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JSAI (Journal Scientific and Applied Informatics)
Published by Universitas Muhammadiyah Bengkulu
ISSN : 26143062     EISSN : 26143054     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal terbitan dibawah fakultas teknik universitas muhammadiyah bengkulu. Pada jurnal ini akan membahas tema tentag Mobile, Animasi, Computer Vision, dan Networking yang merupakan jurnal berbasis science pada informatika, beserta penelitian yang berkaitan dengan implementasi metode dan atau algoritma.
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Articles 32 Documents
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Search results for , issue "Vol 8 No 1 (2025): Januari" : 32 Documents clear
Deteksi Bahasa Isyarat Indonesia (BISINDO) Pada Video dengan YOLOv7 Renaningtias, Nurul; Utama, Ferzha Putra; Sobri, Azzahrah Nur Awaliah
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7067

Abstract

Sign language is a method of communication that does not use sound but uses physical movements such as hands, body, and lips. One of the sign languages that many deaf people use to communicate is Indonesian Sign Language (BISINDO). This study aims to implement an object detection and image classification model for BISINDO alphabet gestures using the You Only Look Once (YOLO) version 7 algorithm. This research uses video image data consisting of 26 alphabet letters. In this study, three experiments were conducted with different parameter values. Evaluation was carried out using the metrics of mean Average Precision (mAP), precision, recall, and F1-Score. Based on the experiments conducted, the best accuracy was obtained in experiment 1 with parameter values of epoch = 100, batch size = 64, learning rate = 0.001, weight decay = 0.0001, and momentum = 0.9, resulting in mAP@IoU 0.5 value of 0.995, recall 1.00, precision 1.00, F1-Score 1.00. However, it was found that in the application of the model to real-time scenarios, the detection results were not as good as the results obtained during the training process.
Analisis Sentimen Layanan Perwalian Mahasiswa UMSIDA Menggunakan Metode Support Vector Machine (SVM) Angga, Angga Wibawa Saputra; Hamzah, Hamzah Setiawan; Rohman, Rohman Dijaya
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7387

Abstract

The myUMSIDA application supports academic activities at Universitas Muhammadiyah Sidoarjo, but student reviews reveal complaints about its services and facilities. Sentiment analysis is necessary to classify these reviews into positive or negative categories, providing insights to improve service quality.This study uses the Support Vector Machine (SVM) algorithm with a linear kernel, known for its high accuracy, combined with the TF-IDF feature extraction method to enhance text classification. A total of 1,300 reviews from 2023 were processed through labeling, preprocessing, transformation, and classification. Data were split into three scenarios: 70:30, 60:40, and 50:50 for training and testing. Performance was evaluated using accuracy, precision, recall, and F1-Score.The best results were achieved in the 70:30 scenario, with an accuracy of 86.92%, precision of 86.60%, recall of 84.72%, and F1-Score of 85.7%. This study highlights the effectiveness of SVM with a linear kernel and TF-IDF in analyzing sentiment, offering a basis for enhancing the myUMSIDA application's services.
MQTT Rancang bangun Server Message Queuing Telemetry Transport ( MQTT) Internet of Things ( IoT) Berbasis Eclipse irwansyah, irwansyah; Wahyuni Eka Sari; Agus Triyono; Yhunike Widiya Pratama; Muhammad Bagus; Bintang Tmur; susanna, susanna
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7403

Abstract

The design of a Message Queuing Telemetry Transport (MQTT) server for the Internet of Things (IoT) utilizes Eclipse Mosquitto as the core server software. The process begins with installation and basic configuration, including port setup, authentication, and encryption to ensure secure communication. Further customization is implemented to meet specific project requirements, such as configuring connection protocols, access permissions, quality of service (QoS) levels, and message retention policies. Integration with other Eclipse platforms, such as Eclipse Paho, supports the development of MQTT clients for IoT devices, enabling bidirectional communication between the server and devices. Additional tools like Eclipse Vert.x or Eclipse Hono may also be utilized to enhance device management and enable more complex message processing. Testing results indicate that the MQTT server implemented on a Raspberry Pi 3 B+ successfully received and transmitted data. The ESP32 device also achieved successful data communication via the MQTT server. The system can be accessed across different networks, offering flexible communication without reliance on the same local network. This implementation demonstrates the reliability of MQTT as a robust solution for IoT communication.
Implementasi RAD Pada Pengembangan Website Halo Gamers MARPAUNG, SOPHYA HADINI
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7405

Abstract

The presence of Key Opinion Leaders (KOL) is increasingly important in the business world, especially in increasing consumer purchasing intentions. KOLs are now widely used in various sectors, including the gaming industry. One of them is the presence of Halo Gamers, a YouTube channel that focuses on gaming product reviews. Since 2017, Halo Gamers has targeted the Indonesian gaming market, driven by government projections to control 50% of the gaming industry market share. With more than 2,700 subscribers and collaboration with 16 brands as of November 2024, Halo Gamers acts as a successful KOL in promoting gaming products. Obstacles arise, especially in managing all content portfolios owned by channel owners and information regarding collaboration with brands that are spread across various platforms without centralized media that makes it difficult for channel owners to collaborate with related parties. To overcome this, the author developed a website with the RAD method (a common and popular method in system development that starts from the requirement planning, user design, construction to implementation stages) which functions as a centralized container for Halo Gamers, allowing brands to access portfolios and published content, as well as expanding opportunities for future collaboration at the address halogamers.info.
Prediksi Keberlanjutan Usaha Kecil Menengah (UKM) Menggunakan Algoritma Machine Learning Terttiaavini, Terttiaavini
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7454

Abstract

Small and Medium Enterprises (SMEs) contribute approximately 60% to Indonesia's Gross Domestic Product (GDP) and absorb more than 97% of the workforce. However, SMEs face various challenges that hinder sustainability, such as limited capital and market instability. This study aims to develop a predictive model to map the sustainability of SMEs based on variables that influence business continuity. The methods used include clustering with Agglomerative Clustering, K-Means, and DBSCAN, as well as classification using algorithms such as Logistic Regression, Random Forest, and XGBoost. The results show that the Agglomerative Clustering method provides the best performance with a Silhouette Score of 0.68. All classification models initially achieved an accuracy of 1.0 with a standard deviation of 0.0, but indicated overfitting due to class imbalance between the "Continues" and "Does Not Continue" categories, where the minority class consists of only 16 data points. To address this issue, the application of the SMOTE (Synthetic Minority Over-sampling Technique) method and 5-Fold Cross-Validation was implemented. The results showed an improvement in the model's ability to recognize patterns in the minority class, making the model's accuracy more representative of both classes. This research is expected to provide valuable insights for the Office of Cooperatives and SMEs in Palembang to support the sustainability of the SME sector in Palembang.
Eksplorasi Model Prediksi Sentimen Postingan Di Media Sosial Fitri Purwaningtias
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7513

Abstract

Sentiment analysis is a text analysis technique that can be used to understand the opinion, feeling, or sentiment of a text. This research aims to explore and compare sentiment prediction models on social media data with three algorithms, namely GaussianNB, Logistic Regression, and Support Vector Machine (SVM). The dataset used is taken from www.kaggle.com, which consists of social media posts from the Twitter, Facebook, and Instagram platforms with positive, negative, and neutral sentiment categories. The analysis process involves text data preprocessing, data labeling, feature extraction with Bag of Words (BoW) and TF-IDF, and handling data imbalance with SMOTE. The results showed that the SVM model with TF-IDF and SMOTE performed best, with 93.25% accuracy on training data and 92.50% on test data. This research contributes to determining the best model for sentiment analysis of social media data and can be a reference in developing better sentiment prediction systems in the future.
Ketepatan Ekspektasi Telemarketing di Bank Portugal: Memanfaatkan Penambangan Data abbas, irfan; Asriani; Faisal Binsar; Abdul Halik
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7519

Abstract

Banks play a basic role in economic improvement as well as contribute various cash related organizations to clients. Telemarketing is a commonly applied exchange method inside banks to offer and develop unused organizations to their clients. This kind of campaign generates a vast collection of data, A suitable examination of this data can support banks in organizing future strategies. Furthermore, it considera proposed data mining approach, to analyze and predict using atelemarketing campaign dataset. This dataset is composed based on demonstration pieces collected from clients, amid live call sessions organized by the bank. To execute the proposed view. The results show that the calculated backslide gives the best precision among the three models, recorded at 91.48%.
Strategi Dan Perencanaan Outsourcing Dalam Pengembangan Sistem Informasi Dengan Memanfaatkan CMMI-ACQ Nurhajati, Riny; Ida Nurhaida; Fitriyana Nuril Khaqqi
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7522

Abstract

Finance companies often face challenges in managing information system development projects through outsourcing. There is a need to improve efficiency and alignment between IT and business in the Project Planning (PP) process. By adopting the McFarlan Strategic Grid and CMMI-ACQ, mapping the current information system and development plan based on four quadrants, measuring the maturity level of the project planning process, and identifying areas that need improvement. Based on the results of the maturity level measurement in the Project Monitoring and Control area, it shows that Specific Goals (SG) have low achievements, with SG 1 (27%) and SG 2 (39%) showing great room for improvement in monitoring and corrective action management. At the Specific Practices (SP) level, practices that have been quite good are project planning monitoring (SP 1.1, 60%) and problem analysis (SP 2.1, 50%). Still, many areas need improvement, such as risk monitoring (SP 1.3, 7%), data management (SP 1.4, 20%), and stakeholder involvement (SP 1.5, 20%). These findings highlight the importance of formulating project risk management, improving project management capabilities, and strengthening collaboration between teams to achieve the success of information system development projects. By implementing the proposed approach, companies can develop more efficient PP process standards, ensure IT alignment, and optimize resource and cost allocation.
Implementasi Algoritma K-Nearest Neighbors Untuk Klasifikasi Spam Email Diani Putri Kusumaningrum; Ahmad Turmudi Zy; Suprapto
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7531

Abstract

In modern life, internet access has become essential for communication. Email is one of many communication tools. Cyberattacks such as ransomware, phishing, and cryptojacking continue to evolve and are difficult to detect by security systems as technology rapidly advances. Therefore, this study uses email spam as the subject of research. The aim of this study is to implement and calculate the accuracy of the K-Nearest Neighbors (KNN) algorithm in classifying spam emails with ham and spam labels. An accuracy of 85%, precision of 87%, recall of 93%, and F1-score of 90% were obtained from tests conducted with an 80% training data and 20% testing data ratio. The results show that the K-Nearest Neighbors algorithm can effectively classify spam emails.
Evaluasi Tata Kelola Teknologi Informasi Aplikasi Layanan Di PT.PQR Dengan Cobit 4.1 Probonegoro, Wishnu Aribowo; Sari, Lili Indah; Romadiana, Parlia
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 1 (2025): Januari
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i1.7544

Abstract

PT PQR is a company engaged in the application of shipping services. It is important for PT PQR to manage and utilize information technology well, but there has never been an assessment of the management system and its application. The author conducted research to assess the management of information technology using the COBIT 4.1 standard, which has 34 processes. This research was conducted through observations, interviews, and measurement of maturity levels, with the aim that PT PQR knows the information technology governance that is carried out, and knows the gaps that exist so that they can be resolved immediately to improve services and compete with other companies. The results showed that the current maturity level at PT PQR is close to level 3, with 14 Information Technology processes in two domains, namely Delivery Support and Monitoring Evaluate. PT PQR has clear and written standard procedures regarding the procedures and management of information technology, which are socialized among management and employees. Overall, the maturity level evaluation shows that PT PQR has fairly good IT governance, with an average achievement close to the expected target. The DS domain has an almost optimal performance with an achievement of 99%, while the ME domain requires more attention to increase the achievement from 90% to 100%. Improvement efforts can be focused on areas that require improvement based on the findings of this analysis.

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