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All Journal JMPM: Jurnal Matematika dan Pendidikan Matematika Building of Informatics, Technology and Science Journal of Students‘ Research in Computer Science (JSRCS) Journal of Fundamental Mathematics and Applications (JFMA) Hortatori : Jurnal Pendidikan Bahasa dan Sastra Indonesia International Journal of Information Technology and Computer Science Applications (IJITCSA) Journal of Computer Science Contributions (Jucosco)
Ramdhania, Khairunnisa Fadhilla
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Mathematics

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CONSTRUCTION OF FUNDAMENTAL THEOREMS OF FRACTIONAL CALCULUS Ramdhania, Khairunnisa Fadhilla; Sari, Rafika; Khalida, Rakhmi; Pratama, Aldira Ryan; Lestari, Nur’aini Puji
Journal of Fundamental Mathematics and Applications (JFMA) Vol 7, No 1 (2024)
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jfma.v7i1.19256

Abstract

This paper discusses the theory of derivatives and integrals in the form of fractions with a particular order initiated by Lioville. Specifically, regarding the correlation between fractional derivatives and integrals, by examining definitions, determining the kernel function, and applying them to several examples, so a general formula will be obtained regarding the relationship between the two. This formula is the product of the fractional derivative of an order of a polynomial function of m-degree which is equal to the (n+1) th derivative of the related order fractional integral of a polynomial function of -degree that the truth is proved by using Mathematical Induction.
Manipulasi Gambar dengan Transfer Gaya Menggunakan Convolutional Neural Network Khalida, Rakhmi; Ramdhania, Khairunnisa Fadhilla
Building of Informatics, Technology and Science (BITS) Vol 3 No 3 (2021): December 2021
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (781.308 KB) | DOI: 10.47065/bits.v3i3.1049

Abstract

Recently computers have been able to produce photographs that allow users to compose selfies with van Gogh paintings. Inspired by the power of convolutional neural networks (CNN), he first learned how to use CNN to reproduce famous painting styles combined with self-portrait images. The method used is called a neural network transfer. However, early versions of neural networks had optimization problems, requiring hundreds or thousands of iterations to transfer forces combined with a single image. To overcome this in-efficiency, researchers developed the CNS-style PerStyle-Per-Model (PSPM) transfer method. The development of force transfer using a deep neural network is also called NST by training the VGG-16 model to change any image in one feed, foward propagation. A trained model can adjust to any drawing mode with just one iteration instead of thousands of iterations over the network and to get the most objective possible style of transfer
Pengaruh Penggunaan Teknik Wawancara Terhadap Kemampuan Menulis Karangan Argumentasi Siswa SMP Negeri 3 Karawang Kuning, Layung; Setiawati, Siti; Ramdhania, Khairunnisa Fadhilla
Hortatori : Jurnal Pendidikan Bahasa dan Sastra Indonesia Vol 8, No 1 (2024): Hortatori: Jurnal Pendidikan Bahasa dan Sastra Indonesia
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jh.v8i1.2154

Abstract

This research aims to determine how much influence the interview technique has on the ability to write argumentation essays for grade 2 students of SMP Negeri 3 Karawang The research method used is an experimental method with control design.The sample was randomly taken from the affordable population of second grade students of SMP Negeri 3 Karawang for the 2022/2023 school year. \ The analytical techniques used in this study are normality test, homogeneity test and hypothesis testing with t-test at significance level a 0.05. Scores on experimental class  scores reached 63 for the lowest grade and 90 for the highest grade with an average score of 78.43. Meanwhile, in the control class, 47 for the lowest value, 79 for the highest value and  62.63 for the average value After analysis for the normality test, the results of the control class calculated L of 0.0996 and in the experimental class of 0.148 smaller than the table L with n = 30, that is, 0.161. The results of the study with the t-test showed t count of 3.78 and t table with n-30 and significance level a = 0.05 obtained a price of 2.04 because t count is greater than t table (3.78 > 2.04), then Ho was rejected.  Thismeans that the interview technique in this study affects the ability to write argumentation essays for students of SMP Negeri 3 Karawang.
Implementasi Metode Naïve Bayes dan Support Vector Machine (SVM) untuk Menganalisis Sentimen Pengguna Twitter terhadap Transjakarta Ramdhania, Khairunnisa Fadhilla; Hidayat, Dian Fitrianto; Salkiawati, Ratna
JMPM: Jurnal Matematika dan Pendidikan Matematika Vol 9 No 1 (2024): March - August 2024
Publisher : Prodi Pendidikan Matematika Universitas Pesantren Tinggi Darul Ulum Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/jmpm.v9i1.4494

Abstract

Twitter merupakan dari salah satu platform media sosial yang populer di Indonesia. Twitter menjadi salah satu media untuk mengungkapkan perasaan bagi para pengguna dan memberikan kritik atau saran terhadap suatu objek. Transjakarta merupakan salah satu transportasi umum yang memiliki jumlah penumpang harian terbanyak dibandingkan dengan transportasi umum lainnya. Berbagai pengalaman dirasakan oleh para pengguna Transjakarta. Beberapa pengguna membagikan pengalaman tersebut di Twitter. Namun tidak hanya pengalaman tetapi pendapat, kritik, dan saran juga pengguna utarakan di Twitter. Salah satu permasalahan yang terjadi pada Transjakarta yaitu beberapa halte mengalami penutupan sementara waktu. Selain itu marak terjadinya kasus asusila yang dialami oleh beberapa pengguna Transjakarta. Tujuan dari penelitian ini yaitu untuk menganalisis opini pengguna media sosial Twitter terhadap Transjakarta dengan menggunakan metode Support Vector Machine (SVM) dan Naïve Bayes. Pada penelitian ini menggunakan lexicon based untuk pemberian label dari masing-masing kelas dan menggunakan dataset sebanyak 6736 tweet. Hasil yang didapatkan dari kelas positif berjumlah 2228 dan kelas negatif 2821. Berdasarkan Metode Support Vector Machine didapatkan akurasi 84.95%, presisi 83%, recall 83% dan f1-score 83% sedangkan Metode Naïve Bayes didapatkan akurasi 76.43%, presisi 78%, recall 68% dan f1-score 73%. Kata kunci: Twitter; Transjakarta; Lexicon Based; Naïve Bayes; Support Vector Machine
Algoritma Levenshtein Distance sebagai Solusi Efisiensi Pencarian pada Training Registration System Akbar, Iqbal Faris; Mugiarso; Ramdhania, Khairunnisa Fadhilla; Rasim
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/mzr20n84

Abstract

The training registration process at Company XYZ faced several challenges, including the use of physical documents, slow file submission, non-standardized document numbering, and inefficient file storage. This research aimed to develop a web-based application called "Training Registration System" using the Waterfall software development method to address these issues, as well as implementing the Levenshtein Distance algorithm in the search feature to enhance training search efficiency. The results showed that the application successfully improved the efficiency and accuracy of the training registration and search process by eliminating the need for physical file submission, accelerating the workflow, and reducing the potential for errors. The implementation of the Levenshtein Distance algorithm also proved effective in improving the efficiency of training searches based on training names, even in cases of typos, such as the strings "Trainning" and "Training" which had a similarity score of 87.5% based on similarity weight calculations.
Analisis Clustering K-Means untuk Pemetaan Tingkat Pengangguran Terbuka di Provinsi-Provinsi Indonesia Tahun 2013-2023 Ramadhan, Alif Izzuddin; Ramdhania, Khairunnisa Fadhilla; atika, prima dina
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/wbpydb62

Abstract

This study analyzes unemployment rates in Indonesian provinces using data from the Central Statistics Agency (BPS) for the period 2013-2023 and the K-Means clustering algorithm. The aim is to group regions based on the Open Unemployment Rate (TPT). Two main clusters were produced: one with a high unemployment rate (cluster 0) and one with a low unemployment rate (cluster 1). Cluster 0 consists of 12 provinces, while cluster 1 consists of 22 provinces. The model evaluation shows a Davies-Bouldin Index score of 0.7041, indicating good clustering quality. The clustering results are visualized in the form of a map for easy interpretation. This research is expected to help policymakers design more effective policies in reducing unemployment in Indonesia, provide deep insights into regional differences in terms of unemployment, and support targeted decision-making.
Peningkatan Literasi Digital dalam Pembuatan Karya Tulis Guru Pada Platform Merdeka Mengajar (PMM) Sari, Ratna; Sari, Rafika; Ramdhania, Khairunnisa Fadhilla; Khalida, Rakhmi; Fitriyani, Aida; Novarizal, Safarin
Journal Of Computer Science Contributions (JUCOSCO) Vol. 5 No. 1 (2025): Januari 2025
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/nd864036

Abstract

This scientific article aims to evaluate a workshop held at SMP Negeri Satu Atap Cibarusah Bekasi to enhance the digital literacy of teachers. The workshop focused on creating written works in the form of Aksi Nyata Documents on the Merdeka Mengajar Platform (PMM), introducing and utilizing the Canva graphic design application and Gemini Artificial Intelligence to support the writing process. Participants were also trained on the structure of writing Aksi Nyata that meet PMM’s Writing Guidelines to ensure validation, as well as how to provide effective feedback for various types of Aksi Nyata. The workshop consisted of three main sessions: (1) Introduction to the Merdeka Mengajar Platform (PMM), (2) Tips for passing PMM Action Plan validation, and (3) Hands-on practice in creating written works aligned with the theme "Literacy Enhancing Student Competence." Evaluation results show that teachers gained increased understanding and skills in composing scientific articles that meet PMM standards and can use technology to improve the quality of their writing. This workshop significantly contributes to strengthening teachers' digital literacy and writing competence, which is expected to be applied in educational development at schools.
Pemanfaatan Artificial Intelligence (AI) Pada Penyusunan Aksi Nyata Platform Merdeka Mengajar di SDN Medalkrisna 01 Sari, Rafika; Sari, Ratna; Ramdhania, Khairunnisa Fadhilla; Juhanda
Journal Of Computer Science Contributions (JUCOSCO) Vol. 4 No. 2 (2024): Juli 2024
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/yme98582

Abstract

This training program is designed to enhance the competency of elementary school teachers in developing practical actions on the Merdeka Mengajar Platform (PMM) by utilizing Artificial Intelligence (AI) technology. Through the use of Turnitin for plagiarism checks and Gamma for document preparation, the program aims to ensure that the work produced is original and well-structured. The training involves teachers in intensive sessions that include the introduction and use of Turnitin to detect plagiarism, as well as Gamma to assist in preparing practical action documents that meet Kemendikbud's validation standards. The results of the training show a significant improvement in teachers' ability to produce creative, innovative, and compliant practical actions according to the assessment criteria. Teachers participating in this program can produce more professional and plagiarism-free documents, thanks to the constructive feedback from AI. Furthermore, the resulting practical action documents have a clear and attractive structure, facilitating the validation process. This program also encourages the formation of a learning community among teachers, where they share best practices and support continuous improvement. Thus, this training program not only enhances teachers' digital competence but also contributes to the overall improvement of education quality. The use of AI in education becomes an important step in preparing teachers to face challenges in the digital era.
Adaptasi Teknologi: Membangun Masyarakat yang Cakap Digital pada Kelurahan Marga Mulya Bekasi Hasan, Febri Zulfatian; Al Fajriy, Muhamad Fadilah; Pribadi, Janwar Irwansah; Hadi, Muhamad Habib Abfsan Maulana; Hasnandi, Azhar; Mahardika, Fauzan Naufaldy; Heikal, Muhammad Alvien; Al Bari, Naufal; Subakti, Rizky; Saputra, Rues Rizki; Ramdhania, Khairunnisa Fadhilla
Journal Of Computer Science Contributions (JUCOSCO) Vol. 5 No. 2 (2025): Juli 2025
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/1dvh7z40

Abstract

Marga Mulya Subdistrict, despite its considerable potential, faces challenges in achieving sustainable development, one of which is the lack of digital literacy. In particular, the limited understanding of digital security poses a significant challenge, especially in RW 02, where many residents own digital devices but remain vulnerable to risks such as the misuse of personal data and online fraud. Kuliah Kerja Nyata (KKN) conducted by UBHARAJAYA as part of the Merdeka Belajar Kampus Merdeka (MBKM) initiative aims to enhance the digital literacy skills of the local community. This program offers education on the wise, safe, and productive use of digital technology, along with training in the use of applications and social media platforms such as WhatsApp, TikTok, Instagram, and Shopee. Furthermore, the program instills awareness of digital security risks and methods to protect personal information. It is expected that through this initiative, the residents of RW 02 will be able to optimize their use of digital technology and build a smart and resilient digital community.
Agglomerative Spatial Clustering Analysis for Mapping Crime Risk Zone Clusters Munandar, Tb Ai; Ramdhania, Khairunnisa Fadhilla
International Journal of Information Technology and Computer Science Applications Vol. 3 No. 2 (2025): May - August 2025
Publisher : Jejaring Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58776/ijitcsa.v3i2.197

Abstract

Public safety and order are crucial aspects of social and economic life, especially in densely populated urban areas. High crime rates can undermine the sense of security and quality of life within society. Therefore, a deep understanding of crime distribution patterns is essential for designing effective prevention strategies. This study aims to map crime risk zones in Indonesia using the Agglomerative Clustering method, by integrating socio-economic and demographic variables. This method was chosen for its ability to group data based on similarity of characteristics, making it easier to identify areas with high-risk levels. The results show the formation of four main clusters that reflect crime risk distribution in Indonesia. The first cluster includes several provinces with similar crime patterns, while the other clusters reflect significant differences in crime patterns, particularly in Jakarta, which has very distinct criminal characteristics. This mapping provides valuable insights for the planning of more efficient, data-driven crime prevention policies. The research is expected to provide a strong foundation for policymakers and law enforcement agencies to formulate more targeted strategies to combat crime in Indonesia.
Co-Authors Aida Fitriyani, Aida Akbar, Iqbal Faris Al Bari, Naufal Al Fajriy, Muhamad Fadilah Hadi, Muhamad Habib Abfsan Maulana Hasan, Febri Zulfatian Hasnandi, Azhar Heikal, Muhammad Alvien Hidayat, Dian Fitrianto Juhanda Khalida, Rakhmi Kuning, Layung Lestari, Nur’aini Puji Mahardika, Fauzan Naufaldy Mugiarso Novarizal, Safarin Pratama, Aldira Ryan Pribadi, Janwar Irwansah Prima Dina Atika Rafika Sari Ramadhan, Alif Izzuddin Rasim Ratna Salkiawati Ratna Sari Saputra, Rues Rizki SITI SETIAWATI Subakti, Rizky Tb Ai Munandar, Tb Ai