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All Journal M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika QISTINA: Jurnal Multidisiplin Indonesia Indonesian Journal of Education and Development Research
Rahmi, Alya
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Religion Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Social Sciences Other

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Urgensi Peran Gubernur dalam Sistem Pemerintahan: Menjaga Stabilitas Politik dan Ekomoni Daerah Rahmi, Alya; Ginting, Ariyantika Br; Mardhiyah, Hanifah; Ami, Hutri; Tanzila, Laili
Indonesian Journal of Education and Development Research Vol 3, No 1 (2025): Januari 2025
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/ijedr.v3i1.4657

Abstract

Gubernur menempati posisi strategis dalam sistem pemerintahan Indonesia sebagai penghubung antara pemerintah pusat dan daerah. Dalam konteks ini, gubernur tidak hanya berperan sebagai penegak kebijakan pusat, namun juga menjaga stabilitas politik dan ekonomi daerah. Artikel ini mengkaji peran tersebut dengan pendekatan deskriptif analitis, dengan fokus pada tantangan yang dihadapi gubernur dalam menjaga keharmonisan politik, mengelola pembangunan ekonomi, dan menjamin keberlanjutan pembangunan daerah. Analisis menunjukkan bahwa stabilitas politik dan ekonomi yang sehat sangat bergantung pada kemampuan gubernur dalam berinovasi dan membangun sinergi dengan pemangku kepentingan. Rekomendasi kebijakan mencakup peningkatan otonomi fiskal dan penguatan kapasitas gubernur dalam manajemen krisis dan pengambilan keputusan strategis.
Developing a Desktop-Based OSI Model Interactive Learning Application Using VB.NET Syahputra, Fahmy; Putri, Tansa Trisna Astono; Mardhiyah, Hanifah; Saragi, Frans Jhonatan; Rahmi, Alya
QISTINA: Jurnal Multidisiplin Indonesia Vol 3, No 2 (2024): December 2024
Publisher : CV. Rayyan Dwi Bharata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57235/qistina.v3i2.4227

Abstract

This research focuses on developing a desktop-based learning application to help students understand the concept of OSI Model using VB.NET. The purpose of this application is to provide interactive learning media that can facilitate understanding of the seven layers of OSI and the process of data transmission in the network. This research applies the Waterfall method, starting from requirements analysis, system design, implementation, testing, to the operation and maintenance stage. The development results show that this application is equipped with structured learning material features, evaluation quizzes, and user-friendly navigation. The application trial shows performance in accordance with the design, where the quiz evaluation feature is able to provide an accurate assessment of student understanding. In conclusion, this learning application can be an innovative solution in the delivery of OSI Model material, with further development opportunities that include the addition of interactive simulations and support for mobile devices.
Classification Of KIP-K Scholarship Using Logistic Regression, Classification Trees, and Boosting Based On Decision Support System Wizsa, Uqwatul Alma; Rahmi, Alya
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 10 No. 1 (2025): Mathline : Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v10i1.837

Abstract

This study addresses the challenge of accurately identifying eligible awardees of the KIP-K scholarship at UIN Sjech M. Djamil Bukittinggi, where scholarship aid requests exceed the allocated funds. The research aims to develop an integrated classification and decision-making model to optimize the selection process. From the 2022 and 2023 scholarship applicant data obtained through AKAMA, preprocessing was conducted, resulting in a final dataset comprising 2,144 records. The dataset includes 14 explanatory variables influencing scholarship eligibility. The study compares three classification methods—logistic regression, classification tree, and boosting—using the 2022 data for training and testing. The SMOTE resampling technique was applied to address class imbalance. The novelty of this research lies in integrating classification analysis with a decision-making system based on the Simple Additive Weighting (SAW) method, enhancing the ranking of applicants based on criteria. The results indicate that logistic regression delivered the best performance in terms of accuracy, sensitivity, and AUC-ROC scores during testing, despite a slight decline in performance when applied to the 2023 dataset. Moreover, integrating logistic regression with SAW significantly improved decision-making precision. The application of logistic regression combined with SAW on the 2023 dataset resulted in a final accuracy of 0.5734 and a balanced accuracy of 0.5820. This integrated framework provides a data-driven, fair, and efficient approach to scholarship allocation. The study highlights the importance of combining predictive models with decision-making systems to ensure equitable and targeted distribution of financial aid to deserving students.
Co-Authors Ami, Hutri Ginting, Ariyantika Br Mardhiyah, Hanifah Putri, Tansa Trisna Astono Saragi, Frans Jhonatan Syahputra, Fahmy Tanzila, Laili Wizsa, Uqwatul Alma