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All Journal Jurnal Komputer Terapan Majalah Ilmiah Warta Dharmawangsa DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY
Nasution, Mardiah
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Biochemistry, Genetics & Molecular Biology Computer Science & IT Education

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SISTEM INFORMASI PENGIRIMAN BARANG PADA PT. POS INDONESIA BERBASIS WEB Zhafar, Raihan; Zulham, Zulham; Prayoga, J.; Nasution, Mardiah
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 4, No 2: DESEMBER 2023
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v4i2.4045

Abstract

Tujuan merancang Sistem Informasi pengiriman barang berbasis web untuk Mempermudah admin,bagian gudang dan bagian finance dalam membuat laporan. Adapun Program yang digunakan dalam penulisan Tugas Akhir ini berbasis web yang menggunakan php sebagai basis datanya serta xampp sebagai penghubungnya. Sistem informasi pengiriman barang berbasis web ini timbul pada saat penulis melakukan observasi, maka diharapkan sistem informasi pengiriman barang ini dapat membantu admin, bagian gudang serta bagian finance dan memberikan solusi yang terbaik bagi perusahaan. Hasil program ini menunjukkan bahwa perangkat lunak dengan basis data yang terhubung sehingga dapat menyimpan berbagai arsip dan informasi yang dibutuhkan. Aplikasi ini mencangkup sistem pengiriman barang, penempatan barang pada gudang serta laporan yang dapat di pindahkan kedalam excel. Kata kunci : Pengiriman barang, sistem informasi, web
Oversampling Menggunakan Pendekatan Latin Hypercube Sampling Dan K-Nearest Neighbors Untuk Meningkatkan Kinerja Klasifikasi Sapriadi, Sapriadi; Nasution, Mardiah
Jurnal Komputer Terapan Vol 10 No 2 (2024): Jurnal Komputer Terapan
Publisher : Politeknik Caltex Riau

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Abstract

Class imbalance in datasets is a significant challenge in machine learning, often leading to a decline in model performance. This issue is frequently encountered in real-world data, where the proportion between majority and minority classes is highly imbalanced. One common approach to address this problem is oversampling, which aims to balance class distribution by adding synthetic data to the minority class. The most popular oversampling technique is the Synthetic Minority Oversampling Technique (SMOTE), although this method has drawbacks such as producing less diverse data and the potential generation of outliers. As an alternative solution, this study proposes the use of the Latin Hypercube Sampling (LHS) method combined with k-Nearest Neighbor (k-NN) to enhance classification performance on imbalanced datasets. The combination of LHS and k-NN is expected to produce higher quality synthetic data, thereby improving the performance of classification models measured using the confusion matrix. The data used in this study is sourced from various online repositories such as KEEL, Kaggle, UCI, as well as the student specialization of vocational high school (SMK) students in Pekanbaru
PERANCANGAN PERANGKAT LUNAK PENGOLAHAN DATA ALUMNI PADA SMK BM TARBIYAH ISLAMIYAH Nuriana, Ayu; Nasution, Mardiah; Prayoga, J.
Jurnal Warta Dharmawangsa Vol 17, No 3 (2023)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/wdw.v17i3.3590

Abstract

Co-Authors J. Prayoga, J. Prayoga Nuriana, Ayu Sapriadi, Sapriadi Zhafar, Raihan Zulham Zulham