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Ir. Rosyid Ridlo Al-Hakim, S.Kom., S.Si., M.T.
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LPPM Universitas Harapan Bangsa Kampus 1 Universitas Harapan Bangsa Jl. Raden Patah No.100, Kedunglongsir, Ledug, Kec. Kembaran, Kabupaten Banyumas, Jawa Tengah 53182 Phone: (0281) 6843493
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KORISA: Jurnal Kolaborasi Riset Sarjana
Published by Universitas Harapan Bangsa Purwokerto
ISSN : -     EISSN : 30639263     DOI : -
Core Subject :
Jurnal KORISA: Jurnal Kolaborasi Riset Sarjana mencakup, namun tidak terbatas pada, topik-topik berikut: Ilmu Sains dan Teknik: Teknologi informasi, rekayasa/keteknikan, fisika, kimia, biologi, ekologi, dan energi terbarukan. Kesehatan dan Kedokteran: Kesehatan masyarakat, kedokteran, bioteknologi, keperawatan, farmasi, dan teknologi kesehatan. Ilmu Sosial dan Humaniora: Sosiologi, psikologi, antropologi, ekonomi, manajemen, dan bisnis. Ilmu Hukum: Hukum publik dan privat, hukum teknologi, regulasi kesehatan, dan hukum internasional. Ilmu Pendidikan: Inovasi dalam metode pengajaran, kebijakan pendidikan, teknologi pendidikan, dan psikologi pendidikan.
Arjuna Subject : -
Articles 31 Documents
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Penerapan Logika Fuzzy dalam Penanganan Penyakit Diabetes: Sistematik Literatur Review Dimas Febri Kuncoro; Purwono
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 1 No. 1 (2024): Jurnal Kolaborasi Riset Sarjana Volume 1 Nomor 1 Januari 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

This study presents an overview of the use of fuzzy methods in the diagnosis and prediction of diabetes mellitus. Fuzzy logic approaches have attracted attention in diabetes management due to their ability to overcome uncertainty and vagueness in medical data. Through the Literature Review research method, related articles selected from online databases have been systematically analyzed to evaluate the various approaches that have been developed. Findings from the literature review show that the use of fuzzy methods in diabetes diagnosis and prediction has resulted in significant progress, with some studies achieving high levels of accuracy. However, some challenges such as dataset limitations and dependency on certain features were also identified. In addition, the potential and challenges of fuzzy logic in diabetes diagnosis are discussed, including opportunities to improve diagnostic interpretation and comorbidity of medical data.
Penggunaan Logika Fuzzy dalam Deteksi Penyakit Kanker Lutviana; Aimar Yudhistira; Anggit Wirasto
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 1 No. 1 (2024): Jurnal Kolaborasi Riset Sarjana Volume 1 Nomor 1 Januari 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

Cancer detection and treatment is a major challenge in global health. Fuzzy logic has proven to be effective in overcoming uncertainty and ambiguity in medical data to improve the accuracy of cancer diagnosis. This article presents a review of the application of fuzzy logic in various cancer detection and treatment studies, including its use in the analysis of medical images such as CT scans and MRIs. Studies show that fuzzy logic not only improves cancer detection accuracy but also reduces the cost and time in the diagnosis process. The results suggest that a hybrid approach combining fuzzy logic with technologies such as artificial neural networks can significantly improve the efficiency and accuracy of cancer detection
Penggunaan Blockchain dalam Rekam Medis Elektronik: Tinjauan Literatur Sistematis Ali Sya’bana Syukurillah; Lutviana; Purwono Purwono
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 1 No. 1 (2024): Jurnal Kolaborasi Riset Sarjana Volume 1 Nomor 1 Januari 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

Electronic medical records (eMR) play a critical role in modern healthcare systems, providing medical information necessary for diagnosis, treatment, and disease management. However, security and accessibility concerns have hampered progress in eMR management. In recent years, blockchain technology has emerged as an innovative solution to overcome these challenges. By applying blockchain principles in eMR management, interesting solutions have been proposed to improve the security, integrity and accessibility of medical data. However, blockchain implementation in eMR is still in the experimental stage and faces several challenges, including infrastructure readiness and high implementation costs. Through this research, we conducted a systematic review of existing literature to identify trends, advantages, disadvantages, and potential benefits of using blockchain in eMR management.
Potensi dan Tantangan Implementasi Blockchain dalam Pengelolaan Citra Medis: Sebuah Tinjauan Literatur Hani Istiqomah; Khoirun Nisa
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 1 No. 1 (2024): Jurnal Kolaborasi Riset Sarjana Volume 1 Nomor 1 Januari 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

Blockchain technology offers a secure, decentralized approach to managing medical data in healthcare. This literature analysis highlights blockchain's potential to enhance data security, reduce manipulation risks, and improve patient privacy by granting individuals control over their medical information. It also boosts data reliability and cyberattack resistance, crucial in healthcare. However, challenges like high energy consumption and computational complexity remain. Further research is necessary to develop efficient solutions for blockchain integration in healthcare, ensuring safe, reliable, and effective data management while addressing these challenges
Pemanfaatan Logika Fuzzy dalam Sektor Pertanian: Sebuah Kajian Literatur Sari Andini Putri; Hani Istiqomah; Anggit Wirasto
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 1 No. 1 (2024): Jurnal Kolaborasi Riset Sarjana Volume 1 Nomor 1 Januari 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

Agriculture is essential to meet the world's food needs, especially with the increasing global population requiring higher food production. Smart agriculture with technologies such as the Internet of Things (IoT) and fuzzy logic can improve agricultural efficiency and productivity. Fuzzy logic, which allows linguistic variables to have more flexible membership degrees, is used in intelligent irrigation systems, productivity prediction, and land use planning. This study reviews systematic literature (SLR) to explore the applications and benefits of fuzzy logic in agriculture, as well as the challenges of its implementation. Results show that fuzzy logic has great potential to improve agricultural efficiency, but faces challenges in implementation. This research paves the way for further studies in this area
Smartphone dan Perkembangan Kognitif Anak Usia Dini: Studi di Desa Ledug, Banyumas Wiharti Juniati; Murniati Murniati; Noor Triana
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 2 No. 3 (2025): Jurnal Kolaborasi Riset Sarjana Volume 2 Nomor 3 September 2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

Toddlers between the ages of one and three undergo a crucial phase of rapid growth and development, including cognitive enhancement. Smartphone usage can influence cognitive development, the process by which children acquire thinking skills. The utilization of smartphones may have both beneficial and adverse effects on cognitive development. This study is to investigate the relationship between cognitive development in children aged one to three and their smartphone usage in Ledug Village, Banyumas Regency. This research is categorized as cross-sectional correlational investigation. The study's population consisted of 65 toddlers from Posyandu Margo Sari in Ledug Village. Methodology for intentional sampling utilizing inclusion and exclusion criteria. The Capute Scale evaluates cognitive development, whereas the study's independent variable is the degree of an individual's smartphone utilization. Data processing includes editing, coding, scoring, tabulating, and doing Spearman Rank test analysis. Of the 37 respondents, the majority (18, or 49%) indicated moderate to heavy smartphone usage, while a larger majority (21, or 57%) reported assessing the results of presumed cognitive enhancement. The results of the Spearman's Rho Rank correlation test indicate a positive correlation and moderate degree of connection, resulting in the rejection of H0, with a p-value of 0.003 (p-value < 0.05; Rho = 0.481). The study's findings indicate a relationship between the extent of smartphone usage and cognitive development in children aged 1 to 3. Parents should oversee and regulate their children's smartphone usage to prevent negative consequences.
Aplikasi Desktop Manajemen Data Buku untuk Solusi Praktis untuk Pengelolaan Digital Agriby Chaniago; Annastasya Nabila Elsa Wulandari; Tri Stiyo Famuji
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 2 No. 1 (2025): Jurnal Kolaborasi Riset Sarjana Volume 2 Nomor 1 Januari 2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

In the digital era, book data management is an important challenge for libraries, bookstores, and private collections. This article discusses a Java-based book data management application designed with an Object-Oriented Programming (OOP) approach for modularity, efficiency, and flexibility. Key features include CRUD operations, data retrieval, recording of borrowing and book return transactions, and fine calculation, with MySQL integration for accurate, stable, and structured relational data storage. Security is strengthened through SHA-256 encryption on the login feature, ensuring limited access to authenticated users only. Testing showed stable performance, with improvements to the interface design and database connections to improve the user experience. This application not only supports efficient data management, but also offers flexibility in adjusting user needs. The development plan includes data export, statistical reports, mobile device compatibility, and interface improvements to provide comprehensive, responsive, and adaptive solutions to meet the needs of future book data management
Perancangan dan Implementasi Sistem Informasi Manajemen Laundry Berbasis Desktop dengan Penggunaan Java Swing Rachman Hidayat; Annastasya Nabila Elsa Wulandari; Purwono Purwono
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 2 No. 1 (2025): Jurnal Kolaborasi Riset Sarjana Volume 2 Nomor 1 Januari 2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

Perkembangan teknologi informasi telah membawa perubahan signifikan di berbagai sektor, termasuk industri laundry. Banyak pengusaha laundry menghadapi kesulitan dalam mengelola operasional secara efisien, terutama dalam hal pencatatan pesanan, pemantauan status pencucian, dan pengelolaan laporan. Penelitian ini bertujuan untuk merancang dan membangun Sistem Informasi Manajemen Laundry berbasis Desktop menggunakan Java Swing dan Maven. Sistem ini dirancang untuk menyederhanakan pengelolaan operasional mulai dari pencatatan pesanan hingga pemantauan status pencucian secara real-time. Java Swing dipilih karena kemampuannya dalam menyediakan antarmuka pengguna yang sederhana namun fungsional, sedangkan Maven digunakan untuk manajemen dependensi dan sistem build yang lebih terstruktur. Sistem ini juga menggunakan MySQL sebagai database untuk menyimpan data pelanggan, transaksi, dan data lainnya. Hasil pengembangan sistem menunjukkan bahwa aplikasi ini dapat meningkatkan efisiensi operasional dengan mengurangi penggunaan metode manual dan mempermudah pemantauan status pencucian. Sistem ini juga menyediakan fitur untuk pengelolaan transaksi dan laporan, yang mendukung pengelola dalam membuat keputusan yang lebih cepat dan tepat. Diharapkan, sistem ini dapat menjadi solusi praktis bagi usaha laundry dalam mengelola operasional mereka secara lebih terorganisir dan efisien.
Revolusi Kesehatan Digital: Peran AI dan Pembelajaran Mesin dalam Diagnosa Perawatan Oktavia Putri Handayani
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 1 No. 2 (2024): Jurnal Kolaborasi Riset Sarjana Volume 1 Nomor 2 Juli 2024
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

Pemanfaatan Kecerdasan Buatan (Artificial Intelligence/AI) dan Pembelajaran Mesin (Machine Learning/ML) semakin berkembang dalam sistem kesehatan modern, khususnya dalam meningkatkan akurasi diagnosis, perencanaan perawatan, dan pengelolaan data medis. Kajian tinjauan naratif ini bertujuan untuk merangkum bukti ilmiah terkini mengenai penerapan AI dan ML dalam diagnosis medis dan layanan perawatan. Pencarian literatur dilakukan melalui database ScienceDirect, IEEE Xplore, dan SpringerLink, dengan fokus pada studi yang membahas diagnostik berbasis AI, pemodelan prediktif, serta sistem pendukung keputusan klinis. Sebanyak 15 artikel relevan yang terbit pada rentang tahun 2015 hingga 2024 disertakan berdasarkan kesesuaian topik dan kualitas metodologis. Hasil kajian menunjukkan bahwa AI dan ML memberikan manfaat besar dalam diagnosis berbasis citra, interpretasi data genomik, manajemen penyakit kronis, serta prediksi risiko klinis. Beberapa studi bahkan melaporkan tingkat akurasi diagnosis yang menyamai atau melampaui tenaga medis manusia. Namun, tantangan tetap muncul, termasuk bias algoritma, isu privasi data, serta keterbatasan infrastruktur kesehatan terutama di negara berkembang. Kajian ini menyimpulkan bahwa integrasi AI dalam layanan kesehatan membutuhkan kolaborasi erat antara tenaga medis dan pengembang teknologi, disertai pengawasan etis dan regulasi yang kuat. Dengan implementasi yang bertanggung jawab, AI dan ML berpotensi besar mendorong peningkatan presisi diagnosis, optimalisasi jalur perawatan, serta penguatan ekosistem kesehatan digital di masa depan.
Penerapan Algoritma Propagasi Balik Jaringan Saraf Tiruan untuk Prediksi Produksi Sumur Gas di Sumatera Bagian Selatan Rofingi Aji; Yanuar Arief; Sinka Wilyanti; Rosyid Al-Hakim; Muhammad Yusro; Rian Ardianto
KORISA: Jurnal Kolaborasi Riset Sarjana Vol. 2 No. 2 (2025): Jurnal Kolaborasi Riset Sarjana Volume 2 Nomor 2 Mei 2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat (LP2M) Universitas Harapan Bangsa

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Abstract

Gas production forecasting plays a crucial role in supporting planning and management within a country's or region's oil and gas (O&G) sector. Artificial Neural Networks (ANN) are among the most effective methods for forecasting; however, the main challenge lies in determining the optimal number of neurons and hidden layers to achieve high prediction accuracy. This study aims to design an ANN architecture using the backpropagation algorithm to predict gas well production. The research stages include gas production data collection, data pre-processing, prediction processing, accuracy and error testing, and implementation. The dataset consists of daily natural gas well production records from January to December 2022, used for both training and testing the model. The results indicate that the ANN architecture 16-4-1 with a sigmoid activation function achieved the highest accuracy of 99.978% and the lowest MAPE of 2.192%. These findings demonstrate that the developed model can accurately represent the complexity of historical daily production data, making it a valuable tool for O&G field managers to plan production, optimize operations, and support strategic decision-making in the energy sector.

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