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All Journal Journal of Informatics and Communication Technology (JICT) Internet of Things and Artificial Intelligence Journal Jurnal Masyarakat Madani Indonesia Akademika
Nindy Raisa Hanum
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Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Public Health Social Sciences

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Implementation of the Design Thinking Method in Designing a Laboratory Room Scheduling System Nindy Raisa Hanum; Hasanatul Iftitah; Yogi Perdana
Journal of Informatics and Communication Technology (JICT) Vol. 7 No. 1 (2025)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Laboratories are essential facilities in higher education institutions, particularly in supporting practical learning and research activities. However, manual management often leads to scheduling conflicts, inefficient room utilization, and limited access to real-time information. This study aims to develop a web-based, integrated laboratory room scheduling system for the Faculty of Science and Technology at the University of Jambi. The research adopts the Design Thinking methodology, which consists of five stages: Empathize, Define, Ideate, Prototype, and Test. Stakeholder needs were identified through interviews with lecturers, students, lab staff, and laboratory heads. The primary issue identified was the lack of a centralized scheduling system. A prototype was designed using Figma, incorporating features such as real-time schedule viewing, room booking management, and usage reporting. Usability testing with five respondents revealed high satisfaction in terms of learnability (84%), memorability (85%), and efficiency (87%). The results confirm that the system meets user needs and improves laboratory management. This study contributes to the digital transformation of academic services by offering a user-centered, context-aware solution tailored to the needs of the Faculty of Science and Technology.
Geographic Information System for Drought Potential Areas in Kampar District Hanum, Nindy Raisa
Internet of Things and Artificial Intelligence Journal Vol. 5 No. 2 (2025): Volume 5 Issue 2, 2025 [May]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v5i2.960

Abstract

Drought is a natural disaster that has an impact on various sectors. Drought occurs during the dry season, which is from May to October. So that there is a need for spatial information in the Kampar Regency area for drought potential so that it can help overcome the problem of drought. The data consists of Landsat 8 OLI / TRIS images and rainfall data. The transformation method used is the Tasseled Cap Transformation to get the wetness and revision index and NDVI to get the vegetation index. The results of each index will be weighted and overlaid so that a map of the area with drought potential is obtained. The results of this study are Kampar District which has an area of 7% located in Tapung Hilir District, while 33% of Kampar District has a very low drought potential. In general, the Kampar Regency is classified as having moderate drought potential.
ANALISIS PERBANDINGAN MODEL GRU DAN LSTM UNTUK PREDIKSI HARGA SAHAM BANK RAKYAT INDONESIA: Deep Learning, GRU (Gated Recurrent Unit), LSTM (Long Short-Term Memory), Stock Price Prediction Perdana, Yogi; Raisa Hanum, Nindy; Rabiula, Andre; Anzari, Yandi
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1692

Abstract

This research implements and compares two deep learning architectures, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), for predicting the stock price of Bank Rakyat Indonesia (BRI) using historical data from February 2023 to October 2024. Through systematic hyperparameter tuning and comprehensive evaluation, the study finds that GRU consistently outperforms LSTM across all regression metrics, with a 10.7% improvement in R² and an 18.5% reduction in MAPE. The optimal GRU configuration (100 units, 100 epochs, batch size 32, learning rate 0.001) achieves an MSE of 6517.5 and MAPE of 1.3764%. Visual analysis confirms GRU's superior ability to capture stock price fluctuations and adapt more quickly to trend changes. The simpler architecture of GRU with fewer parameters proves more effective for handling the high-noise characteristics and varying volatility of stock price data. While both models face challenges in predicting extreme market events, GRU demonstrates better resilience and faster recovery after such occurrences. This research contributes to the understanding of recurrent neural network applications in financial time series forecasting and provides practical insights for developing more accurate stock price prediction systems.
PEMODELAN PREDIKTIF TRAFIK WEBSITE BERDASARKAN VOLUME KONTEN: PENDEKATAN REGRESI: Web performance, content strategy, linear regression model, page view analysis, digital content optimization Hasanatul Iftitah; Nindy Raisa Hanum
JURNAL AKADEMIKA Vol 17 No 2 (2025): Jurnal Akademika
Publisher : LP2M Universitas Nurdin Hamzah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53564/akademika.v17i2.1694

Abstract

In today's digital landscape, a website's performance serves as a key metric of an institution’s online presence and communication strategy. This research focuses on forecasting website performance by analyzing the relationship between the number of published articles and the volume of page views using a simple linear regression approach. Monthly data was obtained from the official website of the Faculty of Science and Technology at Universitas Jambi, comprising content publication frequency and corresponding traffic. The analysis reveals a strong positive correlation, where each additional published article contributes to a notable increase in page views. The regression model yields a coefficient of 103.75 with an R² value of 0.7278, indicating that over 72% of traffic variation is attributable to content volume. These results emphasize the importance of consistent content production in enhancing web visibility and provide valuable insights for content strategy development.
Pemberdayaan Siswa SMK melalui Pelatihan IoT untuk Sistem Monitoring Tanaman dalam Mendukung Smart Farming Khaira, Ulfa; Saputra, Edi; Waladi, Akhiyar; Perdana, Yogi; Hanum, Nindy Raisa; Iftitah, Hasanatul; Ashar, Rahmad; Rozi, Syamsyida
Jurnal Masyarakat Madani Indonesia Vol. 5 No. 1 (2026): Februari (In Progress)
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/9xvxt587

Abstract

Provinsi Jambi memiliki potensi besar di sektor pertanian, namun praktik konvensional masih menghadapi kendala terkait efisiensi, produktivitas, dan keberlanjutan. Smart farming berbasis Internet of Things (IoT) hadir sebagai solusi inovatif, namun implementasinya memerlukan sumber daya manusia yang kompeten. Kegiatan Pengabdian kepada Masyarakat (PPM) ini melibatkan sebanyak 20 orang siswa SMK, serta guru SMKN 1 Muaro Jambi, dengan tujuan meningkatkan kompetensi peserta dalam merakit, memprogram, dan memanfaatkan sistem monitoring tanaman berbasis IoT. Program dilaksanakan dalam empat sesi pelatihan yang meliputi pengenalan konsep smart farming dan IoT, pengenalan komponen, praktik perakitan sistem, serta dasar pemrograman mikrokontroler. Hasil evaluasi menunjukkan peningkatan signifikan pemahaman peserta, yang ditunjukkan oleh kenaikan nilai rata-rata post-test sebesar 26 poin (dari 37,1 menjadi 63,1), serta keberhasilan peserta dalam merakit prototipe sistem monitoring tanaman yang fungsional. Temuan ini menegaskan bahwa pelatihan berbasis praktik mampu menjembatani kesenjangan kompetensi siswa vokasi terhadap kebutuhan teknologi pertanian modern. Keberlanjutan program ini diharapkan dapat memperkuat peran sekolah vokasi dalam mendukung penerapan pertanian cerdas sekaligus membuka peluang karier dan kewirausahaan di bidang agroteknologi.
Co-Authors Abda Abda Akhiyar Waladi Andre Rabiula Ashar, Rahmad EDI SAPUTRA Hasanatul Iftitah Perdana, Yogi Ulfa Khaira, Ulfa Yandi Anzari