menganalisis titik-titik keputusan ini diperlukan BPMN (Business Process Model Notation) dari proses-proses yang ada. Dari BPMN tersebut titik-titik keputusan dilambangkan dengan gateway (XOR, OR, dan AND gateway) yang berada di setiap percabangan yang terbentuk. Hasil dari penelitian ini adalah berupa titik-titik keputusan yang ada dalam model proses bisnis manajemen proyek beserta kriteria-kriteria apa saja yang diperlukan serta pilihan metode pengambilan keputusan.
Tujuan dari penelitian ini adalah untuk menganalisis kebutuhan Enterprise Resource Planning (ERP) sekolah berdasarkan Standar Nasional Pendidikan (SNP). Analisis dimulai dengan menerapkan konsep ERP ke dalam proses-proses bisnis yang ada di sekolah. Kemudian, melakukan pemetaan ERP ke dalam SNP sehingga menghasilkan output berupa kebutuhan ERP sekolah. Hasil dari penelitian ini berupa susunan atau daftar terperinci mengenai kebutuhan ERP sekolah. Selanjutnya data tersebut dapat digunakan untuk membuat rancangan arsitektur kebutuhan ERP sekolah berdasarkan SNP. Dibangunnya sistem informasi ERP bertujuan untuk menciptakan sebuah sistem informasi sekolah yang lebih terstruktur dan terintegrasi.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.