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All Journal JISKa (Jurnal Informatika Sunan Kalijaga)
Kurniyatul Ainiyah
Universitas Islam Negeri Maulana Malik Ibrahim Malang
Computer Science & IT Electrical & Electronics Engineering Library & Information Science

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Rancang Bangun Film Animasi 3D Sejarah Terbentuknya Kerajaan Samudra Pasai Menggunakan Software Blender Kurniyatul Ainiyah; Nurul Hidayah; Faradilah Putri Damayanti; Indana Nuril Hidayah; Juniardi Nur Fadila; Fresy Nugroho
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 5 No. 3 (2020): November 2020
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2267.564 KB) | DOI: 10.14421/jiska.2020.53-04

Abstract

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.
Analisis Perbandingan Algoritma Decision Tree, kNN, dan Naive Bayes untuk Prediksi Kesuksesan Start-up Adhitya Prayoga Permana; Kurniyatul Ainiyah; Khadijah Fahmi Hayati Holle
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 6 No. 3 (2021): September 2021
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1857.312 KB) | DOI: 10.14421/jiska.2021.6.3.178-188

Abstract

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%.
Co-Authors Adhitya Prayoga Permana Faradilah Putri Damayanti Fresy Nugroho Indana Nuril Hidayah Juniardi Nur Fadila Khadijah Fahmi Hayati Holle Nurul Hidayah