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All Journal JUSIFO : Jurnal Sistem Informasi JSiI (Jurnal Sistem Informasi) Jurnal Teknik Informatika (JUTIF) Walisongo Journal of Information Technology
Siti Nur’aini
Universitas Islam Negeri Walisongo
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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Pengenalan Deoxyribonucleic Acid (DNA) Dengan Marker-Based Augmented Reality Siti Nur’aini; Arnia Sari Mukaromah; Siti Muhlisoh
Walisongo Journal of Information Technology Vol 1, No 2 (2019): Walisongo Journal of Information Technology
Publisher : Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/wjit.2019.1.2.4531

Abstract

Proses belajar yang baik harus memuat aspek interaktif, memotivasi, menyenangkan dan memberikan ruang bagi siswa untuk dapat mengembangkan kreativitas dan kemandirian. Siswa kadangkala merasa kesulitan pada saat mengillustrasikan isi pembelajaran yang berupa pengetahuan konsep dan prosedur. Dalam pelajaran biologi, materi terkait konsep dasar struktur Deoxyribonucleic Acid (DNA) merupakan materi yang bersifat teoritik dan abstrak. Pemahaman konsep seperti ini  memerlukan penggambaran dan modelling yang lebih realistik agar mudah dipahami. Visualisasi dari sumber belajar dan media belajar yang ada sudah dapat membantu  mempermudah pemahaman  konsep, tetapi variasi media yang lebih nyata, menarik, dan kekinian diharapkan dapat lebih meningkatkan minat siswa.  Pengembangan aplikasi Augmented Reality dapat menjadi salah satu alternatif media pembelajaran DNA. Aplikasi ini dikembangkan dengan metode ADDIE menggunakan Unity3D dan Vuforia. Hasil pengujian fungsional menunjukkan semua fitur dapat berjalan dengan baik sesuai dengan kebutuhan di berbagai versi sistem operasi android. Sedangkan pengujian usability menunjukkan kepuasan mahasiswa sebanyak  86% yang artinya aplikasi ini dapat membantu mahasiswa dalam memahami materi DNA.
Steganografi Pada Digital Image Menggunakan Metode Least Significant Bit Insertion Siti Nur’aini
Walisongo Journal of Information Technology Vol 1, No 1 (2019): Walisongo Journal of Information Technology
Publisher : Universitas Islam Negeri Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/wjit.2019.1.1.4025

Abstract

Steganography is a way to hide messages or confidential data in a medium called a carrier file. Embedding is done by the Least Significant Bit Insertion method, which is to replace the lowest bit of Red Green Blue (RGB) each pixel with the data bit you want to insert. With this method the difference between pixels that have not been pasted by messages and pixels that have been pasted by messages cannot be distinguished by human eye sight. Because the LSB insertion method is used, it is necessary to consider the type of digital image format used, this is necessary to avoid the loss of messages when extracting. And the best digital image format used is the 24-bit BMP because the BMP format is lossless compression
AUGMENTED REALITY FOR UNIVERSITAS ISLAM NEGERI WALISONGO'S PROFILE USING AGILE METHODOLOGY Siti Nur’aini; Muhammad Naufal Muhadzib Al-Faruq
Jurnal Teknik Informatika (Jutif) Vol. 3 No. 4 (2022): JUTIF Volume 3, Number 4, August 2022
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jutif.2022.3.4.519

Abstract

The use of Information Technology for the process of delivering information has grown so rapidly. One of them is Augmented Reality. Augmented Reality is widely implemented for various things, including in the world of education, health, military, entertainment and many others. Augmented Reality is a technology that combines virtual objects and the real world in real-time and interactively. This research developed an Augmented Reality Application that can be used to introduce Universitas Islam Negeri (UIN) Walisongo more broadly, attractively, interactively, and competitively. This application is named AR UINWS. Agile methodology was chosen to develop AR UINWS. The results show that the agile methodology is suitable to be implemented because of its flexibility, so that the needs of developing applications can be easily adapted. AR UINWS works well on all types of android devices that have a minimum camera resolution of 720x1280 pixels. AR UINWS can detect markers if the marker surface is visible at least 65% of the total marker surface area. This application can detect markers of various sizes as long as the background is light. The size of the marker that can be detected is 1.5x2 cm with the minimum distance between the marker and the android device is 1 5cm. While the largest marker size being tested is 15x23cm with the minimum distance between the marker and the android device is 150 cm.
Sentiment Analysis on WeTV Application Reviews Using Naïve Bayes: A Study of Preprocessing, Balancing, and Model Performance Wilis Brawijaya; Khothibul Umam; Siti Nur'aini; Maya Rini Handayani
JUSIFO : Jurnal Sistem Informasi Vol 11 No 1 (2025): June
Publisher : Program Studi Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Islam Negeri Raden Fatah Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19109/jusifo.v11i1.27925

Abstract

This study investigates the application of the Naïve Bayes classification algorithm for sentiment analysis of user-generated reviews on the WeTV application available on the Google Play Store. A structured methodology was employed, consisting of data scraping, sentiment labeling based on heuristics, multi-stage preprocessing, class balancing using Synthetic Minority Over-sampling Technique (SMOTE), and performance evaluation through standard metrics. Prior to balancing, the model exhibited strong performance on the dominant class but underperformed on the minority class. The introduction of SMOTE led to improved F1-scores, particularly for positive sentiment, increasing from 61% to 64%, while maintaining overall accuracy around 71%. These findings confirm that Naïve Bayes, when supported by effective preprocessing and data balancing, can deliver robust and interpretable classification results in text mining tasks. This research contributes to the growing literature on machine learning for opinion mining and provides practical implications for developers aiming to extract structured insights from large-scale user reviews.
Evaluasi Efektivitas Support Vector Machine dan Random Forest dalam Klasifikasi Ulasan Pengguna Aplikasi Streaming Vidio Fastabiqul Khusna; Khothibul Umam; Siti Nur'aini; Maya Rini Handayani
Jurnal Sistem Informasi Vol. 12 No. 2 (2025)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v12i2.10495

Abstract

Perkembangan pesat platform streaming telah menghasilkan banyak ulasan pengguna yang dapat dimanfaatkan sebagai sumber masukan untuk pengembangan aplikasi. Penelitian ini dilakukan untuk mengevaluasi kinerja algoritma Support Vector Machine (SVM) dan Random Forest (RF) dalam mengklasifikasikan sentimen ulasan pengguna terhadap aplikasi Vidio. Sebanyak 1.000 ulasan berbahasa Indonesia dikumpulkan menggunakan teknik web scraping dan diberi label sentimen berdasarkan rating bintang, di mana rating 1–2 dikategorikan sebagai sentimen negatif dan 3–5 sebagai sentimen positif. Data ulasan diproses melalui beberapa tahap preprocessing, seperti pembersihan teks, tokenisasi, penghapusan stopword, dan stemming, sebelum dikonversi menjadi representasi numerik menggunakan metode TF-IDF. Dataset dibagi menjadi 80% data latih dan 20% data uji. Kedua model dilatih dan dievaluasi menggunakan metrik accuracy, precision, recall, dan F1-score. Hasil penelitian menunjukkan bahwa performa yang lebih unggul diperoleh oleh algoritma SVM, dengan akurasi mencapai 76,11%, dibandingkan dengan RF yang memperoleh akurasi sebesar 71,67%. Selain itu, identifikasi ulasan dengan sentimen negatif juga dilakukan dengan lebih efektif oleh SVM. Temuan ini membuktikan bahwa klasifikasi sentimen ulasan aplikasi Vidio lebih tepat dilakukan menggunakan SVM, sehingga berpotensi mendukung otomatisasi analisis sentimen dan peningkatan kualitas layanan streaming. Hasil ini dapat diimplementasikan dalam sistem dashboard otomatis untuk mendeteksi keluhan pengguna secara real-time, memungkinkan pengembang Vidio meningkatkan pengalaman pengguna dengan respons yang lebih cepat dan tepat. Kata Kunci: Text Classification, User Sentiment, Support Vector Machine, Random Forest, Vidio.
Co-Authors Arnia Sari Mukaromah Fastabiqul Khusna Khothibul Umam Khothibul Umam Maya Rini Handayani Maya Rini Handayani Muhammad Naufal Muhadzib Al-Faruq Siti Muhlisoh Wilis Brawijaya