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Arie Vatresia
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Jurnal Pseudocode
Published by Universitas Bengkulu
ISSN : 23555920     EISSN : 26551845     DOI : https://doi.org/10.33369
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
Pseudocodeis a scientific journal in the information science family that contains the results of informatics research, scientific literature on informatics, and reviews of the development of theories, methods, and application of informatics engineering science. Pseudocode is published by the Informatics Study Program, Faculty of Engineering, University of Bengkulu. Editors invite researchers, practitioners, and students to submit article manuscripts in the field of informatics engineering. Pseudocode is published 2 (two) times a year in February and September with p-ISSN 2355-5920 e-ISSN 2655-1845. Jurnal Pseudocode is Accredited by the Ministry for Research, Technology and Higher Education (RISTEKDIKTI) in SINTA 4 No. 36/E/KPT/2019 since 13 December 2019.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 209 Documents
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Penerapan Motion Graphics Pada Media Edukasi Parenting Berbasis Android Dengan Pendekatan Material Design Guidelines Untuk Bekal Young Parents Dalam Mendidik Anak
Jurnal Pseudocode Vol 12 No 1 (2025): Volume 12 Nomor 1 Februari 2025
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.12.1.28-38

Abstract

This research focuses on developing Eduparent, an Android-based parenting education app designed to help young parents under 21 educate their children in the digital age. The app incorporates animated motion graphics and follows material design guidelines for an intuitive and engaging user experience. The Research and Development (R&D) method and the Multimedia Development Life Cycle (MDLC) model were used to ensure systematic and effective development. Eduparent offers parenting tutorials through materials, expert videos, and animations. A study conducted with 36 young parents in Lubuk Layang Village showed a significant increase in parenting understanding after using the app. The Wilcoxon signed-rank test revealed a significance value of 0.01, indicating a positive impact on parenting knowledge. Keywords: Material Design Guidelines, Young Parents, Parenting, EduParent, Motion Graphics, Education
Pendekatan Ensemble Learning untuk klasifikasi serangan DDoS Nurfajri, Muhammad Oriza; Herwanto, Guntur Budi
Jurnal Pseudocode Vol 12 No 2 (2025): Volume 12 Nomor 2 September 2025
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.12.2.39-46

Abstract

This research proposes an ensemble learning approach for classifying Distributed Denial of Service (DDoS) attacks using the CIC-DDoS2019 dataset. DDoS attacks remain a significant threat to network security, necessitating efficient detection methods. We developed an ensemble model combining Random Forest, Gradient Boosting, and AdaBoost classifiers to enhance detection accuracy. Our methodology involves preprocessing the CIC-DDoS2019 dataset, extracting relevant features, and implementing both binary classification (benign vs. attack) and multiclass classification (attack type identification). The experimental results show that our ensemble model achieves an F1-score of 0.9967 for binary classification, with Gradient Boosting performing best among individual models. The multiclass classification reaches an accuracy of 0.8742 in distinguishing between different types of DDoS attacks. This research demonstrates that ensemble learning significantly improves the accuracy and reliability of DDoS attack detection compared to single-model approaches. Keywords: Ensemble learning; DDoS attack; network security; CIC-DDoS2019; machine learning.
Analisis Kualitas Citra Steganografi Berbasis Spasial Pada Metode Least Significant Bits Dan Pixel Value Differencing Masruri, Nizar Haris
Jurnal Pseudocode Vol 12 No 2 (2025): Volume 12 Nomor 2 September 2025
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.12.2.47-52

Abstract

Steganography is a method in network security systems that functions to hide confidential information by inserting it into other media without changing the authenticity of the information. One of the steganography media is images. Image steganography has two domains: spatial and frequency. The spatial domain works on the pixels of an image, and the frequency domain works on the image frequency. Spatial image steganography is said to be good if the level of stego-image damage is very small. There are several intermediate methods in spatial steganography, namely: LSB, PVD, GLM, EBE, RPE, and others. However, there are two most popular methods, namely LSB (Least Significant Bit) and PVD (Pixel Value Differencing). Therefore, this study aims to test the quality of stego-images produced by these two methods. Testing is carried out using the MSE and PSNR value parameters. A stego-image is considered good when the MSE value is close to 0 and the PSNR value is above 30 dB. From the test data used, this study produced an MSE value of 0.0006 for LSB stego-images and 0.007 for PVD stego-images. The PSNR value was 90 dB for LSB stego-images and 72 dB for PVD stego-images. This study concluded that LSB stego-images have less damage than PVD stego-images, so the researchers recommend using the LSB method in carrying out the steganography process. Keywords: Spatial;MSE;PSNR;LSB;PVD
Penerapan Metode Dempster Shafer Pada Sistem Pakar Identifikasi Hama Tanaman Buah Naga Merah Safitri, Hanifah Nur; Andreswari, Desi; Ginting, Sempurna Br
Jurnal Pseudocode Vol 12 No 2 (2025): Volume 12 Nomor 2 September 2025
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.12.2.60-70

Abstract

Red dragon fruit is a type of fruit that has bioactive components such as flavonoids, phenolics, betacyanins and anthocyanins. Red dragon fruit has a distinctive combination of flavors, namely sweet, sour and refreshingly savory. Apart from that, red dragon fruit also has several health benefits so this fruit is liked by many people. However, a lack of knowledge in maintaining red dragon fruit from pest attacks can cause the growth of red dragon fruit to be less than optimal and result in crop failure. Therefore, an expert system for identifying red dragon fruit pests is needed to minimize the risk of crop failure. The use of an expert system in identifying red dragon fruit pests by applying the Dempster Shafer method can determine the appropriate treatment thereby reducing the percentage of crop failure. The Dempster Shafer method is used to determine the level of certainty of a symptom and provide an accurate level of confidence. The results of this expert system test show that the identification results are close to the truth from an expert using 9 types of pests and 24 symptoms. The resulting accuracy level has a percentage of 100%. Keywords: Red Dragon Fruit, Expert System, Dempster Shafer Method
Perbandingan Kinerja Algoritma Naive Bayes dan K-Nearest Neighbor dalam Menganalisis Sentimen Pengguna Game Free Fire Sudiasta Putri, Nyoman Dinda Indira; Maysanjaya, I Made Dendi; Sunarya, I Made Gede
Jurnal Pseudocode Vol 12 No 2 (2025): Volume 12 Nomor 2 September 2025
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.12.2.53-59

Abstract

Free Fire is one of the most popular online games in Indonesia, yet it continues to receive a wide range of user reviews regarding gameplay experiences. These reviews reflect diverse user perceptions, including both praise and criticism, making sentiment analysis essential to understanding user satisfaction. This study aims to classify user sentiments toward Free Fire using a combined dataset collected from the Google Play Store and App Store, and to compare the performance of two text classification algorithms: Naive Bayes and K-Nearest Neighbor (KNN). The data were collected using web scraping techniques and manually labeled by expert validators. Text preprocessing involved cleansing, tokenizing, stopword removal, and stemming, followed by term weighting using the Term Frequency-Inverse Document Frequency (TF-IDF) method. The experimental results show that the Naive Bayes algorithm achieved the highest accuracy of 72.78%, while the KNN algorithm recorded a maximum accuracy of 45.91%. Based on these findings, Naive Bayes is proven to be more effective in classifying user sentiments related to Free Fire. The results of this study are expected to provide constructive insights for developers to improve the quality and user experience of the game.
Model Penentuan Nilai Mahasiswa Pada Aspek Partisipasi Belajar Dengan Pendekatan Fuzzy Tsukamoto Kesuma, Novriyanti Kesuma; Armansyah, Armansyah; Suhardi, Suhardi
Jurnal Pseudocode Vol 12 No 2 (2025): Volume 12 Nomor 2 September 2025
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.12.2.71-79

Abstract

This study aims to determine the model of student learning participation value and also to determine the criteria for student participation that triggers the value of student learning participation. This study has 5 variables, namely attendance participation, questioning participation, giving ideas participation, helping friends and group discussion activity, each of which has a certain weight. The application of fuzzy logic in this assessment uses fuzzy tsukamoto, the fuzzy rules obtained are 46 rules. The defuzzification results get 87.47 with a very good category, so out of 31 participants who get a fairly good category are 21 participants, participants who get a good category are 9 participants and those who get a very good category are 1 participant.
Prototype sistem monitoring status pintu berbasis iot dengan notifikasi web dan telegram Apriansa Arwandi Panjaitan; Annastia Reza Dzulha; Susilawati Sobur
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.1-8

Abstract

In the era of the Industrial Revolution 4.0, the Internet of Things (IoT) has become an innovative solution for enhancing home security. This study designs and implements an IoT-based monitoring door status system using the ESP8266 microcontroller combined with a magnetic sensor. The system enables real-time monitoring and notifications to users via Telegram and provides door status display through a website. With an integrated alarm feature to prevent unauthorized access, this system is expected to enhance home security at a more affordable cost compared to conventional security systems. Testing results indicate that the system accurately detects door status changes with a notification response time of less than 2 seconds. These findings demonstrate the system’s effectiveness in improving security and user conveniencel.
Klasifikasi Severity Level Diabetic Macular Edema Berbasis ResNet-50 I Made Dendi Maysanjaya; Putu Yudia Pratiwi; I Gusti Ayu Agung Diatri Indradewi
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.9-13

Abstract

Diabetes is one of the most common diseases people suffer from today, and it can lead to complications such as blindness, heart disease, and kidney failure. The condition of blindness caused by this disease is known as diabetic retinopathy (DR). An ophthalmologist will use a fundus camera to examine the retina, looking for several clinical features, such as microaneurysms (MA), hemorrhages (HM), cotton-wool spots (CWS), and exudates. Based on these clinical symptoms, clinicians then determined the patient's level of diabetic macular edema (DME) severity. Although several studies have applied CNN-based architectures for diabetic retinopathy detection, limited attention has been given to the impact of dataset imbalance handling on DME severity classification, particularly using ResNet-50. This study highlights the significant impact of extensive data augmentation on classification performance in imbalanced DME datasets. Evaluate performance using the accuracy, precision, and recall metrics. We used the IDRiD dataset, which consists of 516 images split into a training set of 413 and a test set of 103. IDRiD divides the dataset into three classes, namely normal, moderate DME, and severe DME. In the preprocessing stage, we enhanced contrast using CLAHE and resized the images to 224x224 pixels. To address the imbalance, we applied 11 data augmentation methods. We experimented by comparing the performance of two models: one with and one without dataset augmentation. Based on the test results, the best performance was obtained with the model that included dataset augmentation, achieving an accuracy of 0.5961, a precision of 0.63, and a recall of 0.61, while the baseline model (without dataset augmentation) gained 0.4553, 0.36, and 0.34 for the accuracy, precision, and recall, respectively.
Pengembangan model pengenalan huruf SIBI pada kondisi low-light berbasis convolutional neural network Francisco Francisco; Syaeful Anas Aklani
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.14-20

Abstract

Deaf and speech-impaired individuals in Indonesia face communication barriers due to limited public understanding of sign language. In real use, SIBI communication often occurs in dim lighting, yet recognition models are mainly evaluated under normal illumination, motivating robust low-light recognition. This study develops a CNN model based on MobileNetV2 to recognize SIBI (Indonesian Sign Language System) letter gestures under low-light conditions (50-100 lux). The dataset comprises 5,579 images of 26 SIBI letters, divided stratified 80:10:10. The methodology includes preprocessing with Bilateral Filter, CLAHE in LAB color space, and Adaptive Gamma Correction, plus transfer learning and fine-tuning with data augmentation. Evaluation results show 97.13% test accuracy, with most errors among similar letters. Real- time testing is stable within 50-100 lux, though accuracy decreases below 50 lux or with shadows. These findings indicate that the proposed preprocessing methods and MobileNetV2 CNN maintain reliable SIBI recognition in low-light environments.
Analisis Sentimen Ulasan Aplikasi Access by KAI Menggunakan Algoritma Naïve Bayes Beni Ariansyah; Edi Surya Negara
Jurnal Pseudocode Vol 13 No 1 (2026): Volume 13 Nomor 1 Februari 2026
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.13.1.21-27

Abstract

The Access By KAI application, developed by PT Kereta Api Indonesia (Persero), allows users to purchase train tickets via mobile devices. This study aims to perform sentiment analysis on user reviews of the Access By KAI application using the naive Bayes algorithm. Data processing was carried out through stages such as case folding, cleaning, tokenizing, stopword removal, and stemming, and evaluation using metrics of accuracy, precision, recall, and F1-score showed that the naive Bayes algorithm provides satisfactory results. The study results indicate that the naive Bayes algorithm is able to classify reviews with an accuracy rate of up to 68% with a precision of 83% for the positive class, 59% for the negative class, and 79% for the neutral class; recall of 67% for the positive class, 93% for the negative class, and 42% for the neutral class. From these results, it is expected to help developers identify the aspects most complained about by users and improve service quality.

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