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Infotech: Journal of Technology Information
Published by STMIK Widuri
ISSN : 26205181     EISSN : 24602108     DOI : https://doi.org/10.37365/it
Core Subject : Science,
Computer Science & IT
Jurnal Infotech adalah jurnal ilmiah yang berisi hasil penelitian yang ditulis oleh dosen, peneliti dan praktisi. Jurnal ini diharapkan untuk mengembangkan penelitian dan memberikan kontribusi yang berarti untuk meningkatkan sumber daya penelitian di bidang Teknologi Informasi dan Ilmu Komputer. Infotech diterbitkan oleh Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Widuri dengan akses terbuka. Setiap artikel yang diterbitkan memiliki pengidentifikasi objek digital (DOI). ISSN 2620-5181 (Online) ISSN 2460-2108 (Print)
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 207 Documents
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SISTEM MONITORING KUALITAS AIR BERBASIS INTERNET OF THINGS DI DESA WONOSARI Pradana, Gibran Arya; Maulindar, Joni; Srirahayu, Agustina
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.417

Abstract

Di daerah-daerah yang masih menggunakan inspeksi manusia sebagai norma, kesehatan masyarakat sangat berisiko akibat air berkualitas rendah. Dengan latar belakang tersebut, tujuan penelitian ini adalah untuk mengembangkan dan meluncurkan sistem pemantauan kualitas air di Desa Wonosari yang memanfaatkan Internet of Things (IoT). Untuk lebih melindungi penduduk dari bahaya kesehatan, sistem ini dimaksudkan untuk memberikan data akurat secara real-time tentang suhu air, kekeruhan, total padatan terlarut (TDS), pH, dan karakteristik lainnya. Teknik penelitian meliputi pengumpulan persyaratan, konstruksi prototipe, evaluasi sistem, dan pengujian. Berdasarkan hasil, sensor pH, kekeruhan, suhu air, dan total padatan terlarut (TDS) masing-masing memiliki akurasi 99,22% dan 98,26%. Perangkat tersebut juga lulus uji ketahanan dengan tingkat keberhasilan 96,66% dan margin kesalahan 3,33%. Hasil ini menunjukkan bahwa metode yang diusulkan meningkatkan efektivitas pemantauan kualitas air dan dapat meningkatkan aksesibilitas air, yang pada gilirannya meningkatkan kesehatan masyarakat. Hasilnya, teknologi ini memberikan pendekatan baru terhadap pemantauan kualitas air masyarakat yang aman dan efisien.
PREDIKSI HARGA DAN RISIKO SAHAM TELKOM DAN INDOSAT MENGGUNAKAN LSTM DAN VAR DENGAN VISUALISASI Alam, Indera Nurul; Pratiwi, Nunik
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.399

Abstract

Investment in Indonesia shows a growing trend, with Telkom (TLKM) and Indosat (ISAT) being among the mostactively traded stocks with high volatility. This condition raises the need for reliable stock price prediction andinvestment risk analysis. This study aims to develop a daily stock closing price prediction model using the Long Short-Term Memory (LSTM) algorithm with a Bidirectional LSTM architecture and to conduct risk analysis based on Valueat Risk (VaR) through parametric Monte Carlo simulation. Fourteen years of historical stock data were utilized andprocessed through feature engineering techniques (return, moving average, volatility) and 30-day windowing.Baseline models with one to four layers were tested, and the best model was further optimized through hyperparametertuning using the Random Search method. The results indicate that the single-layer Bidirectional LSTM modeldemonstrated the best performance on the testing data. Evaluation shows a significant performance improvement aftertuning, with RMSE decreasing from 69 to 67, MAPE from 1.61% to 1.59%, and R-Square remaining high at 0.97 forTelkom, as well as a reduction in RMSE from 91 to 74, MAPE from 2.81% to 2.27%, and an increase in R-Squarefrom 0.76 to 0.84 for Indosat. The VaR analysis reveals that the predicted daily and 80-day risk values show onlyminor deviations from the actual values, supporting the validity
PENGEMBANGAN SISTEM DETEKS EMOSI WAJAH MENGGUNAKAN ALGORITMA MACHINE LEARNING Pebriansyah, Dendi; Suroyo, Heri
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.420

Abstract

Facial emotion detection is one of the essential technologies in human–computer interaction. This study aims to compare the performance of the Convolutional Neural Network (CNN) and the CNN–Long Short-Term Memory (CNN-LSTM) algorithms in detecting emotions using three datasets: FER2013, CK+, and AffectNet. The research process involved data collection, preprocessing, model training with transfer learning, and evaluation using accuracy, precision, recall, F1-score, and confusion matrix metrics. The results show that CNN achieved only 60% accuracy with varying precision and recall, whereas CNN-LSTM reached an accuracy of 80–87% with more stable performance. Analysis of accuracy curves, loss, log loss, and radar charts indicates that CNN-LSTM outperforms CNN in classifying emotions more evenly and consistently, although it requires longer computational time. These findings emphasize that integrating CNN and LSTM can enhance the effectiveness of facial emotion detection systems, particularly in handling complex and dynamic expressions.
ANALISIS SENTIMEN TERHADAP MINAT MASYARAKAT JAKARTA YANG MEMILIH KENDARAAN UMUM MENGGUNAKAN ALGORITMA NAÏVE BAYES Dewanto, Yogga Tolly; Wiranata, Ade Davy; Sulaeman, Mia Kamayani
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.407

Abstract

The worsening traffic congestion in Jakarta highlights the need to understand public interest in using public transportation. Social media platforms such as X serve as valuable sources of real-time public opinion data. This study aims to analyze the sentiments of Jakarta residents toward public transportation to identify the factors influencing their interest in using it. Data was collected from X and analyzed using the Naïve Bayes algorithm through the RapidMiner application. The analysis was conducted by splitting the dataset into 60% training data and 40% testing data. The results of the study show 203 positive sentiment data, 135 negative sentiment data, and 138 neutral sentiment data. Positive sentiments were mostly associated with affordability and ease of access, while negative sentiments were related to discomfort and lack of punctuality. This research is expected to serve as a reference for policymakers in improving the quality of public transportation services in Jakarta.
IMPLEMENSTASI CONVOLUTIONAL NEURAL NETWORK UNTUK DETEKSI DAN KLASIFIKASI MOTIF BATIK SOLO SECARA OTOMATIS Ardiansyah, Muhammad Irfan; Srirahay, Agustina; Permatasari, Hanifah
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.421

Abstract

Batik is a recognized intangible cultural heritage of Indonesia, featuring diverse motifs and deep-rooted philosophical meanings. Solo is one of the regions known for its distinctive batik patterns. However, manual identification remains challenging due to visual similarities between motifs. This study aims to develop an automatic classification system for identifying four Solo batik motifs Parang, Sidoasih, Sidomukti, and Truntum using a Convolutional Neural Network (CNN). The dataset includes 250 labeled digital images collected from online repositories and prior research. The data were split into training, validation, and test sets. Preprocessing steps involved resizing to 224×224 pixels, normalization, and data augmentation. The CNN architecture comprises three convolutional layers, max pooling, a flatten layer, and two dense layers. The model was trained for 20 epochs using the Adam optimizer and categorical cross-entropy loss function. Evaluation results showed that the model achieved an accuracy of 89.36% and a loss value of 0.5172. The macro and weighted f1-scores exceeded 0.88, indicating high classification performance. These results demonstrate the potential of CNNs in recognizing complex batik motifs and highlight the role of AI in preserving cultural heritage through technology.
IMPLEMENTASI CHATBOT BERBASIS ARTIFICIAL NEURAL NETWORK UNTUK MENDUKUNG EFISIENSI LAYANAN KONSULTASI DI PT LOKAKITA KREATIF INDONESIA Harist, Muhammad Abdul; Sopingi, Sopingi; Irawan, Ridwan Dwi
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.449

Abstract

The rapid development of information technology has driven companies to innovate in delivering faster and more efficient services. PT Lokakita Kreatif Indonesia, a company engaged in consulting and mapping services, often receives recurring questions from clients, which were previously handled manually. To address this issue, this study aims to design and develop a Chatbot system based on Artificial Neural Networks (ANN) that can understand user intent and provide automated responses. The system was developed through several stages, including data collection, text preprocessing, ANN model training using Keras, and integration into a web application built with Flask. The dataset was compiled from frequently asked questions submitted by clients and processed into a machine-readable format. Testing results show that the Chatbot can provide accurate answers with an accuracy rate of up to 87% and a relatively fast response time. These findings indicate that the system can assist the company in delivering initial consultation services in a consistent and autonomous manner. The Chatbot not only improves work efficiency but also opens opportunities for further development through integration with other communication platforms.
RANCANG BANGUN SISTEM DETEKSI HUJAN OTOMATIS MENGGUNAKAN ARDUINO UNO Riadi, Ahmad Sharul; Salam, Ahmad Al-Baihaqi; Diantoro, Karno; Sitorus, Anwar T; Juwari, Juwari; Samroh, Samroh
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.555

Abstract

This research focuses on the design and construction of an automatic rain detection device that utilizes an Arduino Uno R3 as its primary microcontroller. The research was motivated by the need for a system capable of detecting rainfall in real time and providing automatic responses, such as driving a servo motor to close the clothesline roof. This device is designed to address weather uncertainty and help people protect their belongings from rain without the need for manual monitoring. By using a rain sensor, the system automatically detects the presence of water droplets and sends a signal to the Arduino to activate the closing mechanism.This research aims to address delays and uncertainties in rain detection, which can damage goods and clothing. Although existing systems use raindrop sensors, their slow response often hinders users from acting quickly. To address this issue, fuzzy logic methods are used to improve accuracy and speed. This system is implemented using Internet of Things (IoT) technology, with the main components being an Arduino Uno R3, ESP32, a raindrop sensor, and a stepper motor. Testing was conducted using Black Box Testing to ensure proper functionality. The Blynk application on a smartphone is used as an interface to control and monitor the system in real time.The results of my research show that the system can detect rain with high accuracy and provide a quick response by closing the canopy. With this system, it is hoped that the application of IoT technology in modern households can increase efficiency in managing unpredictable rainfall and provide better protection.
TINJAUAN SISTEMATIS QUALITY OF SERVICE PADA LAYANAN JARINGAN SOFTWARE DEFINED NETWORKING Wiranata, Ade Davy; Sunardi, Sunardi; Riadi, Imam
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.422

Abstract

Software-Defined Networking (SDN) offers revolutionary flexibility and centralized management, yet ensuring reliable Quality of Service (QoS) for various applications remains a primary challenge. Although extensive research on QoS in SDN has been published, the proposed architectures, methods, and evaluation metrics are often disparate and complex. Consequently, A discernible gap exists in the current literature regarding a comprehensive survey of the research landscape for QoS in SDN. This literature review aims to identify and analyze the research trends, architectures, methods, and metrics related to QoS in SDN published between 2020 and 2025. Based on inclusion and exclusion criteria, 80 studies on QoS in SDN were identified. The analysis reveals four main research topics: Resource Management (45%), QoS-aware Routing (30%), Traffic Classification (20%), and QoS Security (5%). The majority of studies (70%) utilize simulation environments such as Mininet, while 30% employ physical testbeds In terms of methodology, it was found that mathematical optimization approaches such as Mixed-Integer Linear Programming (MILP) are still the most frequently implemented. However, there is a very clear trend of increasing proposals for Machine Learning (ML)-based methods, particularly Reinforcement Learning, as a solution for dynamic QoS management. This review provides a holistic view for researchers and practitioners to understand the current state and future direction of QoS research in SDN environments.
ANALISIS DAMPAK GAME ONLINE TERHADAP PERILAKU SOSIAL DAN KOGNITIF PENGUNA STUDI KASUS PLUS GAMING Aminah, Siti; Diantoro, Karno; Chandra, Ilham Aditya
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.548

Abstract

The development of information and communication technology has driven the growth of online gaming into a global phenomenon, especially among the younger generation. The ease of internet access and the availability of supporting devices have increased the intensity of gaming. Online games can provide benefits in terms of strategic thinking, teamwork, and cognitive development, but excessive use can have a negative impact on social interaction, emotional stability, and user time management. The problem in this study is that as the intensity of online gaming increases, it leads to a decrease in social interaction, emotional disturbance, impulsive thinking, and poor time management in users. These impacts not only interfere with the quality of social and emotional life, but also productivity and the balance of daily activities. Therefore, this study utilized a clustering technique with K-Means algorithm using Orange Data Mining application, to group users based on the duration of play as well as social, emotional, and cognitive indicators. This approach helps to objectively identify groups of users who experience both positive and negative impacts. The analysis resulted in two clusters: C1, containing users with moderate playing intensity and positive behavioral tendencies (56.49%, silhouette 0.588), and C2, containing high-intensity users with negative behavioral tendencies (43.51%, silhouette 0.549). This study aims to map the behavior of online game users based on the intensity of playing, so that the general pattern of positive and negative impacts that appear in different groups of users can be known. The findings are expected to be the basis for further studies on the influence of playing intensity on the balance of users' lives.
ANALISIS SISTEM INFORMASI PENDAFTARAN KOMPETISI ARCHERY TINGKAT NASIONAL MENGGUNAKAN ALGORITMA FIFO MELALUI METODE WATERFALL Satrio Wibowo, Ryan Rafif; Sitorus, Michael
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.550

Abstract

This research addresses the issue of inefficiency and disorder in the registration process of national-level archery competitions, which often results in data errors and unstructured participant queues. The objective of this study is to design and develop a web-based registration system capable of automatically managing participant queues, enhancing transparency, and speeding up the registration process. The methodology employed includes the application of the Waterfall software development model and the FIFO (First In First Out) algorithm for queue management. Testing results indicate that the developed system successfully performs its core functions, including input validation, automatic data management, and real-time participant listing. User surveys show a high level of acceptance regarding the system, particularly concerning fairness and transparency. The conclusion of this study is that the web-based information system developed using this approach can improve registration efficiency and transparency, with potential applicability for various sporting events.

Page 19 of 21 | Total Record : 207

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