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INDONESIA
JURNAL SISTEM INFORMASI BISNIS
Published by Universitas Diponegoro
ISSN : 20883587     EISSN : 25022377     DOI : -
Core Subject : Economy, Science,
Computer Science & IT Economics, Econometrics & Finance
JSINBIS merupakan jurnal ilmiah dalam bidang Sistem Informasi bisnis fokus pada Business Intelligence. Sistem informasi bisnis didefinisikan sebagai suatu sistem yang mengintegrasikan teknologi informasi, orang dan bisnis. SINBIS membawa fungsi bisnis bersama informasi untuk membangun saluran komunikasi yang efektif dan berguna untuk membuat keputusan yang tepat waktu dan akurat. Business intelligence sebagai dasar pengembangan dan aplikasi SINBIS menjadi kerangka kerja teknologi informasi yang sangat penting untuk membuat agar organisasi dapat mengelola, mengembangkan dan mengkomunikasikan aset dalam bentuk informasi dan pengetahuan. Dengan demikian SINBIS merupakan kerangka dasar dalam pengembangan perekonomian berbasis pengetahuan.
Arjuna Subject : -
Articles 13 Documents
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Search results for , issue "Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024" : 13 Documents clear
Pengembangan Game Edukasi Digital Tema Seni dan Bahasa dengan Metode Multimedia Development Life Cycle Nurul, Hanan; Nugraheni, Dinar Mutiara Kusumo; Noranita, Beta; Bahtiar, Nurdin
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp302-310

Abstract

Education for early childhood, especially for PAUD TK-B in the age range of 4-6 years, is crucial in providing and shaping the foundation of children's knowledge. An engaging teaching method will enhance children's interest in learning, thus the need for digital learning media as an alternative. One step in implementing digital learning is through Educational Games. This research is conducted by developing the PAUD TK-B Nurussunnah Educational Game using the Multimedia Development Life Cycle (MDLC) method. The game's validation includes usability aspects such as effectiveness, satisfaction levels, and adaptation to the TK-B curriculum. After development, the educational game undergoes alpha and beta testing using the black box method. Beta testing involves evaluating usability for the efficiency and satisfaction of TK-B students, with an effectiveness rate of 98.94%  and satisfaction rate of 88.57%. The interview results with expert teachers indicate that the educational game aligns with the curriculum at the educational unit level for PAUD. Thus, based on the research findings, the PAUD TK-B Educational Game application can be considered an alternative learning media for TK-B students.
Perbandingan Metode Machine Learning dalam Analisis Sentimen Komentar Pengguna Aplikasi InDriver pada Dataset Tidak Seimbang Mola, Sebastianus Adi Santoso; Luttu, Yufridon Charisma; Rumlaklak, Dessy Nelci
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp247-255

Abstract

The InDriver service is an online transportation service that has more flexibility in price and driver choice by consumers. Various comments from InDriver service users can affect people's views, so it is necessary to carry out a sentiment analysis of these comments. The purpose of this study was to identify positive, negative and neutral sentiments in user comments and to compare the performance of classification methods. The results of analysis with unbalanced datasets show that the Support Vector Machine (SVM) and Logistic Regression methods have the highest accuracy, reaching 89%. However, quality assessment is not only based on accuracy alone. In terms of the balance between precision and recall in the minority (neutral) class, the Random Forest method shows a more balanced performance with an F1-score of 55%. After balancing the dataset with the SMOTE method, performance increases significantly for the Naïve Bayes Classifier method, especially in the neutral class for recall and F1-score metrics of 57% and 52%. In conclusion, SVM and Logistic Regression have high accuracy, but to consider the balance of precision and recall in the minority class, the Random Forest method is recommended.
Front matter JSINBIS 14 (3) 2024 Mustafid, Prof
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3ppi

Abstract

Front matter JSINBIS 14 (3) 2024
Prediksi Perubahan Hemodinamik Pasien setelah Pemberian Premedikasi menggunakan Machine Learning Neural Network Guna Meningkatkan Kinerja Penanganan Medis Aryasa, Jiyestha Aji Dharma; Widodo, Aris Puji; Widodo, Catur Edi
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp256-266

Abstract

This research presents the development process of a machine learning neural network model for predicting hemodynamic changes in patients after premedication, aiming to enhance the performance of medical interventions. The model was constructed using 3055 patients’ data who underwent premedication processes. The developed neural network model has an architecture consisting of 10 nodes in the input layer, 10 nodes in the hidden layer, and 3 nodes in the output layer. The evaluation results of the model indicate an overall accuracy of 85%. The precision values are high for normal class predictions at 0.85 and for hypertension class predictions at 0.81 with corresponding recalls of 1 (high) and 0.6 (moderate), respectively. However, predictions for the hypotension class still have a low precision of 0.6 and a recall of 0.04 (very low) due to the significantly lower number of samples in the hypotension class compared to the normal and hypertension classes. While testing with new data, the model has successfully predicted whether patients will experience hemodynamic pressure changes. It is expected that this model can contribute to improving the performance of medical interventions, thereby minimizing undesirable hemodynamic pressure changes.
Analisis Sentimen Komentar Konsumen Industri Jamu di Media Sosial menggunakan Artificial Neural Network dan K-Nearest Neighbor Kurniawan, Daniel; Purnomo, Hindriyanto Dwi; Iriani, Ade
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp210-223

Abstract

Phytopharmaceutical plants have become one of the main commodities contributing significantly to the economy through their use in the pharmaceutical, cosmetic, and health industries. However, behind this economic potential, traditional herbal medicine businesses often face challenges, particularly in promotion and brand identity. Social media platforms like Instagram have now introduced unique features to support business and marketing, primarily by providing in-depth information about herbal products and offering opportunities for businesses to receive feedback from consumers. Comments on social media are valuable but often unstructured; hence, sentiment analysis is necessary to organize and categorize this data. By combining comment data with information from Google Trends, cause-and-effect relationships from comments during specific periods can be identified using path analysis. This research aims to analyze consumer comments on the Sidomuncul company's Instagram platform, with the hope of benefiting the company and advancing herbal medicine products. The methods used in this study include Artificial Neural Network (ANN) and K-nearest neighbor (KNN) to classify comments into positive, negative, and neutral categories. Both methods show satisfactory results in classification, with an average accuracy of 0.887 for ANN and 0.874 for KNN. However, the ROC curve for the KNN model indicates a relatively low AUC value in classifying negative comments, at 0.598.
Preface JSINBIS 14 (3) 2024 Mustafid, Prof
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3ppvi

Abstract

Preface JSINBIS 14 (3) 2024
Analisis Penerimaan dan Kesuksesan Aplikasi M-health pada Lansia menggunakan Model UTAUT dan Delone & McLean Merdekawati, Utami; Nugraheni, Dinar Mutiara Kusumo; Nurhayati, Oky Dwi
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp267-276

Abstract

M-health plays a crucial role in providing medical services through features like online doctor appointments. While it offers convenience, there are challenges in its adoption among the elderly. The success of M-health depends on user acceptance and continued use. Therefore, an evaluation of information technology focused on the elderly in Indonesia is necessary. Technology accepted by users is not necessarily successful, and vice versa. This study aims to identify factors influencing the acceptance and success of M-health applications among the elderly. It combines the UTAUT and Delone & McLean models to investigate acceptance and success factors. The variables used are performance expectancy, effort expectancy, information quality, system quality, service quality, user satisfaction, and continuance intention. The PLS-SEM method is used to process respondent data. Analysis result shows that 61.6% of elderly users' satisfaction with M-health is influenced by information quality, service quality, performance expectancy, and effort expectancy. Meanwhile, 59.4% of the continuance intention is influenced by user satisfaction. This indicates that the application is well received and successful because it provides a satisfying experience. This study confirms that the combination of the UTAUT and Delone & McLean models is adequate.
Sistem Informasi Bimbingan Tugas Akhir Mahasiswa menggunakan Model SDLC Berbasis Iconix Process Ana Wati, Seftin Fitri; Fitri, Anindo Saka; Vitianingsih, Anik Vega; Najaf, Abdul Rezha Efrat; Maukar, Anastasia Lidya
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp224-236

Abstract

The final thesis assignment plays a crucial role in enabling students to meet the graduation requirements from college. However, the process of scheduling guidance for the final assignment between students and lecturers still relies on several common applications such as WhatsApp or email, which are not specifically designed for this purpose. The accumulation of incoming messages and various types of message information poses a challenge in the guidance process, leading to missed messages between students and lecturers and a lack of recorded information regarding the history of the process and guidance materials. These are some of the current issues. This paper aims to evaluate the functionality, quality, and reliability of the system by conducting black box testing on the application developed for the student final project guidance information system. This application uses the Iconix process-based SDLC (system development life cycle) model, covering student and lecturer profile information, guidance information, proposal submission, progress of the final thesis assignment, meeting schedule, guidance material, discussion forum, survey evaluation, and contact information. The SDLC model is employed in this research because it can effectively and efficiently achieve project targets, enhance software quality standards, and assist in better risk management and adaptation to change. The model comprises planning, needs analysis, design using the Iconix process, implementation, system testing, and maintenance. The Iconix process is utilized for system design modeling and analysis. Black box testing is performed on the system to verify that the system’s functional requirements are operating correctly. The findings of this research can serve as a control for management in the service and administration of final assignment guidance in higher education.
Back matter JSINBIS 14 (3) 2024 Mustafid, Prof
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3ppvii

Abstract

Back matter JSINBIS 14 (3) 2024
Analisis Kepuasan Pengguna Gojek dengan Metode Kuantitatif Multimodel Yulianing Tyas, Sasmi Hidayatul; Muftikhali, Qilbaaini Effendi
Jurnal Sistem Informasi Bisnis Vol 14, No 3 (2024): Volume 14 Nomor 3 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss3pp277-288

Abstract

Gojek is the first start-up company in Indonesia to have decacorn status based on CB-Insight's records. With Go-Jek's achievement status being the background factor for satisfaction with Go-Jek application users. This research aims to identify factors that influence Gojek customer satisfaction with application use. In this research, quantitative methods using the EUCS, TAM and Delone and McLean (Multi Model) models were used to identify the independent variables, while the dependent variable was customer satisfaction. The dependent variables in this research consist of Content, Accuracy, Format, ease of use, Timeliness, Perceived Usefulness, System Quality, Information Quality and Service Quality. Quantitative methods were used in this research, based on the calculation results of the GeSCA application. The R-squared value of the model proposed in this study is 0.6922. This means that the independent variables in the model can explain the customer satisfaction variable by 69.22% and the remaining 31.78% is explained by other independent variables that are not in the model. Based on the results of the analysis, it was found that 9 variables had an influence on the customer satisfaction variable, but there was 1 variable that had a significant influence (Service Quality). Conclusion  of this research show that the variables Content, Accuracy, Format, ease of use, Timeliness, Perceived Usefulness, System Quality, Information Quality and Service Quality have an influence on user satisfaction.

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