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All Journal Jurnal Ilmiah Kursor Jurnal IPTEK
Putri, Ika Kusumaning
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering Mechanical Engineering

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STUDENT ACADEMIC PERFORMANCE PREDICTION FRAMEWORK WITH FEATURE SELECTION AND IMBALANCED DATA HANDLING Wijayaningrum, Vivi Nur; Kirana, Annisa Puspa; Putri, Ika Kusumaning
Jurnal Ilmiah Kursor Vol. 12 No. 3 (2024)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/kursor.v12i3.356

Abstract

Various factors cause the low scores of students in practicum courses. If these factors cannot be identified, more and more students will drop out of the study due to low scores, especially Vocational College students who do not have the opportunity to improve their scores in the short semester. Students with the potential to drop out must be identified as soon as possible because the number of dropouts can have an impact on a university's accreditation value. In this study, the prediction of student academic performance was carried out using a framework consisting of imbalanced data handling using SMOTE and feature selection using Random Forest, as well as the application of Multi-Layer Perceptron (MLP) for the formation of a classification model. The MLP architecture consists of some neurons in the input layer, two hidden layers with five neurons each, and two neurons in the output layer. SMOTE succeeded in selecting ten significant parameters from 22 initial parameters, which produced the most accurate predictions. According to the test results, the proposed framework offers the best accuracy of 0.8889 and an F1-Score of 0.9032. These results prove that the proposed framework can be used as an alternative for the Department to take action to prevent students from dropping out.
Implementation of Hot Code Update in Hybrid Mobile Development Using Dynamic Bundle Loading Arhandi, Putra Prima; Putri, Ika Kusumaning; Zaka, Muhammad Nindra
Jurnal IPTEK Vol 26, No 2 (2022)
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2022.v26i2.2372

Abstract

Setiap kali developer akan merilis update pada aplikasi mobile, update tersebut akan ditinjau terlebih dahulu oleh marketplace. Sehingga membutuhkan waktu tambahan agar update tersebut bisa sampai ke user. Lamanya proses peninjauan ini bisa menjadi masalah apabila ada perbaikan pada fitur aplikasi yang harus segera diterima oleh user. Sehingga dibutuhkan cara agar user dapat menerima update pada aplikasi mobile tanpa harus menunggu tinjauan dari marketplace. Hot code update merupakan metode yang dapat menambahkan dan memperbaiki fitur pada aplikasi tanpa perlu ditinjau terlebih dahulu oleh marketplace. Dynamic Bundle Loading merupakan salah satu penerapan dari metode hot code update yang dapat diimplementasikan pada hybrid mobile development. Developer akan mengunggah source code javascript terbaru ke server dalam bentuk bundle. Kemudian aplikasi akan mengunduh dan menerapkan fitur - fitur yang ada pada bundle tersebut. Pada penelitian ini akan dibuat sistem untuk menerapkan hot code update menggunakan dynamic bundle loading pada hybrid mobile development menggunakan framework react native.  Hasil dari penelitian menunjukkan bahwa metode hot code update dapat merilis update kepada user dengan lebih cepat daripada mengunggah update melalui google play store  dengan selisih waktu 4 jam 39 menit 54 detik. Selain itu, ukuran file update yang harus diunduh oleh user lebih kecil apabila menggunakan metode hot code update dengan selisih 6.1 MB
Co-Authors Annisa Puspa Kirana Putra Prima Arhandi, Putra Prima Vivi Nur Wijayaningrum Zaka, Muhammad Nindra