<p>Salah satu penyebab dari lamanya waktu tempuh mahsiswa di Jurusan Informatika UPN “Veteran” Jawa Timur adalah sullitnya memantau kemajuan studi mahasiswa secara seksama, mengingat jumlah mahasiswa yang cukup banyak serta pihak akademik belum memiliki metode yang akurat untuk memetakan mahasiswa yang diprediksi akan mengalami keterlambatan dalam penyelesaian studinya. Melalui perkembangan teknologi informasi yang berkembang pesat saat ini, maka sangat dimungkinkan untuk membuat sebuah sistem yang mampu memprediksi kemungkinan keterlambatan kelulusan mahasiswa melalui penggunaan berbagai metode komputasi yang ada. Salah satu pendekatan yang dapat digunakan untuk membuat sebuah sistem prediksi kelulusan adalah menggunakan pendekatan populer yang digunakan dalam pembuatan sistem cerdas <em>(intelligent system) </em>yaitu <em>case based reasoning </em>(CBR). Langkah-langkah yang dilakukan pada penelitian ini adalah melakukan pengumpulan dan memasukkan data kasus pada basis kasus, melakukan praprosesing yakni normalisasi atribut yang akan digunakan dalam perhitungan similartitas antar kasus menggunakan normalisasi min-max, implementasi CBR menggunakan metode Euclidean Distance, serta melakukan pengujian pada 141 data kasus. Dari sisi perhitungan akurasi, sistem mampu memberikan nilai akurasi paling tinggi sebesar 100% pada pada pengujian berdasarkan predikat kelulusan, sedangkan berdasarkan ketepatan waktu, sistem mampu memberikan akurasi tertinggi dengan nilai 85,71%, dan sistem mampu memberikan nilai akurasi tertinggi sebesar 71,43% pada pengujian berdasarkan massa studi. Untuk pengujian presisi, sistem mampu mengasilkan nilai terbesar berturut-turut sebesar 90,90%, 43,33%, dan 100%. Sedangkan pada pengujian sensitivitas, sistem berturut-turut mampu menghasilan nilai sebesar 90,90%, 40,48%, dan 100%. Hasil pengujian ini tentunya sangat bergantung dari basis kasus yang dimiliki, oleh sebab itu perbaikan dan peningkatan jumlah kasus yang dimiliki diharapkan mampu meningkatkan performa sistem rekomendasi.</p><p> </p><p><strong><em>Abstract</em></strong></p><p class="Judul2"><em>One of the reasons for the length of study time for students of the Informatics study program of UPN "Veteran" </em><em>Jawa Timur</em><em> is the difficulty of monitoring the progressy, given the large number of students and academics do not have an accurate method to map students who are predicted to experience delays. </em><em>I</em><em>t is possible to create a system that is able to predict the possibility of student graduation delay through the use of various existing computational methods. One approach that can be used to create a graduation prediction system is to use the popular approach namely case based reasoning (CB).</em><em> </em><em>The steps taken in this study are collecting and entering case data, normalizing the attributes using min-max normalization, implementing CBR using the Euclidean Distance, and system testing</em><em> in 141 data case</em><em>.</em><em> </em><em>Sy</em><em>stem is able to provide the highest accuracy value of 100% in testing based on the predicate of graduation, while based on timeliness, the system is able to provide the highest accuracy value with a value of 85.71%, and the system is able to provide the highest accuracy value of 71.43%. on testing based on the study period. For precision testing, the system was able to produce the largest values of 90.90%, 43.33% and 100%, respectively. Whereas in the sensitivity test, the system was able to produce values of 90.90%, 40.48%, and 100% respectively. The results of this test are of course very dependent on the basis of cases that are owned, therefore improvements and an increase in the number of cases owned are expected to be able to improve the performance.</em></p><p><strong><em><br /></em></strong></p>
During the COVID-19 pandemic, teaching and learning activities must be carried out online from home. The development of technology today really helps the online teaching and learning process, there are many tools / software that can be used. Tools / software commonly used in online teaching and learning activities are Ms. Word, Ms. Power Point, and Virtual Lab. Another impact of technological developments coupled with pandemic conditions has led to more interactions between humans being carried out online through internet intermediaries on cellphones or computers. Currently cellphones do not only function as a medium of communication, some work that was previously completed using a computer / laptop can now be completed using a smart phone. So that cellphones can be used for more positive activities and support the teaching and learning process, sharing is carried out with students through sharpening design creativity through mobile applications on smart phones. In this activity, students hone graphic design skills using the CANVA application to support the teaching and learning process. The enthusiasm of students is quite high, as evidenced by the work produced in the form of personal profile designs, extracurricular activities and logos. Students can practice well the material presented. The school welcomes this activity, and wants to form an extracurricular Graphic Design at SMA Dharma Wanita so that it becomes a forum for student creativity in graphic design.
Global and local thresholding are two thresholding approaches for white blood cell (WBC) image segmentation. Global thresholding determines the threshold value based on the histogram of the overall pixel intensity distribution of the image. In contrast, adaptive thresholding computes the threshold value for each fractional region of the image, so that each fractional region has a different threshold value. In this work, we are assessing both of these approaches for two threshold values. We extended the Otsu’s equation to calculate more than one threshold as it originally designed to find only a single threshold value. Adaptive thresholding first divides an image into fractional-image by considering an imaginary bounding box that surrounds the location of WBC, which involves the Gram-Schmidt orthogonalization method. For segmentation performance evaluation, we compare 35 blood smear test images which segmented by our proposed method, with their corresponding ground truth image to representing them in Zijdenbos Similarity Index (ZSI), precision, and recall measurement. Experimental results show that adaptive thresholding achieves average ZSI, precision and recall, 92.5%, 91.79%, 94.03%, while global thresholding achieves 30.72%, 23.38%, and 99.39% respectively.
Model-View-Controller (MVC) design pattern is design pattern that is suitable for interactive systems. MVC is adapted in desktop and web-based applications. Moreover, many frameworks are adapting MVC pattern. Each layer of MVC has a different function. The main function of the model layer is query to the database system that represented by SQL language. In software development, code duplication or code clone is a serious problem because it will impact on the maintenance process. Associated with model layer and code clone, clone detection approach that exists today is not effective to detect clones in the model layer represented by SQL language, because the definition of code clone is not suitable for SQL clone. SQL is declarative language that is different from the common programming language like C and Java. So, the definition of code clone must be adjusted with characteristic of SQL. In this research, we investigate the existence of SQL clone on MVCbased application and define the types of SQL clone. We define four types of SQL clone and they are confirmed exist in MVCbased application datasets that used in this research.
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