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INDONESIA
Journal of Information Systems and Informatics
Published by Asosiasi Doktor Sistem Informasi Indonesia
ISSN : 26565935     EISSN : 26564882     DOI : 10.63158/journalisi
Core Subject : Science,
Computer Science & IT
Journal-ISI is a scientific article journal that is the result of ideas, great and original thoughts about the latest research and technological developments covering the fields of information systems, information technology, informatics engineering, and computer science, and industrial engineering which is summarized in one publisher. Journal-ISI became one of the means for researchers to publish their great works published two times in one year, namely in March and September with e-ISSN: 2656-4882 and p-ISSN: 2656-5935.
Arjuna Subject : -
Articles 653 Documents
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Design and Development of the Mobile-Based Hydroponic Planting Machine Application MyHydro Christanto, Henoch Juli; Sutresno, Stephen Aprius; Lim, Ricardo Jonathan; Angkur, Lusiana V.G; Charmelita, Pauelina; Valentina, Vierena; Dewi, Christine
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.581

Abstract

In the contemporary era, technological advancements have significantly impacted various aspects of human life, offering increased efficiency and convenience. Indonesia, aiming to enhance international competitiveness, recognizes the importance of integrating technological innovation across economic sectors. Despite its abundant natural resources, Indonesia's vital agricultural sector faces challenges, including the limited adoption of modern technology, resulting in suboptimal productivity. This study focuses on addressing these challenges by developing the MyHydro mobile application, utilizing IoT and Progressive Web App (PWA) technology to enable remote monitoring and control of hydroponic systems. The research methodology includes literature review, user requirement analysis, system design, and black-box testing. Results show that MyHydro successfully bridges the gap between traditional farming practices and modern technology. Users can efficiently monitor and control hydroponic systems, enhancing crop yields and promoting sustainability in Indonesian agriculture. In conclusion, MyHydro offers a valuable solution to modernize Indonesian farming, aligning with global trends in smart agriculture. It empowers farmers and contributes to the nation's agricultural growth.
The Assessing Cimenyan Village's IT Readiness for Digital Transformation in West Java Majapahit, Sali Alas
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.582

Abstract

Digital Village Development has become an important agenda in efforts to modernize and improve the quality of life in rural areas. This transformation relies on the use of information and communication technology (ICT) to increase convenience and efficiency in various fields. The success of developing a Digital Village depends on the readiness of ICT infrastructure. The village office, which is the center for administration and services to the community, must have adequate ICT infrastructure as the main requirement for activating various digital initiatives. The research was conducted to determine the current state of readiness of Cimenyan village, Bandung Regency in implementing ICT in village government offices. The readiness level analysis is prepared based on the COBIT framework in 3 domains, namely: IT process domain PO1 (defining IT strategic plans), PO2 (determining information architecture), and PO4 (defining IT processes, IT organization, and their relationships) The results of the analysis will be mapped based on the maturity level of each domain in COBIT. The level of maturity obtained will help the Cimenyan Village government to make appropriate preparations for implementing ICT so that the goal of Cimenyan Village becoming a digital village in West Java can be achieved.
Cybersecurity Cloud-Based Online Learning: A Literature Review Approach Malele, Vusumuzi
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.583

Abstract

Cloud-based online learning is the electronic learning activity that supports teaching and learning (T&L) that could be done from anywhere and in the world. Some of its benefits are scalability and affordability that could in a decision-making support on the mechanisms of material selection. Cloud computing has been adopted by most universities around the world. In this regard, lecturers and students will use it to facilitate T&L; however, due to concerns of information technology or systems security, cloud-based online learning users are also not immune. In this regard, the users could be affected by different cybersecurity attacks. In this paper, a systematic literature review method was used to sift the different models and solutions used to address the cybersecurity concerns surrounding cloud-based online learning. A brief Likert-scale questionnaire was used to obtained data that could corroborate the systematic literature findings. In this regard, a group of 20 online learning designers were sampled as participants. It was found that the confidentiality, integrity, and availability issues are a concern. This led to issues of security awareness, authentication and blended attacks being issues. In this regard, a cloud-based online learning model is not immune from security issues. In this paper, a conceptual framework as the line-of-defense is proposed as a solution towards having a cybersecure cloud based online learning.
The Problem of Data Extraction in Social Media: A Theoretical Framework Chani, Tarirai; Olugbara, Oludayo O; Mutanga, Bethel
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.585

Abstract

In today's rapidly evolving digital landscape, the pervasive growth of social media platforms has resulted in an era of unprecedented data generation. These platforms are responsible for generating vast volumes of data on a daily basis, forming intricate webs of patterns and connections that harbor invaluable insights crucial for informed decision-making. Recognizing the significance of exploring social media data, researchers have increasingly turned their attention towards leveraging this data to address a wide array of social research issues. Unlike conventional data collection methods such as questionnaires, interviews, or focus groups, social media data presents unique challenges and opportunities, demanding specialized techniques for its extraction and analysis. However, the absence of a standardized and systematic approach to collect and preprocess social media data remains a gap in the field. This gap not only compromises the quality and credibility of subsequent data analysis but also hinders the realization of the full potential inherent in social media data. This paper aims to bridge this gap by presenting a comprehensive framework designed for the systematic extraction and processing of social media data. The proposed framework offers a clear, step-by-step methodology for the extraction and processing of social media data for analysis. In an era where social media data serves as a pivotal resource for understanding human behavior, sentiment, and societal dynamics, this framework offers a foundational toolset for researchers and practitioners seeking to harness the wealth of insights concealed within the vast expanse of social media data.
Application of Clustering-Based Data Mining for the Assessment of Nutritional Status in Toddlers at Community Health Centers Fianty, Melissa Indah; Johan, Monika Evelin; Aulia, Azka; Veronica, Mella Margareta
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.586

Abstract

Nutritional status is a crucial foundation for human health and development. Global facts indicate serious challenges in ensuring adequate nutrition, and the situation is no different in Indonesia. This research collected data from the Kelapa Dua Tangerang community health center and utilized data mining techniques with the k-means clustering algorithm to delve deeper into the nutritional status of toddlers. The research findings revealed that nearly 37.3% of toddlers experience issues with abnormal height or weight, as well as poor nutritional conditions, highlighting the importance of careful and timely intervention. With regular health monitoring by community health centers and active parental involvement, actions can be taken to support the optimal growth and development of these children. The results of this research provide a strong understanding to address malnutrition issues, which will ultimately support the formation of a healthier and more promising future generation in Indonesia.
Development of Web-based Application for Private School Tuition Fee Management with Prototyping Model Wiratama, Jansen; Johan, Monika Evelin; Sobiyanto, Sobiyanto; Wijaya, Matthew Chandra; Sugara, Victor Ilyas
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.588

Abstract

Private schools need help in handling school fees and financial processes. Traditional manual payment systems result in data processing issues, delayed financial reporting, and complications from misplaced records. Late fee payments threaten school income, which is crucial for staff salaries. Modern solutions are imperative. Desktop applications have limitations, requiring installation on specific devices, leading to compatibility concerns. This research opts for a web-based application. It employs prototyping models and predictive abilities using the Naïve Bayes algorithm. The web-based application aims to streamline fee management and predict payment delays, enhancing financial transaction management while prioritizing data security through database encryption. This web-based solution aligns with private schools' operational needs, simplifying payments and increasing late payment prediction accuracy. Extensive black-box testing validated its suitability, satisfying administrative staff needs. Four test cases gained administrative team approval. This innovation empowers private schools to optimize operations and financial management. In summary, the research tackles critical financial challenges private schools face by introducing a web-based application that simplifies payment processes, enhances accuracy in predicting late payments, and aligns seamlessly with administrative needs.
Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting for Supplier Measurement In Furniture Business Rwanda, Rwanda; Oetama, Raymond Sunardi
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.589

Abstract

This study delves into the complexities of supplier selection in the furniture industry, where Decision Support Systems play a pivotal role in achieving data-driven, sustainable supplier choices. It underscores the Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting approach, particularly emphasizing Price, response time, and delivery fees as critical factors. The overarching objective is to elevate supplier selection in alignment with furniture companies' specific requirements and strategic goals. Additionally, the Supplier Ranking System leverages Fuzzy Multiple Attribute Decision Making and Simple Additive Weighting techniques, ranking the third Supplier as the top Supplier with a high preference score of 0.90 and the fourth Supplier as the lowest-ranked Supplier with a score of 0.50. Notably, User Acceptance Tests affirm the System's outstanding performance and intense user satisfaction.
Comparing the Prediction of Numeric Patterns on Form C1 Using the K-Nearest Neighbors (K-NN) Method and a Combination of K-Nearest Neighbors (K-NN) with Connected Component Labeling (CCL) Suriani, Uci; Kurniawan, Tri Basuki
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.592

Abstract

Indonesia's elections serve as a cornerstone of its democratic system, with the active participation of its citizens being of paramount importance. To bolster transparency and civic engagement during these elections, the SITUNG system (Election Result Information System) is employed for the tabulation of election results. However, the current tabulation process remains manual, potentially leading to data entry errors and a reduced accuracy of election outcomes. This research endeavor seeks to enhance the efficiency and accuracy of election result tabulation by employing the K-Nearest Neighbors (K-NN) method for recognizing numeric patterns on Form C1, both independently and in combination with Connected Component Labeling (CCL). The K-NN method demonstrates a commendable 60.0% accuracy in recognizing numeric patterns from the original Form C1 data. However, when combined with CCL, the accuracy drops to 51.2%. This research makes a significant contribution by simplifying the tabulation process and improving the accuracy of election results in Indonesia through the application of the K-NN method. The technology is anticipated to fortify democracy by promoting a more transparent and participatory electoral process for the citizens.
Enhancing Digital Forensic Investigation: A Focus on Compact Electronic Devices and Social Media Metadata Tuharea, Ibnu Rohan; Luthfi, Ahmad; Ramadani, Erika
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.594

Abstract

The rise of portable electronic devices and social media has led to new criminal activities, necessitating advancements in digital forensics. This paper introduces Small-Scale Digital Device Forensics (SSDDF), focusing on the forensic examination of miniature digital devices often used in crimes. SSDDF addresses the challenges posed by these devices, particularly in extracting and analyzing data from them. A key aspect of this research is exploring ontology in social media forensics, particularly within the Android operating system. This involves extracting digital evidence like user accounts, messages, and images from social media platforms. While the paper primarily focuses on social media data, it acknowledges the importance of the devices used in crimes. The integration of SSDDF and the analysis of Android system structures are highlighted as key advancements in digital forensic methodologies. These enhancements are expected to improve the process of collecting and analyzing digital evidence from both compact electronic devices and social media platforms. The study offers significant contributions to the field of digital forensics. It provides new strategies for more efficient and effective forensic investigations, especially in the context of extracting and analyzing digital evidence from small electronic devices and social media, thus paving the way for more robust digital evidence handling in future forensic inquiries.
Detection of Hate Speech Code Mix Involving English and Other Nigerian Languages Ndabula, Joseph Nda; Olanrewaju, Oyenike Mary; Echobu, Faith O
Journal of Information System and Informatics Vol 5 No 4 (2023): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v5i4.595

Abstract

Hate speech is a recurrent event and has become a cause for global concern. The proliferation of hate speech has recently become prevalent, breeding room for violence and discrimination against specific individuals or groups. In Nigeria, message masking (use of language-mix) has become the new normal, especially in disseminating hateful and inciting comments. Hence, there is a need to curb the spread over social media. Therefore, this research focuses on detecting hate speech on social media with a code-mix of English, Pidgin and any of the three major Nigerian languages (Hausa, Igbo and Yoruba). The research used two machine learning algorithms: Support Vector Machine (SVM) and Random Forest (RF). Data were collected from tweets on the EndSARS protest and the 2023 Nigerian elections. The major features were extracted, and the text was converted into vectors using TF-IDF and Bag-of-words (BoW), which were used to train and test the model. The result showed that SVM performed better in classifying hate speech than RF on both TF-IDF and BoW features, averaging 93.43% for accuracy, 93.70% for precision, 93.43% for recall, and 93.57% for F1-score.

Page 28 of 66 | Total Record : 653

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