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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 410 Documents
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Assessing Public Reaction to Artificial Intelligence in Promoting Green Tourism and Infrastructure Initiatives in Indonesia's New Capital Nusantara Fahlevi, Mochammad; Romli, Zainur; Asetya, Dimvy Rusefani; Dandi, Mochamad
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp179-184

Abstract

This study aims to answer these questions by examining the effectiveness of green tourism marketing strategies by the Indonesian government, utilizing social media platforms Instagram and X (formerly Twitter), and learning how the public perceives its initiative. We collected comments on government posts promoting green infrastructure and tourism and analyzed them using a mixed-method approach. Sentiments were divided into three categories: positive, neutral, and negative, using Natural Language Processing (NLP) techniques. The results reveal a general negative reception of AI-authored advertising messages, amounting to 64.18% disapproving comments for Instagram and 81.93% for X, both expressing suspicion toward the overuse of AI and lack of authenticity calling into question transparency as well as genuine intentions behind sustainability goals. While a few responders gave positive reviews, the fact that so many responses were bordering or fully negative indicates that there needs to be clearer and more genuine communication strategies. Our research helps illuminate how the public perceives aspects of green tourism marketing, thus underscoring the significance of authenticity in promotional practices designed for sustainable development.
Preface JSINBIS_15 (2) 2025 JSinbis, Editorial
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp%p

Abstract

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Smart Village Tourism: Barriers and Facilitators in Adopting a Smart City Perspective Using SWOT Analysis Widarti, Erni; Erkamim, Moh.; Nugraha, Tegar Wijanarko Surya
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp280-291

Abstract

This disruptive era, tourist villages must adapt to technological advancements to innovate and drive the digitalization of these villages. Data processing, speed, and clarity of information can be utilized for the development of smart village tourism, where innovation and technology become the main drivers of transformation. The smart city concept can be adopted in the development of smart village tourism to enhance sustainability in tourist villages. A deep and ongoing study of the potential and local wisdom of rural communities is a key factor in the development of smart village tourism. This research serves as a preliminary study in the context of smart village tourism. The aim of this study is to formulate a development model for smart village tourism based on the identification and analysis of the barriers and facilitators in adopting the smart city perspective. The case studies involve two tourist villages in Boyolali Regency. The data analysis method uses SWOT analysis (Strengths, Weaknesses, Opportunities, Threats). SWOT analysis is useful for evaluating various aspects of tourist villages and identifying strategies that can be implemented for development and improvement. These findings represent an initial step towards formulating the development of smart village tourism by adopting a smart city perspective based on an ICT model, aligned with local potential and wisdom as key factors for the sustainability of tourist villages.
IoT-based Recording of Waste Types and Weights in Waste Processing System Ishlakhuddin, Fauzan; Muhamad, Fachrul Pralienka Bani; Ismantohadi, Eka; Jannah, Miftahul
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp216-220

Abstract

Effective waste management requires the separation of waste types into categories such as organic, non-organic, and recyclable. This is necessary because not all types of waste can be processed. Therefore, accurate recording of waste types and weights is crucial in waste processing. A common issue today is that waste data is still recorded manually, leading to a lack of accuracy in the records. This research aims to develop an IoT-based waste type recording tool that can accurately record the weight and type of waste by retrieving values from a scale and transmitting the data in real-time to a waste processing system. The device development method used is the prototype model. This research successfully connected to and retrieved values directly from the Sayaki T-18 digital scale, ensuring that the weight values sent to the system are more accurate. During the testing of the developed IoT device, it accurately recorded and transmitted the quantity and type of waste as specified by the user, and the data stored in the system matched the test data accurately.
Detection of Nutritional Status using K-Nearest Neighbors on a Mobile Based Platform Puspaningrum, Alifia; Santosa, Yaqutina Marjani; Nugraha, Nur Budi
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp185-190

Abstract

In recent decades, health issues related to nutritional status have become a major concern for the Indonesian government. Malnutrition or overnutrition can severely impact individual health, especially in children and adolescents. If left unaddressed, these issues can lead to various diseases, ranging from malnutrition to obesity and their associated complications. Despite the recognized importance of monitoring nutritional status, several challenges remain. Manual monitoring systems require significant time and resources. Moreover, access to healthcare services and qualified medical personnel for regular nutritional assessments is limited, particularly in remote or underserved areas. Indonesia’s geographical complexity, consisting of thousands of islands, further complicates the equitable distribution of healthcare services. As a result, many cases of malnutrition or overnutrition go undetected early, causing delayed interventions. This research proposes the development of a K-NN-based mobile application to detect nutritional status. The application provides an initial diagnosis based on the user's physical parameters, such as weight, height, age, and gender. The dataset includes 120,999 samples, with 70% used for training and 30% for testing. Implementation of K-NN with k=7 achieved an accuracy of 91% on the test data, with the best performance in the normal category (F1-score 0.950), followed by stunted (0.889) and severely stunted (0.863). This platform has the potential to contribute to sustainable health systems, particularly in low-resource settings, by reducing reliance on energy-intensive infrastructure and minimizing the need for long-distance travel for healthcare. It could also support public health initiatives by enabling efficient large-scale population monitoring and reducing the environmental impact of traditional health services.
Back matter JSINBIS_15 (2) 2025 JSinbis, Editorial
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp%p

Abstract

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Identification of Grouper Fish Types using Convolutional Neural Network Resnet-50 Algorithm Nuraini, Rini; Syafei, Wahyul Amien; Wibowo, Adi; Jaya, Indra
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp173-178

Abstract

Grouper is a type of fish that is popular with the public. It is necessary to identify the type of grouper fish based on color patterns with increase the epoch value to get the best accuracy. The purpose of the research is to predict the type of grouper. This research use CNN Resnet-50 algorithm. 30 data used. The accuracy of prediction is 75 % to predict the image groupers. In the grouper prediction process, the more we increase the epoch value, we will get the best accuracy value. Epoch is a factor that affects the time of training an AI model and affects the accuracy value of the AI model.
Information System Development of Cattle Weight Recording and Forecasting Using Website-Based Linear Regression Suprihanto, Didit; Delwizar, Muhammad Arya; Burhandenny, Aji Ery; Harjanto, Arif; Nugroho, Happy; Rumawan, Fatkhul Hani
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp293-300

Abstract

Cattle plays an important role in meeting food demand in Indonesia, especially in the livestock sector, where cattle farms must be prepared to provide beef supply to various regions in Indonesia. On the other hand, in East Kalimantan, the demand for beef is also increasing along with the growth of population and economic activity. The role of technology is also quite important in meeting the need for beef. One of them is the use of website information system technology as a recording and reporting application. One of the distributors also involved in cattle farming in East Kalimantan is PT XYZ, which was newly established in 2020. The need for technology includes recording system, reporting system and cattle weight forecasting system. The purpose of this study is to design a web-based application that helps PT XYZ to record, report and predict cattle weight. The application development used Laravel framework to predict the increase in cattle weight using linear regression method. While the methodology used to develop the application was Waterfall method which included the phases of requirement analysis, application design, software development, testing and implementation. The application testing results showed that the application complied with the design that has been implemented and all the functions on the application page worked properly. The cattle weight recording and forecasting information system generated various reports, such as monthly cattle weight progress, monthly cattle sales reports, cattle weight growth forecast analysis, and cattle sales profit reports.
Machine Learning Methods for Academic Achievement Prediction: A Bibliometric Review Nugraha, Fajar; Widowati, Widowati; Sugiharto, Aris
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp221-226

Abstract

This study examines research trends regarding the prediction of academic achievement using machine learning. Research in the field of academic achievement is currently continuing to develop, but has not been explored comprehensively in a bibliometric context. The visualization provided includes a map of publication development using machine learning methods based on country, analysis of bibliographic pairs and keywords used. To find out the visualization results, bibliographic analysis was used using VOSviewer. The data used in this analysis were 76 articles collected from the Scopus database from 2018-2023. From the results of the analysis, it is known that research related to academic achievement still shows a growing trend in publications in the field of discussion of factors or predictors that influence academic achievement as well as research that proposes or evaluates models for predicting academic achievement. The research results show that although machine learning techniques such as Random Forest and Support Vector Machine are often used in academic achievement prediction research. Future research could consider developing a more adaptive and comprehensive approach regarding the contribution of specific factors that influence the accuracy of more in-depth prediction models in this field.
Harvest Data Processing Information System for Rice Productivity Prediction in Indramayu Regency Farismana, Riyan; Sholihah, Debi Nabilah; Lena, Sonty
Jurnal Sistem Informasi Bisnis Vol 15, No 2 (2025): Volume 15 Number 2 Year 2025
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/vol15iss2pp191-197

Abstract

Rice plants that are processed into rice are the staple food of the Indonesian people, and the lack of rice production will have an impact on weakening national food security. Efforts that can be made are to process harvest data in national rice barn areas such as Indramayu Regency properly. So far, there are still many errors and differences in harvest data both by agencies and original data in the field. Differences in data cause inaccurate harvest data to be used as a reference for policies or to see the potential of rice in Indramayu. This study aims to build a website-based data processing information system so that it can be accessed and managed by agricultural officers in all sub-districts in Indramayu, and the agricultural service as admin, so that the data produced is accurate data and provides predictions of harvest results, and makes predictions of future harvests based on harvest data, land area and rainfall that affect the rice harvest in Indramayu using fuzzy tsukamoto. From the predictions made, there are 16 sub-districts that have the potential to experience a decrease in harvest from 31 sub-districts in Indramayu. This information system also displays harvest data and graphs based on year and sub-district in Indramayu so that the increase or decrease in harvest in previous years can be seen compared to predictions for the coming year.

Page 38 of 41 | Total Record : 410

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