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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.
Arjuna Subject : -
Articles 471 Documents
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Aplikasi Promosi dan Penjualan Business-to-Business Berbasis Web (Studi Kasus PT. Revass Utama Medika) Nengsiana, Nengsiana; Ayumi, Vina
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7415

Abstract

The existence of a sales information system in the current digital era is increasingly important for companies in managing their business processes. The purpose of this research is to analyze the design of a Business-to-Business Promotion and Sales information system so that it makes it easier for companies to integrate information needs that can support overall services and adjust sales and product marketing strategies that are more targeted. The research methods used include field studies and observations by conducting interviews using the waterfall method, modeling design using the UML method. The results of the analysis carried out show that the manual sales information used in this company is inefficient and it is proposed to create a web-based sales and promotion application. The aim of making this application is to improve time efficiency in processing and transactions as well as more targeted product marketing. This application has several quite complete features such as adding and deleting products, a sales graph dashboard, transaction features, shipping options features and sales report retrieval features.
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.
Analisis Faktor Kepercayaan dan Kepuasan Pengguna Website Marketplace: Studi Empiris pada E-Commerce Lazada Hari Haji, Wachyu; Ratnasari, Anita; Ayumi, Vina; Noprisson, Handrie; Ani, Nur
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7476

Abstract

This study aims to identify the factors influencing trust and user satisfaction in online marketplaces by applying the DeLone & McLean information system success model. Data were collected through an online questionnaire distributed to Lazada marketplace buyers in Indonesia. The empirical results indicate that trust is a key predictor in determining the quality of sellers and their ability to provide the best services. Statistically, the first hypothesis (H1) shows a significant influence of website reputation on user trust (**T-Stat = 8.50; Sig = *). The second hypothesis (H2), regarding the influence of perceived website size on trust, is not significant (T-Stat = 1.42; Sig = NS). The third hypothesis (H3) demonstrates a significant positive relationship between trust and user satisfaction with the website (**T-Stat = 5.62; Sig = *). The fourth hypothesis (H4) confirms a highly significant positive relationship between trust and perceived website quality (**T-Stat = 14.59; Sig = *). This study recommends that online marketplaces enhance the prestige of sellers and maintain customer trust, as these factors play a critical role in improving user satisfaction when shopping on online marketplaces.
Model HSI-EfficientNetB7 Untuk Analisis Citra Histopatologi Kanker Payudara Ratnasari, Anita
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7477

Abstract

The practice of analysis is expanding in tandem with the advancement of computer science and histopathology image technologies. Combining different types of learning, such as deep learning, machine learning, and image processing, is one way to get the highest level of Precision. The purpose of the research that has been proposed is to evaluate the effectiveness of the EfficientNetB7 transfer learning approach in assessing the histology of breast cancer. This investigation is divided into three primary stages: data gathering, image categorization, and analysis. EfficientNetB7 transfer learning is the methodology that is utilized for data classification. Histopathological pictures of breast cancer specimens with a resolution of 50 x 50 were used as the source of the evaluated data (198,738 negative classes and 78,786 positive classes). Evaluation of the training accuracy, validity, and testing of breast cancer histopathological specimen images with a resolution of 50 x 50 (198,738 negative class and 78,786 positive class) obtained 91.63% accuracy (training stage) and 90.34%ccuracy (validation stage), and the accuracy result (testing stage) is 62.67%. This is the final result of evaluating the training accuracy, validity, and testing of the breast cancer histopathological specimen images. A score of 0.1158 was acquired for Cohen's Kappa, a score of 0.5422 was obtained for the F1-Score, a score of 0.6558 was obtained for Precision, and a score of 0.6267 was received for Recall for the alternative evaluation model.
Analisis Usabilitas Sistem Informasi Akademik Berdasarkan Usability Scale (Studi Kasus: Universitas Mercu Buana) Rahayu, Sarwati; Nugroho, Andi; Sandiwarno, Sulis; Salamah, Umniy; Dwika Putra, Erwin; Purba, Mariana; Setiawan, Hadiguna
JSAI (Journal Scientific and Applied Informatics) Vol 7 No 3 (2024): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v7i3.7478

Abstract

The usability analysis on the website of Mercu Buana University (UMB) is an important research carried out to ensure that the site effectively supports the university's goals, especially in terms of the user's experience in completing academic and administrative goals with ethical and professional standards. This research was carried out during the period January 2024 to May 2024. The main purpose of this study is to measure the usability of the UMB website using a questionnaire method. The questionnaire used for the research adapted the System Usability Scale (SUS) which consisted of a total of 10 questions. Based on the calculation of each statement item having a minimum score of 0 and a maximum score of 2.5, the final score of each respondent ranged from 0 to l00. The average score obtained was 63,125. Based on the results of the score of 63,125, the UMB website has a score in the range of 50 to 70. This shows that the UMB website is in the "quite good" category but there is still a need for a little improvement. Some icons or layouts on the UMB website are not familiar to respondents. In addition, there needs to be guidelines developed to provide information on how to use the website for users who are using the UMB website for the first time.
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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