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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 412 Documents
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Perancangan Arsitektur Enterprise FMIPA UNTAN Menggunakan Kerangka Kerja TOGAF Berbasis SOA Nurul Mutiah; Ferdy Febriyanto
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 12, No 2 (2022): Volume 12 Nomor 2 Tahun 2022
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol12iss2pp116-123

Abstract

The research aims to develop an Enterprise Architecture from FMIPA UNTAN, this is based on the many individual information systems that have been developed by FMIPA UNTAN which are not integrated in data and technology. This situation results in overlapping data that can affect the effectiveness of decision making within the organization. The designed Enterprise Architecture implements the concept of service-oriented architecture in order to support the integration between the business layer and the organization's technology layer. To support the research, several concepts are used, such as TOGAF as a framework for developing Enterprise Architecture, Service Oriented Architecture as a supporter for integration of architectural layers, and Archimate and Business Process Modeling Notation as a modeling language used to create architectural artifacts. The stages of the research included problem identification, the Enterprise Architecture development process followed the stages of TOGAF ADM namely the preliminary phase, architectural vision, business architecture, information system architecture, technology architecture, and making an architecture implementation roadmap. The results of the development of Enterprise Architecture are architectural artifacts consisting of catalogs, matrices, and diagrams of business, information system, and technology architecture. Based on the design results, it is found that the Enterprise Service Bus concept in Service Oriented Architecture can be used to support application and data integration in organization, as well as the concept of service access can bridge the gap between the business layer and the technology layer.
Analisis Perbandingan Metode Mobile-D Dan Prototype Pada Pembangunan Aplikasi E-Book Anak Usia Dini Puji Rahayu; Nirmala Rahmi; Widya Wicaksana
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 12, No 2 (2022): Volume 12 Nomor 2 Tahun 2022
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol12iss2pp124-131

Abstract

Literacy education in Indonesia is very low, which occupies the 62nd rank of 70 countries in the world. Based on the survey, one of the ways to increase the reading interest in the Indonesian people is to teach literacy education early in the age range of 3-6 years, where children begin to increase their cognitive, psychosocial and physical, and physical abilities. Therefore, we will develop an e-book as a learning medium to attract early childhood attention. The method used to develop this application is the Mobile-D method and prototype. The results of the test conducted on the E-Book Application of the Early Children's E-Book stated that all input forms and buttons in the system could run properly and the integrity of the output data on the input or the action carried out is following the user's expectations. The results of the analysis, design, implementation and comparison of the methods that have been carried out in the manufacture of this application show that the mobile-D development model is suitable for mobile development that can run on the system environment that accepts if there is a change or addition, the number of teams is a little, at level Applications, small-built systems and relatively short, development times. While the prototype development model is more suitable for systems made based on certain requests and needs by use.
Perbandingan Algoritma K-Means dan K-Medoids Untuk Pemetaan Daerah Penanganan Diare Pada Balita di Kabupaten Kuningan Tri Septiar Syamfithriani; Nita Mirantika; Ragel Trisudarmo
JSINBIS (Jurnal Sistem Informasi Bisnis) Vol 12, No 2 (2022): Volume 12 Nomor 2 Tahun 2022
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol12iss2pp132-139

Abstract

Diarrhea is an endemic disease that contributes to the high mortality rate in Indonesia, especially among children under five. The Kuningan District Health Office had difficulties in monitoring and supervising the spread of diarrheal diseases. This study aims to produce a mapping scheme of priority areas in handling the prevention and control of the spread of diarrheal disease in children under five in Kuningan Regency. The method used is the Data Mining Clustering method by comparing two algorithms, namely the K-Means algorithm and the K-Medoids algorithm. Determination of the optimum number of clusters using the Elbow and Silhouette Coefficient methods. With this method, the result is that in the K-Means algorithm the optimum number of clusters is 3 clusters while the K-Medoids algorithm is 2 clusters. The best cluster evaluation uses the Davies-Bouldin Index (DBI) method and the results show that the K-Means DBI value is always smaller than the K-Medoids algorithm in either 2 clusters or 3 clusters, this shows that the K-Means algorithm is better than the K-Medoids algorithm. Based on these results, it is recommended to map priority areas for handling diarrheal diseases using the K-Means algorithm with 3 clusters, namely medium priority areas consisting of 9 regions, high priority areas consisting of 3 regions and low priority areas consisting of 25 regions. The results of the mapping can be used as input for the Kuningan District Health Office to develop strategies for preventing and preventing diarrheal diseases in children under five.
Sentiment Analysis of Customer Reviews Using Support Vector Machine and Smote-Tomek Links For Identify Customer Satisfaction Dody Indra Sumantiawan; Jatmiko Endro Suseno; Wahyul Amien Syafei
Jurnal Sistem Informasi Bisnis Vol 13, No 1 (2023): Volume 13 Nomor 1 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss1pp1-9

Abstract

Shopping activities in the online market, especially fashion trends, continue to increase with all the promo efforts offered. One of the considerations for buying products on the online market is to read reviews. Each consumer review shows the level of interest in the product. The number of negative reviews and the emergence of many varied reviews pose a problem in categorizing reviews. Sentiment analysis is a way of looking at the polarity of reviews to classify positive and negative reviews. The Support Vector Machine method and the combination of the Synthetic Minority Oversampling Technique (SMOTE) with Tomek Links are applied in this study. Classification using the Support Vector Machine method and the combination of the Synthetic Minority Oversampling Technique (SMOTE) with Tomek Links showed better results with an Accuracy of 0.92, Precision of 0.89, Recall of 0.89, and F1-score of 0.89 than without the combination of the Synthetic Minority oversampling Technique (SMOTE) with Tomek Links with an Accuracy of 0.68, Precision of 0.55, Recall of 0.99, and an F1-score of 0.71.
Analisis Adopsi Sistem ERP dalam Mengoptimasi Industri Pangan Menggunakan SEM dan Model UTAUT2 Haryasena Panduwiyasa; Rachdian Habi Yahya
Jurnal Sistem Informasi Bisnis Vol 13, No 1 (2023): Volume 13 Nomor 1 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss1pp10-19

Abstract

In the era of Society 5.0 and the post-COVID-19 recession, entrepreneurs experienced digital disruption and economic instability, especially in the food industry sector. The low awareness of entrepreneurs in adopting technology and information systems, as well as their doubts about the high cost and time that needs to be allocated, are also reasons why the process of adopting technology and information systems is increasingly difficult to realize. To overcome costs and a relatively long development process, one of the efforts that companies can make is to adopt an open-source Enterprise Resource Planning (ERP) system that is useful for supporting resource management and decision-making. The purpose of this research is to prove how the adoption of ERP systems can support business digitalization processes and can produce industrial systems that are agile, effective and efficient. A series of analyzes were carried out using a survey aimed at 292 food industry business actors who had been digitalized by ERP, to prove the influence of behavioural factors on ERP usage using the UTAUT2 model, with the variables tested including performance expectations (PE), effort expectations (EE), price values (PV), facility conditions (FC), habits (HT), and behavioural intention (BI) toward the use behaviour of ERP (UB) in the food industry sector in Central Java, Indonesia.
Perbandingan Performa Cluster Model Algoritma K-Means Dalam Mengelompokkan Penerima Bantuan Program Keluarga Harapan warisa warisa; Nurahman Nurahman
Jurnal Sistem Informasi Bisnis Vol 13, No 1 (2023): Volume 13 Nomor 1 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss1pp20-28

Abstract

Poverty has so far played a role as a problem faced by residents of the Mentawa Baru sub-district, Ketapang. The inability of this community is related to the need to meet education and health needs in social welfare. In assisting the grouping of beneficiary data is carried out using the K-Means algorithm. Apart from that, to increase performance, those who have gone through the first grouping process are then continued using feature selection in the decision tree tool. The algorithm used aims to classify PKH beneficiary data to help the government find out about the handling of the aid program in Mentawa Baru Ketapang sub-district. As for the results obtained from this study, namely, the accuracy of the initial clustering obtained a DBI value of -0.994 at K=8 while the second clustering value that had gone through feature selection with K=3 obtained a DBI value of -0.865. It is known from the performance testing of the comparison of the two clustering that the best performance value is found in the second cluster after going through feature selection.
Implementasi Algoritma Fuzzy C-Means dalam Mengelompokkan Produktivitas Nauplius Vanammei di BBPBAP Jepara Nur Aeni Widiastuti; Raden Hadapiningradja Kusumodestoni; Buang Budi Wahono; Diah Ayu Chumaisaroh
Jurnal Sistem Informasi Bisnis Vol 13, No 1 (2023): Volume 13 Nomor 1 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss1pp37-44

Abstract

Balai Besar Perikanan Budidaya Air Payau often experiences changes in the number of vanammei shrimp production that is uncertain every day. This resulted in the scarcity of vanammei shrimp larvae seeds, unmet market demand and high selling prices. So that the BBPBAP experienced problems in monitoring the quality of the production of vanammei shrimp larvae. To overcome these problems, data mining is used as an alternative solution. The research method used is the Fuzzy C-Means algorithm. With the research stages starting from data collection, pre-processing data to clean data or attributes that are not suitable, clustering using the Fuzzy C-Means algorithm, testing using the MATLAB tool, and evaluating validation using the Davies Bouldin Index (DBI). Based on the results of the clustering that has been carried out from a total of 894 data, which are included in the good cluster, 569 data with the unfavorable category is 325. The results of the evaluation and validation obtained a value of 0.32 with the resulting cluster quality is optimum.
Perbandingan Pre-Trained CNN: Klasifikasi Pengenalan Bahasa Isyarat Huruf Hijaiyah Yulrio Brianorman; Rinaldi Munir
Jurnal Sistem Informasi Bisnis Vol 13, No 1 (2023): Volume 13 Nomor 1 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss1pp52-59

Abstract

The number of documented deaf people continues to increase. To communicate with each other, the deaf use sign language. The problem arises when Muslims with hearing impairment or deafness need to recite the Al-Quran. Muslims recite Al-Quran using their voice, but for the deaf, there are no available means to do the reciting. Thus, learning hijaiyah letters using finger gestures is considered important to develop. In this study, we use the recognition of hijaiyah letters based on pictures as the learning model. The real-time-based recognition then uses the learning model. This study uses 4 CNN pre-trained models, namely MnetV2, VGG16, ResNet50, and Xception. The learning process shows that MnetV2, VGG16, and Xception reach the accuracy limit of 99.85% in 2, 3, and 11 s, respectively. Meanwhile, ResNet50 cannot reach the accuracy limit after processing 100 s. ResNet50 achieves 82.12% accuracy. The testing process shows that MnetV2, VGG16, and ResNet50 achieve 100% precision, recall, f1-score, and accuracy. ResNet50 shows figures 81.55%, 86.04%, 82.04%, and 82.58%. The implementing process of the learning outcomes from MnetV2 shows good performance for recognizing finger shapes in real-time.
Implementasi Framework Laravel Dalam Pembuatan Sistem Pencatatan Notula Berbasis Website Ahmad Azhar Kadim; Lillyan Hadjaratie; Muthia Muthia
Jurnal Sistem Informasi Bisnis Vol 13, No 1 (2023): Volume 13 Nomor 1 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss1pp45-51

Abstract

Minutes of Meeting are notes that function to record the things discussed in a meeting agenda. Minutes of Meeting are important and must exist so that agreements and decisions can be saved, so that they can be discussed again on the agenda of the next meeting. With the development of current technology, it is hoped that it can be implemented in various ways, one of which is that Minutes which were previously only written in books can be presented on the website so that it can facilitate monitoring and evaluation quickly, precisely, anywhere, and anytime. This study aims to realize a Web-based E-Notulen system by utilizing the Laravel framework and the Waterfall method for design which includes Analysis, Data Requirements, Design, Development, Testing, and Implementation. Based on the method used, the E-Notulen system can be designed by utilizing the existing Laravel Framework library using the Waterfal method. The Waterfall method can be applied in system development, especially systems that require fast time from design to implementation such as the E-Minutes system.
Klasifikasi Penyakit Jantung Menggunakan Algoritma Analisis Diskriminan Linier Ibnu Rashad; R Rizal Isnanto; Catur Edi Widodo
Jurnal Sistem Informasi Bisnis Vol 13, No 1 (2023): Volume 13 Nomor 1 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss1pp29-36

Abstract

The number of documented deaf people continues to increase. To communicate with each other, the deaf use sign language. The problem arises when Muslims with hearing impairment or deafness need to recite the Al-Quran. Muslims recite Al-Quran using their voice, but for the deaf, there are no available means to do the reciting. Thus, learning hijaiyah letters using finger gestures is considered important to develop. In this study, we use the recognition of hijaiyah letters based on pictures as the learning model. The real-time-based recognition then uses the learning model. This study uses 4 CNN pre-trained models, namely MnetV2, VGG16, ResNet50, and Xception. The learning process shows that MnetV2, VGG16, and Xception reach the accuracy limit of 99.85% in 2, 3, and 11 s, respectively. Meanwhile, ResNet50 cannot reach the accuracy limit after processing 100 s. ResNet50 achieves 82.12% accuracy. The testing process shows that MnetV2, VGG16, and ResNet50 achieve 100% precision, recall, f1-score, and accuracy. ResNet50 shows figures 81.55%, 86.04%, 82.04%, and 82.58%. The implementing process of the learning outcomes from MnetV2 shows good performance for recognizing finger shapes in real-time.

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