Claim Missing Document
Check
Articles

Found 26 Documents
Search

Implementasi Aplikasi Pembelajaran Matematika Bangun Datar Bagi Siswa Sekolah Dasar Berbasis Android Sarwati Rahayu; Vera Yunita; Umniy Salamah
KILAT Vol 6 No 1 (2017): KILAT
Publisher : Sekolah Tinggi Teknik - PLN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (669.124 KB) | DOI: 10.33322/kilat.v6i1.670

Abstract

Mathematics is the study of quantity, structure, geometry, and changes to a number. Math comes from the Greek, which Mathematikos which means an exact science. In the Dutch language of mathematics called as Wiskunde which means the science of learning. Mathematics is a science that is widely used in everyday life. Either generally or specifically. In general, mathematics is used in the trade transaction, carpentry and others. Almost every aspect of the life of mathematics can be applied. Therefore mathematics dubbed as the queen of all sciences. Math also has many advantages over other sciences. In addition to its flexible and dynamic, mathematics can always keep pace with the times. Especially in the present when everything can be done with a computer. Mathematics became one language programs effectively and efficiently. Mathematics is a compulsory subject for primary school students. Elementary school students often have difficulty in studying mathematics, especially in memorizing formulas. The material presented is usually in the form of a conventional, such as textbooks. In Mathematics Learning Application Geometry Two Dimensional Based Android, automatically the application can be run through the medium of mobile phones. This learning app designed using object-oriented modeling, using UML diagrams such, Use Case diagram, activity diagram, sequence diagram and Class diagram. Applications are also made using the programming language Java (J2ME)
Automated Fruit Classification Menggunakan Model VGG16 dan MobileNetV2 Umniy Salamah; Anita Ratnasari; Sarwati Rahayu
JSAI (Journal Scientific and Applied Informatics) Vol 5 No 3 (2022): November 2022
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v5i3.3615

Abstract

Pengembangan robot atau mesin untuk membantu kegiatan pertanian memerlukan riset yang panjang. Teknologi tersebut harus dapat memiliki keahlian dalam melakukan berbagai macam aktivitas dan mampu mendeteksi objek yang menjadi sasaran pekerjaannya. Untuk memenuhi hal ini, riset untuk mendeteksi objek pertanian, misalnya buah, menjadi salah satu agenda riset yang perlu dilakukan dan dikembangkan. Tujuan penelitian ini adalah untuk mengetahui hasil perbandingan performa deep learning yaitu VGG16 dan MobileNetV2 untuk fruit classification. Penelitian ini menggunakan dataset dengan jumlah total 90.483 data dengan ukuran gambar 100x100 piksel dan jumlah kelas tanaman buah yang akan diklasifikasi adalah sebanyak 131 kelas. Pada proses testing menggunakan dataset yang ada, MobileNetV2 mendapatkan akurasi 98.4% dan ResNet50 mendapatkan akurasi 99,2%.
Model Sequential Resnet50 Untuk Pengenalan Tulisan Tangan Aksara Arab Sarwati Rahayu; Sulis Sandiwarno; Erwin Dwika Putra; Marissa Utami; Hadiguna Setiawan
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 2 (2023): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i2.5379

Abstract

Research for Arabic handwriting recognition is still limited. The number of public datasets regarding Arabic script is still limited for this type of public dataset. Therefore, each study usually uses its dataset to conduct research. However, recently public datasets have become available and become research opportunities to compare methods with the same dataset. This study aimed to determine the implementation of the transfer learning model with the best accuracy for handwriting recognition in Arabic script. The results of the experiment using ResNet50 are as follows: training accuracy is 91.63%, validation accuracy is 91.82%, and the testing accuracy is 95.03%.
PENGORGANISASIAN FILE MENGGUNAKAN GOOGLE DRIVE DAN COLABORATION FILE DI POSYANDU KELURAHAN MERUYA UTARA Andi Nugroho; Ratna Mutu Manikam; Sarwati Rahayu; Achmad Kodar
Jurnal Pengabdian Masyarakat Nasional Vol 2, No 2 (2022)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/pemanas.v2i2.17790

Abstract

Saat ini sudah banyak sekali aplikasi yang dibuat serta dikembangkan untuk memenuhi kebutuhan manusia seperti halnya aplikasi MS Office yang hingga saat ini sudah versi MS Office 2016 dan MS Office 365, serta adapun aplikasi open source nya seperti Open Office, Libre Office, KMS, dan yang terbaru kali ini adalah aplikasi dari cloud yang diberinama google doc, dengan teknologi cloudnya yang diberi nama google drive. Aplikasi cloud yang akan digunakan adalah google doc spreed sheet. Posyandu merupakan pelaynan kesehatan yang dimiliki oleh masing-masing kecamatan dan kelurahan di seluruh Indonesia. Terutama pada Posyandu pada Kelurahan Meruya Utara. Posyandu ini dalam menyampaikan laporan kesehatan warga disetiap RT dengan melampirkan catatan yang telah ditulis oleh petugas Posyandu. Kemudian petugas Kelurahan Meruya Utara pun sudah tidak perlu lagi menginput data cukup langsung mengumpulkan datanya dari setiap kelurahan dan dikirimkan ke Kementrian kesehatan, dan proses penyampaian laporan selesai dilakukan. Dengan adanya pengabdian kepada masyarakat di Kelurahan Meruya Utara maka para Kader Posyandu sudah mengetahui pemanfaatan google drive dalam menyimpan data bayi dan balita.
SOSIALISASI PENGGUNAAN APLIKASI GOOGLE CLASSROOM DALAM MENDUKUNG KEGIATAN BELAJAR MENGAJAR SISWA DI RUMAH Andi Nugroho; Ratna Mutu Manikam; Sarwati Rahayu
PEMANAS: Jurnal Pengabdian Masyarakat Nasional Vol 2, No 1 (2022)
Publisher : PEMANAS: Jurnal Pengabdian Masyarakat Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/pemanas.v2i1.15179

Abstract

Aplikasi Google Classroom adalah aplikasi yang dikembangkan oleh raksasa aplikasi Google. Aplikasi Google Classroom saat ini digunakan oleh guru-guru sekolah baik tingkat sekolah dasar hingga sekolah menengah umum untuk disampaikan soal-soal yang akan dikerjakan maupun untuk materi yang disampaikan oleh guru. Orang tua siswa wajib mengetahui secara keseluruhan aplikasi Google Classroom seperti menjawab soal, membuat komentar, ataupun bertanya ke guru. Tidak hanya itu aplikasi Google Classroom juga dapat digunakan oleh pihak sekolah untuk mengambil nilai siswa-siswanya dari ulangan harian hingga ujian. Adapun aplikasi Google Classroom ini sangat populer dimasa pandemi covid 19 seperti saat ini guna mendukung proses elajar mengajar. Selain itu para orang tua murid yang dalam hal ini diwakili oleh Ibu Pembinaan Kesejakteraan Keluarga (PKK), diharuskan mengetahui proses belajar mengajar dengan aplikasi tersebut. Hal ini yang menjadi tujuan dibuatnya pengabdian kepada masyarakat ini mengenai penggunaan aplikasi Google Classroom guna menunjang proses belajar mengajar dimasa pandemi Covid 19.
Sosialisasi Pemanfaatan Bahan Ajar Berbasis Multimedia Bagus Priambodo; Nur Ani; Sarwati Rahayu; Rinto Priambodo; Inge Handriani; Anita Ratnasari; Yuwan Jumaryadi; Nia Rahma Kurnianda
Journal of Social Responsibility Projects by Higher Education Forum Vol 4 No 2 (2023): November 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jrespro.v4i2.4187

Abstract

Today's rapidly developing technology makes it easier for humans to do their work. Education is the main thing in educating children in a country so that they can perform well and in accordance with normative values. In the world of education we can do many things as a source of learning not only books, but also by utilizing the environment around us. Apart from the environment, we can also use digital media as a source of learning to make it easier. The development of a curriculum has always been the main focus and continues to be carried out to improve and respond to community needs so that the socialization of the use of multimedia applications is felt to be very useful for improving the quality of learning media. In this community service activity, we conducted socialization regarding the use of several multimedia applications at the Early Childhood Education Cluster Activity Center (PKG) in Sukaraja District. Based on the results of the questionnaire given after the activity, the activities carried out were very useful to support the teaching activities carried out.
Komparasi Hasil Color Feature Extraction HSV, LAB dan YCrCb pda Algoritma SVM untuk Klasifikasi Spesies Burung Sarwati Rahayu; Andi Nugroho; Erwin Dwika Putra; Mariana Purba; Hadiguna Setiawan; Sulis Sandiwarno
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 3 (2023): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i3.5920

Abstract

The classification of bird species is a problem often faced by ornithologists, and has been considered scientific research since antiquity. This study aims to evaluate the results of color feature extraction including HSV, LAB and YCrCb against the results of the SVM classification. In addition, the results of this study are useful to determine the performance of color feature extraction that is suitable for bird species classification. The dataset used was 22,617 bird species images. Based on experimental results, the effect of HSV on the SVM classification caused a decrease in accuracy by -0.33% while LAB and YCrCb on the SVM classification caused an increase in accuracy of 0.44% and 0.21%. However, the accuracy of the SVM classification does not yet have good performance so that further research will be carried out using other classifications, including convolutional neural networks and others.
Analisis Performa Metode Klasifikasi Dataset Multi-Class Kanker Kulit Menggunakan KNN dan HOG Rahayu, Sarwati; Sandiwarno, Sulis; Dwika Putra, Erwin; Utami, Marissa; Setiawan, Hadiguna
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 2 (2024): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i2.6423

Abstract

Detection of skin cancer in its early phase is a challenge even for dermatologists. This study aims to analyze the performance of classification methods on multiclass skin cancer datasets using K-nearest neighbor (KNN) and histogram of oriented gradients (HOG). The dataset is taken publicly under the name Skin Cancer MNIST dataset: HAM10000 dataset totaling 10,015 data. The first experiment used the pixels per cell parameter of 8.8 and cells per block of 2.2 to get an accuracy of 60.58%. The second experiment used the pixels per cell parameter of 8.8 and cells per block of 2.2 to get an accuracy of 60.58%. The last experiment using the pixels per cell parameter of 8.8 and cells per block of 2.2 got the best accuracy of 61.43%.
Analisis Usabilitas Sistem Informasi Akademik Berdasarkan Usability Scale (Studi Kasus: Universitas Mercu Buana) Rahayu, Sarwati; Nugroho, Andi; Sandiwarno, Sulis; Salamah, Umniy; Dwika Putra, Erwin; Purba, Mariana; Setiawan, Hadiguna
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7478

Abstract

The usability analysis on the website of Mercu Buana University (UMB) is an important research carried out to ensure that the site effectively supports the university's goals, especially in terms of the user's experience in completing academic and administrative goals with ethical and professional standards. This research was carried out during the period January 2024 to May 2024. The main purpose of this study is to measure the usability of the UMB website using a questionnaire method. The questionnaire used for the research adapted the System Usability Scale (SUS) which consisted of a total of 10 questions. Based on the calculation of each statement item having a minimum score of 0 and a maximum score of 2.5, the final score of each respondent ranged from 0 to l00. The average score obtained was 63,125. Based on the results of the score of 63,125, the UMB website has a score in the range of 50 to 70. This shows that the UMB website is in the "quite good" category but there is still a need for a little improvement. Some icons or layouts on the UMB website are not familiar to respondents. In addition, there needs to be guidelines developed to provide information on how to use the website for users who are using the UMB website for the first time.
Application of Random Contrast and Brightness Range Methods on Phytomedicine Leaf Image Dataset Purba, Mariana; Ayumi, Vina; Rahayu, Sarwati; Salamah, Umniy; Handriani, Inge; Farida, Ida
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 2 (2025): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i2.8766

Abstract

This study aimed to enhance the performance of deep learning models in detecting and classifying medicinal plant leaf images by applying two data augmentation techniques, namely Random Contrast Augmentation (RCA) and Brightness Range Augmentation (BRA). The RCA technique randomly adjusted the contrast of images by calculating the pixel average and modifying each pixel value based on a contrast factor, thereby increasing the variation in image lighting. Meanwhile, BRA randomly altered the brightness of the images to simulate varying lighting conditions. The research process began with the collection of medicinal plant leaf image datasets, which were then divided into three parts: training data, validation data, and testing data. The dataset was then pre-processed to prepare the images before applying the augmentation. Augmentation techniques were employed to enrich the dataset by generating modified copies of images using RCA and BRA techniques. The application of both augmentation techniques resulted in a training dataset of 2,400 images, 300 validation images, and 300 testing images.