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International Journal of Computer and Information System (IJCIS)
Published by Institut Teknologi Bisnis AAS Indonesia
ISSN : -     EISSN : 27459659     DOI : https://doi.org/10.29040/ijcis
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering
The aim of this journal is to publish quality articles dedicated to all aspects of the latest outstanding developments in the field of informatics engineering. Its scope encompasses the applications of (but are not limited to) : 1. Artificial Intelligence 2. Software Engineering 3. System Design Methodology 4. Data mining and Big Data 5. Human and Computer Interaction 6. Mobile Computing 7. Soft Computing 8. Animation 9. Multimedia and Image Processing 10. Parallel/Distributed Computing 11. Machine Learning 12. Computational Lingustics 13. Data Comunication 14. Networking
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 188 Documents
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Artificial Intelligence System Integrated With Smartphone Application For Early Detection Of Stunting Based On Toddler Growth Index Iskandar, Dwi; Putri, Frestiany Regina; Kusuma, Junianto Chandra; Saputro, Rizal Tommy
International Journal of Computer and Information System (IJCIS) Vol 5, No 3 (2024): IJCIS : Vol 5 - Issue 3 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i3.185

Abstract

Toddlers have certain characteristics and needs that require growth monitoring. Toddlers will experience a period called the "Golden age" which is a period of experiencing a golden period in early life. What needs to be considered during the Golden Age of Toddlers is the record of weight, height, and head circumference of the child at each visit, then the results are recorded using the Healthy Menu Card. Collaboration between Artificial Intelligence and IoT can provide innovative and effective solutions, these two fields of science can be collaborated with IoT Sensors for measuring weight and height, data collection and storage, AI systems for data analysis, providing recommendations, notification systems and monitoring. The method used to complete this research is a literature study and data collection to find reference materials, design technology concepts, development preparation, hardware assembly, Arduino IDE coding, uploading coding to hardware, PHP (Hypertext Preprocessor) coding, uploading PHP (Hypertext Preprocessor) Code to hosting, coding .Apk (Android Package), technology trials. This application is available on two platforms, namely web-based and Android. Everyone can weigh, but to record data to the system, users must register to get an account and QR code. QR code is used to transfer weight and height data into the system, and the account allows the user to view all weighing data and history. The system also displays a graph containing height, weight, and upper and lower limits of ideal weight.
Classification of Cattle Diseases in Semin District Using Convolutional Neural Network (CNN) Permana, Xvan Erik Kobar; Rozaq Rais, Nendy Akbar; Muqorobin, Muqorobin
International Journal of Computer and Information System (IJCIS) Vol 5, No 2 (2024): IJCIS : Vol 5 - Issue 2 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i2.172

Abstract

Cattle farming is a crucial sector for the economy and food security in Semin District. However, cattle diseases pose a serious threat, leading to economic losses and animal welfare issues. Farmers' lack of understanding about cattle diseases hinders effective disease management, and some solutions implemented by farmers can worsen the condition of the animals. Therefore, this study aims to implement a disease classification system for cattle using Convolutional Neural Network (CNN). The diseases targeted in this study include three common threats to cattle in this region: Bovine Ephemeral Fever (BEF), Mastitis, and Scabies. With the advancement of technology, it is expected that cattle farmers in Semin District can minimize errors in diagnosing cattle diseases through the application of artificial intelligence (AI) for disease classification. The study utilized a dataset consisting of 864 training data and 216 validation data, achieving an accuracy of 1.0000 and a loss of 0.0040. For testing, the system achieved an accuracy of 0.9306 and a loss of 0.4430.
Used Car Price Prediction Model: A Machine Learning Approach Budiono, Daniel Aprillio; Utomo, Kevin Sander; Wibowo, Kenny Jinhiro; Wiradinata, Marcell Jeremy
International Journal of Computer and Information System (IJCIS) Vol 5, No 1 (2024): IJCIS : Vol 5 - Issue 1 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i1.147

Abstract

The impact of the Covid-19 pandemic over the past two years has slowed down the economy, including the market of used cars. However, the recent decline in the number of cases infected with Covid-19 has reignited interest in the used car market. One of many persisting issues found in the used car market is that sellers want the highest price possible; but, buyers and used car dealers bid the lowest price due to economic stability uncertainty. To accelerate the recovery of the used car industry, various innovations are required. This study proposes the use of the K-Nearest Neighbors (KNN) regression model to predict used car prices to address this issue. The proposed KNN model is a machine learning algorithm which is capable of handling multi-dimensional data and its robustness to noisy data, making it suitable for predicting used car prices based on multiple factors. By analyzing collected data on used car prices, a machine learning-based regression model can be developed to predict used car prices based on factors commonly used in the used car industry, such as year of production, car type, car condition, and others. This study makes use of 504 used car data collected through web scraping as a secondary data collection method. With a relatively small error rate of 8.3% and an R2 value of 98.8%, the results of this analysis can provide insight for used car buyers and sellers, to better gauge the price of used cars in the market.
Evaluating Effective Social Media Marketing With Artificial Intelligence Using The AIDA Model Approach Alia, Putri Ariatna; Cahyono, Warna Agung; Shodikin, Mohamad; Meisyarani, Jihan Salsabila; Sani, Rosi Rijal; Kriswibowo, Rony
International Journal of Computer and Information System (IJCIS) Vol 5, No 4 (2024): IJCIS : Vol 5 - Issue 4 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i4.205

Abstract

The rapid growth of information and communication technology, especially social media, has significantly changed the marketing landscape. In the face of this challenge, companies are increasingly adopting marketing strategies through social media to reach their intended target markets. This research aims to analyze the effectiveness of Social Media Marketing by utilizing Artificial Intelligence, especially ChattGPT and applying the AIDA Model approach (Awareness, Interest, Desire, Action). This research methodology uses descriptive qualitative methods with data collection through virtual ethnography and interviews from the Babelubozz online store using the Instagram platform: @grosirhijabtermurahsidoarjo. Artificial intelligence algorithms to analyze interaction patterns and user responses. The AIDA (Awareness, Interest, Desire, Action) model. used as a basis for measuring the stages of consumer awareness, interest, desire, and action in the context of marketing through social media. The results of this analysis provide an in-depth understanding of how companies can improve the effectiveness of their marketing campaigns on social media by optimizing each stage of the AIDA Model. Therefore, the marketing and promotional content generated by ChatGPT is able to increase the effectiveness of social media marketing.
Design of a Web-based Document Management Application at the Gunungsindur District Office Bogor Regency Safudin, Mahmud; Yulianto, Eko; Setiaji, Setiaji
International Journal of Computer and Information System (IJCIS) Vol 5, No 4 (2024): IJCIS : Vol 5 - Issue 4 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i4.195

Abstract

Efficient and secure digital archive management is crucial in the digital era. This research aims to develop a digital archive information technology system to facilitate document search and storage while enhancing data security through user authentication and authorization. The methodology includes requirements analysis, system design, implementation, and testing. Requirements analysis was conducted to understand user needs. System design involved creating an Entity Relationship Diagram (ERD) and Logical Record Structure (LRS). Implementation used PHP and MySQL. Testing was performed using the black box method to ensure system functionality according to specifications. The results indicate improved archive management efficiency, ease of document search, and enhanced data security. The system also allows for the integration of various types of archives into a structured platform. Recommendations for further development include regular security testing, adding a disposition feature, optimizing the search algorithm, and user training.
Expert System For Diagnosing Goat Diseases Using The Forward Chaining Method (case study of SHQ Nura Farm) Saputra, Aditya Aji; Efendi, Tino Feri; Pakarti, Moch Bagoes
International Journal of Computer and Information System (IJCIS) Vol 5, No 3 (2024): IJCIS : Vol 5 - Issue 3 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i3.178

Abstract

Goats are livestock that provide many benefits for human life, such as meat and milk. Healthy goats will produce quality meat and milk. good so it increases the selling price. Disease can interfere with the growth of goats and if left untreated can kill goats. Most of the farmers still have low knowledge about disease control, whereas goat livestock diseases thrive in tropical climates such as Indonesia. The number of experts available in rural areas is still limited. Information technology such as expert systems can help farmers carry out early treatment of diseases that attack goat livestock. An expert system is a system that tries to adopt human knowledge to a computer, so that the computer can solve a problem as experts usually do. The research here uses the forward chaining method to solve problems that exist in goat livestock. Forward Chaining is a reasoning inference method that uses facts to reach conclusions. The results obtained are in the form of a simple website application to help determine goat diseases and are easy to operate by entering symptom facts of 2 - 3 visible symptoms. The results of the system testing showed 80% accuracy in diagnosing diseases in goats.
Research on Relation Extraction Method Based on Active Learning Duan, Lianzhai
International Journal of Computer and Information System (IJCIS) Vol 5, No 2 (2024): IJCIS : Vol 5 - Issue 2 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i2.166

Abstract

The knowledge in contemporary society has exploded, and the most common knowledge is contained in unstructured natural language texts. Information Extraction technology expresses semantic knowledge in unstructured text through a set of mentioned entities, the relationships between these entities, and the events in which these entities participate. As a key part of information extraction, Relation Extraction technology provides important theoretical basis and use value for text knowledge understanding by judging the relationships between given entities. Currently, relationship extraction based on supervised learning requires a large number of labeled samples. Randomly selecting some data labels is not only a waste of data resources, but also directly affects the final accuracy of the classification model. In fact, with the development of data collection and storage technology, it has become very easy to obtain a large amount of unlabeled natural language text. Therefore, it is of great practical value to design an algorithm that can effectively utilize unlabeled sample sets for relationship extraction. In order to solve the above problems, this paper uses active learning as the starting point to implement a variety of sampling algorithms, mainly including uncertainty, diversity, representativeness and other algorithms. On the basis of verifying that active learning is suitable for relationship extraction tasks, through the fusion of multiple This sampling criterion ultimately yields an active learning sample selection strategy that is still effective under multiple data sets and multiple learning models. Experiments have proven that the multi-criteria fusion sampling strategy proposed in this article is an effective and universal strategy. Compared with multiple single-strategy sampling algorithms, it can achieve equivalent or higher classification accuracy on multiple data sets.
Predicting Cross-border E-commerce Purchase Behavior in Organic Products: A Machine Learning Approach Integrating Cultural Dimensions and Digital Footprints Ma, Xiaowen; Jiang, Xiaoxiao
International Journal of Computer and Information System (IJCIS) Vol 5, No 1 (2024): IJCIS : Vol 5 - Issue 1 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i1.212

Abstract

This study proposes an integrated machine learning approach for predicting cross-border e-commerce purchase behavior in organic products, incorporating cultural dimensions and digital footprints. Through the analysis of 1.2 million transactions across 15 major cross-border e-commerce platforms spanning 2021-2023, the research develops a novel predictive framework combining adaptive neural networks with cultural dimension analysis. The methodology employs a multi-stage data processing pipeline achieving 88.5% accuracy in cross-cultural prediction scenarios. Implementation of the proposed framework demonstrates significant improvements in market performance metrics, including a 23.5% increase in customer retention rates and 18.7% enhancement in conversion rates. The study introduces a sophisticated digital footprint analysis methodology, successfully processing 8.5 million interaction data points with a mean accuracy of 0.892 across different cultural contexts. Results indicate strong correlations (r=0.82) between cultural factors and purchasing patterns, validating the framework's effectiveness in cross-cultural prediction scenarios. The research contributes to both theoretical understanding of cross-border e-commerce dynamics and practical applications in international trade operations, while establishing new methodological approaches for integrating cultural dimensions with machine learning in e-commerce contexts.
Using an Institution Platform of E-Learning in English Language Teaching (ELT) Process at ITB AAS Indonesia Fitria, Tira Nur
International Journal of Computer and Information System (IJCIS) Vol 5, No 1 (2024): IJCIS : Vol 5 - Issue 1 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i1.150

Abstract

E-learning relies on technology. It requires hardware, software, and network infrastructure. Most e-learning environments today are Web-based, so they can be accessed via Web browsers (using HTTP) over a TCP/IP network such as a university or campus network. The objective of this research is to describe the implementation and to find the strengths and weaknesses of the institution's platform of e-learning in ITB AAS Indonesia. This research is descriptive qualitative research. The result analysis shows that ITB AAS Indonesia has an e-learning system that can be accessed at https://itbaas.ac.id/elearning/. The learning process may be governed or managed by a system based on LMS (Learning Management System). The implementation of online English teaching by using e-learning consists include planning, implementation, and evaluation. In preparing English language teaching, the lecture follows instructions for creating materials. Before uploading material, the English lecturer prepares the material file that he/she wants to upload, fills in all material identities (title of the material, choice of courses, choice of class, material content) then uploads material files. In the implementation of English Language Teaching, the English lecturer prepares the media of video conferencing in online learning. The English lecturer carries out online learning by using Zoom meetings and YouTube Live Streaming. In evaluation, the English lecturer can evaluate by giving the mid-term and final semester tasks in the e-learning platform. The e-learning system in ITB AAS Indonesia has advantages, of course, it also has disadvantages. Therefore, the process of improving the e-learning application is still required and needs to be improved for the success of the teaching and learning process.
Interactive Learning: Human Anatomy Mobile Application for Elementary Students Sipahutar, Lahmudin; Handayani, Nursyah
International Journal of Computer and Information System (IJCIS) Vol 5, No 4 (2024): IJCIS : Vol 5 - Issue 4 - 2024
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v5i4.198

Abstract

Student has a different method. One interesting learning method that can increase student interest is by utilizing multimedia. Multimedia applications in learning methods are quite interesting because they contain colored images, sound and even animation. Learning using multimedia makes a student not very dependent on the presence of a teacher. Where a teacher or lecturer only acts as a mediator and facilitator who helps the learning process of students or students to run well. A researcher can be carried out correctly by choosing a method to guide research activities. The process of collecting data then analyzing the data to conclude the research results. Method of observation in data search by observing directly at the research object. The method involves asking teachers and students questions about the anatomy of the human body in science lessons. The library method is carried out by collecting information according to the topic of the problem. This Android-based human anatomy learning application program for elementary school students was created using Android Studio for the display and processes running in it. Based on the results of the research and discussion, it can be concluded that this mobile learning application for human body anatomy for elementary school children can be achieved using the MDLC (Multimedia Development Life Cycle) method which is carried out to the testing stage and using developer tests with the Black box testing method, so that the application Mobile-based learning for elementary school children.

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