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International Journal of Integrative Sciences
Published by PT FORMOSA CENDEKIA GLOBAL
ISSN : -     EISSN : 29859050     DOI : https://doi.org/10.55927/ijis.v2i2
Core Subject : Science, Social, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering Social Sciences
International Journal of Integrative Sciences (IJIS) is an international peer-review, and double-blind review journal published by Formosa Publisher. The IJIS is aimed to provide a forum for review, reflection, and discussion informed by the results of recent and ongoing research from a multidisciplinary perspective. IJIS encourages new ideas and works in all fields and it publishes high-quality original papers, theory-based empirical papers, review papers, case reports, conference reports/papers, technology reports, book reviews, commentaries, events, and news. We welcome papers from both academicians and practitioners on theories, business models, conceptual paradigms, academic research, and consultancy projects. The Journal invites original papers, review articles, technical reports, and short communications that are not published or are not being considered for publication.
Arjuna Subject : Umum - Umum
Articles 297 Documents
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Classification of Plant Leaf Diseases Using Convolutional Neural Networks Teti Desyani; Mahromi, Muhammad; Ramadhan, Fazzil Alfis; Alfiansyah, Muhammad; Maulana, Muhammad Iqbal; Rosyani, Perani
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13478

Abstract

Leaf diseases significantly impact agricultural productivity and economic stability. This study explores the use of Convolutional Neural Networks (CNN) for classifying plant leaf diseases, addressing limitations of traditional visual inspection methods. Utilizing a Kaggle dataset with three classes (Healthy, Powdery, Rust), data preprocessing techniques such as resizing, augmentation, and normalization enhanced model performance. The CNN model achieved 95% accuracy in classification, demonstrating its capability to detect intricate patterns on leaf surfaces. Despite challenges like dataset imbalance and limited disease categories, the research highlights the potential of integrating CNN with web or mobile platforms to aid farmers in disease identification. These findings align with previous studies and underscore the importance of deep learning in agricultural innovation. Future research should focus on expanding datasets, exploring advanced architectures, and validating models under real-world conditions to maximize utility and accuracy in diverse environments
Efforts to Improve Students' Cognitive Learning Outcomes by Using Demonstration Methods in Fiqh Subjects on Hajj Subjects (Classroom Action Research on Class V Students of MI Al Istiqomah Katapang Bandung District) Faturahman, Rizqi; Hadi, Muhammad Sofian; Surizkika, Aldi
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13480

Abstract

This study seeks to enhance students' cognitive learning outcomes in Fiqh subjects focused on Hajj through the implementation of the demonstration method. In Indonesia, the education system continues to grapple with challenges, particularly regarding teaching methods that often lack variety. This research emphasizes the effectiveness of the demonstration method in Fiqh education, especially in relation to Hajj, with the goal of fostering a deeper understanding among students. The findings indicate that this method not only boosts student engagement but also reinforces conceptual comprehension and improves overall learning outcomes. Adopting a holistic approach, the study aims to cultivate insightful, empathetic, and socially responsible individuals capable of making meaningful contributions to society. Results indicate a progressive increase in student understanding of Hajj Fiqh throughout the cycles of learning facilitated by the demonstration method
Development of an Expert System for Diagnosing Respiratory Diseases in Animals Using the Bayesian Network and Rule-Based System Methods Farhan Stiady Syah; Rosyani, Perani; Suryaningrat; Putri, Firda Salsabila; Ashari, Idpan; Sofian, Kurnain
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13481

Abstract

Respiratory diseases in animals are a common health issue affecting both livestock and pets. These conditions can lead to significant economic losses in the livestock sector and reduce the quality of life for pets if left untreated. Early and accurate diagnosis is crucial to identify diseases promptly, prevent further spread, and minimize negative impacts on animals and their owners. Therefore, a system capable of providing fast, accurate, and data-driven diagnoses is essential. This study aims to develop an expert system specifically designed to diagnose respiratory diseases in animals using two main approaches: Bayesian Network and Rule-Based System. The Bayesian Network models uncertainties by analyzing probabilistic relationships between observed symptoms and potential diseases, while the Rule-Based System supports decision-making based on predefined rules. The combination of these methods is expected to yield more accurate and informative diagnostic results. Symptom data for this study were obtained from various sources, including relevant medical literature and animal health databases. The system was developed using Python programming language, leveraging libraries such as pgmpy for constructing Bayesian Network models and experta for implementing the Rule-Based System. The development and testing processes were conducted on the Google Colab platform, enabling efficient data processing, simulation, and visualization. The expert system was evaluated using simulated symptom data, with performance parameters including diagnosis probability and overall accuracy. The results indicate that the expert system effectively provides diagnoses based on user-input symptoms. The probability information included in the diagnostic results aids veterinarians and livestock owners in making more precise, data-driven medical decisions
The Role of the Fisheries Subsector in the Regional Economy of Tolitoli Regency Fitri S. Kasim; Fatimah; Rifay, Riski Thamrin G.; Syafitri, Euis
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13482

Abstract

The purpose of this study was to determine the role of the fisheries subsector in the regional economy of Tolitoli Regency in 2018-2022. The type of research used is quantitative research with technical analysis of Location Quotient (LQ) analysis data with secondary data obtained from the Tolitoli Regency Central Statistics Agency (BPS). The results of this study indicate that the production of the Tolitoli Regency fisheries subsector according to the calculation of Location Quotient (LQ) analysis shows an average value for 2018-2022 of 0.69 which means less than 1 (LQ <1) and is included in the criteria for non-base or non-leading sectors, it can be said that the fisheries subsector has a role as a local economic sector in the regional economy of Tolitoli Regency in 2018-2022
Review of Company Compliance with Occupational Safety and Health Standards Utomo, Bekti
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13483

Abstract

This study used the field inspection method, which involves a direct visit to a work site to observe and evaluate the implementation of occupational safety (OSH) standards. Data were collected through direct observation, interviews with relevant personnel, and examination of OHS-related documents. A sample of companies was randomly selected from various industrial sectors to represent a wider range of people.The objectives of this study are many-fold. As a first step, the study aimed to evaluate the company's utomo of compliance with applicable OHS standards. It is important to know the general level of compliance in the workplace. In addition, the purpose of the study was to find places where compliance may not be fully met. This identification can form the basis for improvement initiatives.Research Background The importance of occupational safety and health (OHS) standards to safeguard employee welfare and company performance, research on the review of companies' compliance with OHS through a field inspection approach is highly relevant. This background is due to the fact that OHS standards have been established and regulated, but companies' compliance with these standards is often inconsistent.According to the study, there are differences in the level of companies' compliance with OHS standards. While some companies have low levels of compliance, others still have low levels of compliance. Compliance is often breached in areas such as the use of personal protective equipment, emergency evacuation procedures, andhandling of hazardous chemicals. Lack of OHS training, lack ofmanagement oversight, and high production priorities are some of the factors affecting compliance.In conclusion, this study emphasizes how important it is to improve OHS standards in companies to make the working environment safer and healthier. Suggested improvements include more OHS training, more management supervision, and more sanctions for OHS violations
Energy Transformation of the EU Defense Industry : A Study of France Hafda Prima Agung; Nugrahani, Henny Saptatia Drajati
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13508

Abstract

This study aims to determine the challenges of energy transformation in the EU Defense Industry, particularly those carried out by French. The French defense industry is adapting its operation to the EU’s new energy policy, which include investment in green technologies, sustainable supply chain management, and adaptation to increasingly stringent environmental regulations. The energy transformation strategy in the French defense industry is important to explore because France is one of the major players in the global defense industry. The research method used is qualitative method with data is obtained through in-depth interviews, policy analysis, and case studies to understand the context, perceptions, and experiences of key actors related to policy implementation. This research uses Daniel Yergin’s energy security theory to analyze the relationship between energy and security and the challenges faced in global energy transformation. In addition, this study uses the energy policy theory of Amory B. Lovins, to analyze, evaluate and implement energy transformation policies. Lovins, to analyze, evaluate and provide recommendations regarding energy transformation strategies in the context of the French defense industry. The study’s findings is that the European Union has established an environmentally friendly strategi yon defense industry and France as one of the member states has implemented the practice in its national security defense operations. The conclusion the study is that EU energy policy has encouraged energy transformation in the French defense industry without undermining France’s national defense progress
Liver Disease Classification Using Decision Tree and Random Forest Algorithms Cahyono, Yoyo; Rosyani, Perani; Syah, Farhan Stiady; Putri, Firda Salsabila; Ashari, Idpan; Sofian, Kurnain
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13509

Abstract

Diagnosing diseases using technology is no longer uncommon. With advancements in healthcare technology, decision-making, particularly in detecting liver diseases, has become more efficient. Liver, an essential human organ, sees its functionality decline in patients with liver diseases. According to WHO data (2013), 28 million individuals in Indonesia suffer from liver diseases, marking it as one of the ten deadliest diseases. Early detection is crucial for effective treatment. This study aims to predict liver diseases using the Random Forest algorithm. Feature selection and classifier choice are pivotal for improving accuracy and computational efficiency. Using the Liver Disease Patient Dataset, the study involved data analysis, preprocessing, algorithm modeling, and visualization. Results show the Random Forest algorithm achieved an accuracy of 0.713326 with an F1 score of 81%
An AfD Victory in Thuringia: A Deep Dive Into the 2024 state Election Hananto, Ridwan Sri; Nugrahani, Henny Saptatia Drajati
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13528

Abstract

In the 2024 state election in Thuringia it was hence another final warning for Germany, with the Alternative for Germany (AfD) as overall winner. This article dives into the many contours of AfD's rise, including populism; anti-immigrant sentiment and larger societal disaffection. The AfD's rise, together with its accompanying challenges and opportunities for Thuringia if party divisions persist, these consider will have implications beyond the region for wider European politics are analyzed using a mixed-methods approach combining quantitative data analysis and qualitative insights from interviews and survey data on voter behavior and party dynamics. The results speak volumes of the nuances between today's electoral quagmire and the challenges posed by populist movements. Here, will be analysed how the AfD managed to win so many votes and offers a few suggestions on how we can tackle this rise of populism in Europe
Human Resource Management to Improve Organizational Commitment and Performance Rukmana, Dany; Nanda, Nur Alfiah; Nurjanah, Esa; Amelia, Tiara; Faiz , Hilmi Achmad; Husein; Sekarini, Ratih Ayu
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13554

Abstract

This study aims to test and analyse the influence of human resource management variables, and commitment to organisational performance. This research is a quantitative study to test the research hypothesis. The study took SMK Muhammadiyah 6 Jakarta teachers as the research site, with the determination of the sample using saturated sampling technique so that 50 respondents were used. Data were collected through distributing questionnaires and data were analysed using multiple linear regression. The results of the analysis found that: 1) there is a positive and significant influence between human resource management variables on organisational performance, with the amount of influence 52.4%, 2) there is a positive and significant influence between commitment variables on organisational performance, with the amount of influence 57.1%, 3) there is a positive and significant influence between human resource management variables, commitment, and organisational performance, with the amount of influence 63.9%
Human Resource Management Strategy to Improve Sustainable Company per Formance In Industry 4.0 at the Organization of PT. KAI Daop 2 Bandung Sakti, Hudan Malik Bhuanan; Kanji, Muhammad Syahrul; Suprapto, Ryan Puspo; Wijaya, Aprilia Lintang; Danistyarini, Pundy; Sekarini, Ratih Ayu
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13555

Abstract

Human resources are an important factor in improving company performance. Competing in the world of work Companies must be able to implement a Human Resource Management Strategy about Industry 4.0 in the Company Organization. The purpose of this study was to determine whether Motivation (X1) and Training (x2) have a significant effect on Company Performance (Y) at PT. Kai Daop 2 Bandung. Thenformulate the right Human Resources Management Strategy to improve sustainable Company Performance in Industry 4.0. The population in this study were all employees at Daop 2 Bandung station. The sample used in this study was 55 employees as respondents. The method in this study uses a Quantitative method with a Correlational approach. The results of the research and hypothesis show that Motivation (X1) and Training (X2) have a positive and significant effect on Company Performance (Y) at PT Kai Daop 2 Bandung.

Page 29 of 30 | Total Record : 297

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