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All Journal Jurnal Penelitian Ilmiah INTAJ Journal of Electronics, Electromedical Engineering, and Medical Informatics
Vina Maulida, Vina
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Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Social Sciences

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SANTRI DAN MULTIKULTURALISME Roihanah, Roihanah; Husna, Ma’rifatul; Maulida, Vina
INTAJ Vol 1 No 1 (2017): #1
Publisher : LP3M IAI Al-Qolam

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (310.618 KB) | DOI: 10.6084/intaj.v1i1.42

Abstract

Sambas conflict in 1997 and 1999 caused big number of refugees, mainly Madureses, which spread in various regions. Many young refugees were sheltered at Islamic boarding schools (pondok pesantren), especially in East Java. They usually got special treatment, from financial dispensation to psychological assistance. One pondok pesantren accommodating the Victims of Sambas conflict was Raudlatul Ulum 1 Ganjaran Gondanglegi Malang. Although it did not have particular program to handle those young victims, a number conflict victims were found. The research problems are formulated as follows: (1) how is the Sambas conflict victims’ perception on multiculturalism at Islamic boarding School Raudlatul Ulum 1; (2) what is the role of the boarding school in the formation of their perception on multiculturalism? It is a field research with qualitative approach. This research resulted that the conflict which the victims had experienced in Sambas had provided deep trauma, especially psychologically one. Their mentality and perceptions are also affected significantly, especially shortly after the conflict. This is noticed from their fear of meeting with people from different ethnicity, especially Dayak and Melayu. But over time, the trauma turned into an understanding that the conflicts occurred because of economic interest or because of political engineering based on the interests of the rulers. One of the factors that shape their perception of this conflict is pondok pesantren. Its environment and the education system significantly affected their perception. Pondok pesantren inhabited by the students with quite vast of race, ethnicity or language, thereby building tolerance between them, while its education system could build the character of leaders who are ready to protect the society with all its diversity.
Feature Selection Using Firefly Algorithm With Tree-Based Classification In Software Defect Prediction Maulida, Vina; Herteno, Rudy; Kartini, Dwi; Abadi, Friska; Faisal, Mohammad Reza
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 4 (2023): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v5i4.315

Abstract

Defects that occur in software products are a universal occurrence. Software defect prediction is usually carried out to determine the performance, accuracy, precision and performance of the prediction model or method used in research, using various kinds of datasets. Software defect prediction is one of the Software Engineering studies that is of great concern to researchers. This research was conducted to determine the performance of tree-based classification algorithms including Decision Trees, Random Forests and Deep Forests without using feature selection and using firefly feature selection. And also know the tree-based classification algorithm with firefly feature selection which can provide better software defect prediction performance. The dataset used in this study is the ReLink dataset which consists of Apache, Safe and Zxing. Then the data is divided into testing data and training data with 10-fold cross validation. Then feature selection is performed using the Firefly Algorithm. Each ReLink dataset will be processed by each tree-based classification algorithm, namely Decision Tree, Random Forest and Deep Forest according to the results of the firefly feature selection. Performance evaluation uses the AUC value (Area under the ROC Curve). Research was conducted using google collab and the average AUC value generated by Firefly-Decision Tree is 0.66, the average AUC value generated by Firefly-Random Forest is 0.77, and the average AUC value generated by Firefly-Deep Forest is 0, 76. The results of this study indicate that the approach using the Firefly algorithm with Random Forest classification can work better in predicting software damage compared to other tree-based algorithms. In previous studies, tree-based classification with hyperparameter tuning on software defect prediction datasets obtained quite good results. In another study, the classification performance of SVM, Naïve Bayes and K-nearest neighbor with firefly feature selection resulted in improved performance. Therefore, this research was conducted to determine the performance of a tree-based algorithm using the firefly selection feature.
Co-Authors Dwi Kartini, Dwi Friska Abadi Herteno, Rudy Ma’rifatul Husna, Ma’rifatul Muhammad Reza Faisal, Muhammad Reza Roihanah Roihanah, Roihanah