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Jurnal Sistem Informasi dan Ilmu Komputer
Published by International Forum of Researchers and Lecturers
ISSN : 29865158     EISSN : 29864976     DOI : 10.59581
Core Subject : Science,
Computer Science & IT
Jurnal Sistem Informasi dan Ilmu Komputer berfokus pada publikasi hasil penelitian, kajian konseptual, dan pengembangan keilmuan di bidang Sistem Informasi dan Ilmu Komputer. Jurnal ini bertujuan menjadi media diseminasi ilmiah bagi akademisi, peneliti, dan praktisi dalam pengembangan serta penerapan teknologi informasi yang inovatif dan berkelanjutan. Ruang Lingkup Ruang lingkup jurnal mencakup, namun tidak terbatas pada, topik-topik berikut: Bidang Sistem Informasi Analisis dan Perancangan Sistem Informasi Manajemen Sistem Informasi Sistem Informasi Manajemen Sistem Enterprise (ERP, SCM, CRM) Sistem Pendukung Keputusan Business Intelligence dan Data Warehouse Tata Kelola Teknologi Informasi Audit dan Keamanan Sistem Informasi E-Government dan E-Business Bidang Ilmu Komputer Rekayasa Perangkat Lunak Kecerdasan Buatan (Artificial Intelligence) Machine Learning dan Deep Learning Data Mining dan Big Data Jaringan Komputer dan Keamanan Jaringan Internet of Things (IoT) Pengolahan Citra dan Visi Komputer Sistem Terdistribusi dan Cloud Computing Human-Computer Interaction (HCI)
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 169 Documents
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Klasifikasi Penyakit Demam Berdarah Dengue dengan Menggunakan Algortima K-Mens
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4251

Abstract

Dengue fever (DHF) is an infectious disease caused by the dengue virus and transmitted through the bite of the Aedes aegypti mosquito. This disease is a major health problem in many tropical countries, including Indonesia. Identification and classification of DHF patients is very important to prevent further spread and to provide appropriate medical treatment. In this study, the classification of DHF disease is carried out using the K-Means algorithm, which is one of the methods in machine learning used to classify data based on similarity of features. This study aims to apply the K-Means algorithm in classifying DHF cases based on data on symptoms that appear in patients, such as high fever, joint pain, skin rashes, and others. The data used includes patient medical records that record various clinical and demographic parameters. The K-Means algorithm is used to group the data into clusters that describe the severity category or potential risk of dengue disease. The results showed that the K-Means algorithm can be used to cluster DHF patients well, with the division of groups that can describe the severity of the disease. Evaluation was conducted using metrics such as silhouette and cluster validity to assess the effectiveness of the algorithm in performing classification. This model is expected to help medical personnel in decision-making, provide early warning, and improve rapid response to dengue cases.
Pengembangan Sistem IoT untuk Pemantuan Kehadiran Mahasiswa Berbasis Sensor Wajah dan RFID di Kampus Menggunakan Metode Radio Frequency Identification(RFID)
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4260

Abstract

Student attendance monitoring is a crucial aspect in education to ensure that students are present in classes and to minimize the potential for fraud. In this study, we developed an Internet of Things (IoT) system to monitor student attendance on campus using two main technologies: facial recognition and Radio Frequency Identification (RFID). The system utilizes RFID technology to identify students through RFID cards issued to each student, as well as facial recognition sensors for additional verification to enhance accuracy and security. This system is designed to provide convenience, security, and efficiency in the attendance process on campus.
Pengembangan Sistem Informasi Akuntansi untuk Meningkatkan Efisiensi dan Akurasi: Studi Kasus pada Implementasi Perubahan Program Akuntansi Juvent Ade Pratama; Rayyan Firdaus
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4266

Abstract

This article discusses the development of accounting information systems to improve efficiency and accuracy, focusing on a case study of the implementation of accounting program changes. Previous studies have shown that effective accounting information systems can significantly improve the quality of accounting and managerial information. The implementation of accounting program changes often involves the integration of information technology to improve the process of financial reporting, internal control, and analysis of company performance. Previous studies have shown that companies that adopt information technology in their accounting systems have a competitive advantage in managing and analyzing financial information more efficiently. Important factors in the development of accounting information systems are the need to ensure data accuracy, reporting speed, and real-time availability of information for internal and external stakeholders. This study also explores the positive impact of the use of accounting information systems on the company's operational efficiency and strategic decision making. Successful implementations show that modern accounting information systems are able to integrate various business functions, such as finance, inventory, and manufacturing, to improve the coordination and effectiveness of the organization as a whole. Thus, the development of accounting information systems not only improves the company's internal processes but also enhances the company's adaptability to rapid and complex changes in the business environment. This study provides a strong theoretical foundation for understanding the importance of information technology integration in the context of accounting program changes to achieve higher efficiency and accuracy goals.
Penerapan Klasifikasi Gambar Buah dalam Aplikasi FruityLens Menggunakan Metode CNN Bagus Hardika; Mahesa Dzikri Kurniawan; Muhammad Adzka; Daffarizqy Prastowiyono; Apik Banyubasa; Gema Parasti Mindara; Endang Purnama Giri
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4275

Abstract

This research develops a fruit classification system using Convolutional Neural Network (CNN) in the educational application FruityLens, which helps children recognize different types of fruits through image recognition. The application can identify four types of fruits: apple, banana, orange, and watermelon, utilizing an image dataset from open sources. The research methods include dataset collection, image pre-processing, CNN model training, and classification accuracy evaluation. The results indicate that the developed CNN model achieves high accuracy, supporting children's learning about fruits. This implementation is expected to contribute to the advancement of artificial intelligence technology, specifically in the field of fruit object recognition.
Tingkat Kepuasan Kinerja IT Support di Divisi Marketing pada PT. Jalatama Artha Berjangka menggunakan Metode Service Quality Mohamad Hilal Monoaarfa; Rouli Doharma
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4279

Abstract

In this study, the researcher uses a quantitative research type, namely the researcher collects data on a certain population or sample. While the study was conducted in the marketing division at PT. Jalatama Artha Berjangka to analyze and calculate statistics using the service quality method. The results of this study are in the marketing division of PT Jalatama Artha Berjangka, I can draw the following conclusions: indicating that the satisfaction of IT Support performance in the Marketing Division at PT. Jalatama Artha Berjangka has not met expectations. Evaluation using the Service Quality method reveals a gap between expectations and performance provided by IT Support services and improvements and enhancements in IT Support services in the marketing division need to be prioritized to improve service quality and achieve a better level of satisfaction. Thus, this study provides an understanding of the condition of IT Support performance satisfaction in the Marketing Division of PT. Jalatama Artha Berjangka and highlights the importance of improvement efforts to increase user satisfaction with IT Support services.
Sistem Deteksi Bahasa Isyarat Alfabet Menggunakan Dataset American Sign Language (ASL) dan Algoritma Random Forest Siti Farah Fakhirah; Muhammad Fillah Alfatih; Hasna Nabiilah Widiani; Thoriq Muhammad Pasya; Endang Purnama Giri; Gema Parasti Mindara
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 4 (2024): November : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i4.4321

Abstract

Introducing alphabetical sign language is necessary to bridge communication between deaf and hard-of-hearing people and their surrounding environment. This research aims to develop a sign language alphabet letter detection system based on American Sign Language (ASL). The research methods include data collection, feature extraction with OpenCV and Mediapipe, model development with Random Forest algorithm, and real-time system testing. The test results show that the developed system can achieve 97% prediction accuracy in recognizing hand patterns that represent ASL letters. The system uses a webcam as real-time input, providing accurate responses in various environmental conditions. This research contributes significantly to developing communication support technology for the deaf community, with implications for increased inclusivity and social engagement.
Pemanfaatan Canva sebagai Alat Kreatif untuk Meningkatkan Strategi Promosi GURAFIX: Bisnis Jasa Desain Grafis
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i1.4369

Abstract

In the rapidly evolving digital era, business promotion strategies have undergone significant transformations, particularly through the utilization of online graphic design platforms. This study aims to explore the use of Canva as a creative tool to enhance the promotional strategies of GURAFIX, a graphic design service business. The method employed is qualitative with direct observation techniques and portfolio analysis. The findings indicate that Canva plays a crucial role in improving the productivity and efficiency of the GURAFIX team in producing visually appealing content aligned with current market trends. Utilizing Canva has also positively impacted the quality of designs and promotional appeal, contributing to an increase in clients. However, the study also identifies Canva's limitations in meeting advanced design requirements. This research provides practical implications for other graphic design service businesses to optimally utilize Canva as part of their promotional strategies.
Penggunaan Artificial Intelligence dalam Klasifikasi Kandungan Gula pada Minuman Berpemanis Yulita Sirinti Pongtambing; Rasyad Bimasatya; Eliyah Acantha Manapa Sampetoding
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i1.4386

Abstract

Excessive sugar consumption has become a serious public health problem. Increasing patterns of food and drink consumption in line with changes in modern lifestyles have contributed to an increase in the prevalence of non-communicable diseases such as obesity, type 2 diabetes and cardiovascular disorders. This study analyzes and analyzes the use of Artificial Intelligence (AI), especially Deep Learning techniques and Neural Network algorithms, in the classification of sugar content in sweetened drinks. The Systematic Literature Review (SLR) method was used to filter relevant studies published between 2020-2024. The study results show that AI is able to provide more efficient and accurate solutions than manual methods. However, although the literature results show great potential, the application of AI in sugar content classification still requires further empirical research. This study emphasizes the importance of developing AI models tailored to the characteristics of sweetened drinks to support consumer decision making regarding healthier drink choices.
Masa Depan Bio Informatika : Mengubah Data Menjadi Terapi
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i1.4410

Abstract

Bioinformatics is an interdisciplinary field that combines biology, computer science and statistics to analyze biological data and translate it into effective therapies. With technological advances, such as next-generation genetic sequencing, bioinformatics enables the development of personalized therapies based on an individual's genetic profile. This approach provides more effective treatment and reduces the risk of side effects. In addition, the integration of artificial intelligence (AI) accelerates big data analysis, predicts therapy response and identifies disease biomarkers. Despite challenges such as the need for big data infrastructure and ethical privacy issues, the outlook for bioinformatics is bright. Through global collaboration and a multi-omics approach, bioinformatics is expected to become a key foundation in future medical therapy innovation.
Sistem Kecerdasan Buatan dalam Bioinformatika : Trend dan Potensi di Masa Depan
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 3 No. 1 (2025): Februari : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v3i1.4430

Abstract

In recent decades, artificial intelligence (AI) has significantly advanced and shown great potential across various fields, including bioinformatics. This paper examines current trends in AI applications within bioinformatics, highlighting future potentials and the challenges of integrating these technologies. The research utilizes secondary data collection from scientific literature, books, conference reports, and official documents on AI and bioinformatics, sourced from reputable databases like Scopus, IEEE, PubMed, and Google Scholar. Through comparative analysis, similarities, differences, and technological advancements were identified and discussed. Descriptive narrative interpretation was employed to provide a holistic view of AI trends and potential in bioinformatics. Key findings indicate that AI, particularly machine learning and deep learning, is instrumental in genomic data analysis, protein structure prediction, drug discovery, and clinical bioinformatics. Furthermore, the study underscores the benefits of AI in enhancing data analysis accuracy and efficiency, while addressing ethical and technical challenges. Future prospects emphasize the importance of interdisciplinary collaboration to fully leverage AI's capabilities in bioinformatics.

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