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Academia Open
Published by Universitas Muhammadiyah Sidoarjo
ISSN : -     EISSN : 27147444     DOI : 10.21070/acopen.11.2026.12985
Core Subject : Health,
Medicine & Pharmacology Public Health
Academia Open is published by Universitas Muhammadiyah Sidoarjo published 2 (two) issues per year (June and December). This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge. This journal aims is to provide a place for academics and practitioners to publish original research and review articles. The articles basically contains any topics research or review. Academia Open is available in online version. Language used in this journal is Indonesia or English.
Arjuna Subject : Profesi Kesehatan - Profesi Kesehatan (Lain-Lain)
Articles 2,389 Documents
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Six Sigma FMEA Roadmap for Beach Chair Defect Reduction: Roadmap Six Sigma FMEA untuk Pengurangan Cacat Kursi Pantai M. Frizky Feri Setiawan; Enny Aryanny
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13445

Abstract

General Background: Product quality control is a critical factor in export-oriented furniture manufacturing, where defect reduction and process capability are central to sustaining competitiveness. Specific Background: PT XYZ, a wood furniture manufacturer producing beach chair model X for export, recorded an average defect rate of 8.65% during January–December 2025, with five Critical to Quality (CTQ) categories: cracked wood, uneven paint, loose weaving, loose fabric, and unattached nuts. Knowledge Gap: Although Six Sigma and Failure Mode and Effects Analysis (FMEA) are widely applied in manufacturing, their integrated application for systematic defect mapping and risk prioritization in beach chair production at PT XYZ had not been formally analyzed. Aims: This study aims to measure process capability, identify root causes of defects, and formulate prioritized improvement proposals using the DMAIC framework and FMEA. Results: From 3,007 units produced, 171 defective units were identified, yielding an average DPMO of 17,291 and a sigma level of 3.66. P-chart analysis revealed several out-of-control points, indicating special cause variation. FMEA evaluation showed the highest Risk Priority Number (RPN) of 343 for the failure mode “product proceeds without nut verification,” followed by undetected initial wood cracks (RPN 336) and uneven paint layers (RPN 252). Novelty: This study presents an integrated Six Sigma–FMEA roadmap that links statistical process control, root cause analysis, and structured risk prioritization in beach chair manufacturing. Implications: The proposed recommendations provide a data-driven reference for systematic quality control and support the company’s zero defect target in export furniture production. Highlights: Process capability averaged 3.66 sigma with 17,291 DPMO across 3,007 units. The most critical failure mode reached an RPN value of 343 in assembly operations. Statistical control charts identified multiple special-cause variations requiring corrective action. Keywords:Six Sigma, FMEA, DMAIC, Defect Reduction, Risk Priority Number
Internship Experience and Grit Shape Gen Z Work Readiness: Pengalaman Magang dan Ketekunan Membentuk Kesiapan Kerja Generasi Z Intan Safitri; Luluk Fadliyanti; Nadia Nuril Ferdaus
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13446

Abstract

General Background: Work readiness is a central issue in human capital development, particularly in the context of Sustainable Development Goals and youth employment in emerging regions. Specific Background: In West Nusa Tenggara Province, open unemployment remains dominated by tertiary-educated graduates, indicating a mismatch between higher education outcomes and labor market demands among Generation Z fresh graduates. Knowledge Gap: Although prior studies have examined internship experience, work motivation, and grit separately, limited research has integrated these variables within a comprehensive model of work readiness grounded in Human Capital and Employability Capital theories. Aims: This study analyzes the relationships between internship experience, work motivation, and grit and their contribution to work readiness among 101 Gen Z fresh graduates using a quantitative survey and multiple linear regression. Results: The findings demonstrate that internship experience and grit have positive and statistically significant associations with work readiness, whereas work motivation does not show a significant partial relationship; collectively, the three variables significantly explain 53.3% of the variance in work readiness (R² = 0.533). Novelty: This study positions grit as the most dominant predictor within an integrated human capital framework combining experiential and psychological dimensions. Implications: The results underscore the importance of structured industry-relevant internship programs and the integration of grit-based character development in higher education curricula to strengthen graduate competitiveness in regional labor markets. Highlights: Practical workplace exposure shows a statistically significant positive association with graduate preparedness for employment. Psychological perseverance emerges as the strongest predictor within the regression model. The combined model accounts for 53.3% of variance in employment preparedness among respondents. Keywords: Gen Z, Grit, Work Readiness, Internship Experience, Work Motivation
Location Based Disaster Response Prioritization Using AHP and GIS: Prioritas Respon Bencana Berbasis Lokasi Menggunakan AHP dan GIS Audy A. Kenap; Abigail A. Raranta; Glenn D. P. Maramis
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13447

Abstract

This study addresses structured decision-making in regional disaster management. General Background: Effective disaster management requires rapid and systematic prioritization to allocate limited emergency resources appropriately. Specific Background: In Minahasa Regency, disaster response prioritization at the Regional Disaster Management Agency (BPBD) has largely relied on rapid assessment and personal judgment, without systematic integration of spatial factors such as accessibility, affected population distribution, and proximity to public facilities. Knowledge Gap: Previous approaches commonly applied Analytic Hierarchy Process (AHP) or Geographic Information Systems (GIS) separately, limiting operational integration between multicriteria decision analysis and spatial information. Aims: This study aims to design and implement a web-based decision support system that determines location-based disaster response priority levels using integrated AHP and GIS. Results: The system applies hierarchical modeling, pairwise comparison, and consistency testing to generate weighted priorities based on disaster severity, affected population, impacted area, accessibility, and escalation potential. Interactive mapping enables spatial visualization of incidents and produces systematic, measurable priority classification compared to subjective assessment. Novelty: This research integrates AHP weighting and spatial analysis within an operational web platform applicable to BPBD Minahasa Regency. Implications: The system offers a quantitative and transparent foundation for data-driven disaster response prioritization at regional and broader administrative levels. Highlights Web-based platform integrates multicriteria weighting with spatial mapping for emergency handling.• Hierarchical modeling generates measurable urgency classification from structured criteria.• Interactive geographic visualization supports transparent allocation of limited resources. Keywords:Analytic Hierarchy Process; Geographic Information Systems; Disaster Response Prioritization; Decision Support System; Location Based System
Tourist Attractions Halal Facilities and Satisfaction Drive Revisit Intention: Daya Tarik Wisata Fasilitas Halal dan Kepuasan Mendorong Minat Kunjungan Ulang Mahdinatul Fitri Zahroh; Wahibur Rohman
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13452

Abstract

This study examines revisit intention in a local tourism destination through key experiential and service-related factors. General Background: Tourism development increasingly emphasizes visitor experience and service quality to sustain destination competitiveness. Specific Background: Pijar Park Kudus, as a semi-artificial nature-based tourist destination, integrates tourist attractions, halal facilities, and visitor satisfaction to attract Muslim tourists. Knowledge Gap: Previous studies have rarely investigated the integration of tourist attractions, halal facilities, and visitor satisfaction within a single analytical model in local tourism contexts. Aims: This study aims to analyze the role of tourist attractions, halal facilities, and visitor satisfaction in shaping revisit intention. Results: Using a quantitative survey of 113 respondents, the findings reveal that tourist attractions, halal facilities, and visitor satisfaction each have positive and significant relationships with revisit intention, both partially and simultaneously, with a contribution of 77.3% to its variance. Novelty: This study highlights halal facilities as a key determinant within local tourism settings and integrates multiple variables in a unified model applied to a semi-artificial nature destination. Implications: The findings provide practical guidance for destination managers to develop integrated tourism strategies focused on improving attractions, halal facilities, and visitor satisfaction to strengthen visitor loyalty and support sustainable tourism development. HIGHLIGHTS • Tourist attractions contribute significantly to repeat visitation behavior• Halal-oriented services become a key determinant in local tourism context• Visitor satisfaction strengthens loyalty formation among young travelers KEYWORDS Tourist Attractions; Halal Facilities; Visitor Satisfaction; Revisit Intention; Halal Tourism
Integrated SQC and FMEA Framework for Woven Bag Defect Reduction In Manufacturing Industry: Kerangka Terpadu SQC dan FMEA untuk Pengurangan Cacat Woven Bag Di Industri Manufaktur Asmaul Husna; Enny Aryanny
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13453

Abstract

General Background: In highly competitive manufacturing industries, systematic quality control is required to maintain product conformity and reduce defect rates. Specific Background: PT XYZ, a plastic packaging manufacturer, recorded woven bag production of 41,749,730 sheets in 2025 with a defect rate of 3.14%, exceeding the company target of below 2%, resulting in rework and recycled products. Knowledge Gap: Previous studies combining Statistical Quality Control (SQC) and Failure Mode and Effect Analysis (FMEA) applied SQC tools to aggregated defect data without differentiating defect types, limiting analytical precision. Aims: This study aims to analyze woven bag quality using an integrated SQC and FMEA framework and to determine prioritized corrective actions based on Risk Priority Number (RPN). Results: Four dominant defects were identified: knit-through (354,623 sheets; 27.1%), improper stitching (25.6%), uneven cutting (24.3%), and printing mismatch (23%). Scatter diagrams indicated a positive relationship between production volume and defect quantity, while p control charts revealed multiple points outside control limits. FMEA results showed the highest RPN (336) for knit-through caused by suboptimal yarn tension on the circular loom machine. Novelty: This research applies SQC tools separately to each defect category, generating more detailed diagnostic insights prior to FMEA prioritization. Implications: The findings provide data-driven recommendations, including sensor upgrades on circular loom machines, routine cleaning of cutting tools, scheduled cliché replacement, and standardized machine settings to reduce woven bag defects and strengthen manufacturing quality control. Highlights: Knit-through recorded the largest proportion of nonconformities at 27.1% of total rejected output. Control chart evaluation showed several monthly proportions exceeding statistical limits. The highest priority corrective action targeted yarn tension deviation on the circular loom with an RPN of 336. Keywords: Statistical Quality Control, Failure Mode and Effect Analysis, Risk Priority Number, Woven Bag Defects, Manufacturing Quality Control
Gender Justice Dissemination via Afkaruna Official Instagram: Diseminasi Keadilan Gender melalui Instagram Afkaruna Official Lili Cahyati; ST. Aisyah BM; Arham Selo; Ramsiah Tasruddin; Haidir Fitra Siagian
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13463

Abstract

General Background: Social media has become a strategic medium for mass communication in disseminating gender justice issues. Specific Background: Instagram is utilized by Afkaruna Official to communicate gender justice based on Islamic feminist perspectives to diverse audiences. Knowledge Gap: Existing studies rarely analyze communication strategies, message representation, and audience reception within Islamic feminist digital activism. Aims: This study examines the urgency of dissemination, communication strategies, and audience responses. Results: Instagram serves as a strategic space shaped by persistent gender bias and low literacy. Strategies include optimized content distribution, persuasive education, visual storytelling, and inclusive Islamic framing. Audience responses are generally positive through likes, comments, and shares, although active dialogue remains limited. Novelty: The study integrates digital communication strategies with Islamic feminist perspectives in social media activism. Implications: The findings indicate that social media contributes to gender justice literacy and public awareness while requiring more participatory communication approaches. Highlights• Instagram operates as a discourse space connecting religious values with equality narratives• Content strategies rely on narrative depth, visual formats, and inclusive language• Audience engagement shows acceptance through symbolic interaction rather than discussion KeywordsGender Justice; Information Dissemination; Mass Communication; Social Media; Islamic Feminism
Socio-Political Conflict Dynamics After the 2024 Polewali Mandar Election: Dinamika Konflik Sosial-Politik Pasca Pemilihan Umum Polewali Mandar 2024 Ahmad Ilham; Jumadi Jumadi; Hasruddin Nur
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13465

Abstract

General Background Regional head elections represent a core mechanism of local democracy in Indonesia, intended to facilitate political participation and power circulation at the subnational level. Specific Background In practice, post-election phases frequently generate socio-political tensions, particularly in communities with strong kinship structures and identity-based affiliations, as observed in Polewali Mandar following the 2024 regent election. Knowledge Gap Existing studies often approach post-election conflict through legalistic or security-centered perspectives, leaving limited understanding of conflict as a prolonged social process embedded in everyday relations and digital interactions. Aims This study aims to analyze the dynamics of post-election socio-political conflict in Polewali Mandar, identify structural, cultural, and communicative factors driving the conflict, and examine its social consequences. Results Using a qualitative descriptive approach through interviews, observation, and documentation, the findings reveal polarized supporter groups, non-physical and symbolic conflicts, the circulation of hoaxes and hate speech in digital spaces, weakened family and community interactions, and declining trust in democratic institutions. Contributing factors include identity politicization, money politics, questioned neutrality of village officials and civil servants, elite rivalries, and low political literacy. Novelty This study conceptualizes post-Pilkada conflict not merely as an electoral event but as a socially embedded process shaped by kinship, local identity, patronage networks, and digital communication. Implications The findings underscore the need for participatory and local-wisdom-based conflict resolution strategies to support democratic consolidation and restore social cohesion at the local level. Highlights: Post-election tensions manifested predominantly through symbolic, non-violent, and latent social frictions. Identity-based alignments and elite rivalries intensified polarization within families and local communities. Digital communication spaces played a central role in sustaining distrust and prolonged social tension. Keywords: Socio-Political Conflict, Pilkada, Local Democracy, Polewali Mandar, Conflict Resolution.
Learning Environment Design and Social Emotional Development in Early Childhood: Desain Lingkungan Belajar dan Perkembangan Sosial Emosional pada Masa Kanak-kanak Lili Rismalah Defi; Choirun Nisak Aulina
Academia Open Vol. 10 No. 1 (2025): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.13472

Abstract

General Background Early childhood education emphasizes social emotional development as a foundation for children’s adaptation, relationships, and self-regulation. Specific Background The learning environment, including physical settings, social interactions, and psychological climate, is considered a central context shaping daily experiences in kindergarten classrooms. Knowledge Gap However, detailed descriptions of how these environmental components function collectively to support social emotional growth in specific early childhood institutions remain limited. Aims This study aimed to describe the role of the learning environment and to identify supporting and inhibiting factors related to social emotional development among children aged 4–5 years at TK Islam Al Wafa. Results Using a descriptive qualitative approach through observation, interviews, and documentation, the findings show that organized classrooms, play corners, consistent routines, teacher guidance, and peer interaction facilitate empathy, cooperation, discipline, and emotional expression, while family constraints and limited responsiveness hinder progress. Novelty The study provides an integrated description of physical, social, and emotional elements within one institutional case. Implications These results offer practical guidance for teachers and early childhood managers in structuring supportive learning environments to foster balanced social emotional competencies. Keywords: Learning Environment, Social Emotional Development, Early Childhood Education, Classroom Climate, Qualitative Study Key Findings Highlights: Structured spaces encourage cooperation and sharing behaviors Daily routines cultivate self-regulation and discipline Teacher guidance and peer play build empathy and communication
Convolutional Neural Network Achieves 97.67 Percent Accuracy for Alzheimer MRI Classification: Convolutional Neural Network Mencapai Akurasi 97,67 Persen untuk Klasifikasi MRI Alzheimer Ichwan Puja Pangestu; Vitri Tundjungsari
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13477

Abstract

AbstractGeneral Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder requiring accurate and accessible diagnostic support. Specific Background: Magnetic Resonance Imaging (MRI) is widely used for structural brain assessment, and Convolutional Neural Networks (CNN) enable automated feature extraction from medical images. Knowledge Gap: Prior studies report high classification performance but rarely integrate comprehensive evaluation with real-time deployment for decision support. Aims: This study develops and evaluates a CNN-based model for classifying 2D axial MRI images into Alzheimer’s Disease (AD), Mild Cognitive Impairment (MCI), and Common Normal (CN), alongside web-based implementation. Results: Using approximately 5,000 ADNI MRI images, the model achieved 97.67% accuracy, 97.73% precision, 97.67% recall, and 97.65% F1-score, with AUC values near 1.00. Learning curves indicated stable convergence without overfitting or underfitting, and confusion matrix analysis confirmed consistent multi-class discrimination. The deployed Hugging Face–Gradio application generated predictions in under five seconds per scan without performance degradation. Novelty: This research combines rigorous multi-metric validation with interactive web deployment as an artificial intelligence decision support system for early AD screening. Implications: The findings demonstrate the technical feasibility of CNN-based MRI classification for preliminary cognitive disorder screening, while emphasizing the need for multimodal integration and prospective clinical validation. Highlights• Achieved robust multi-class discrimination among AD, MCI, and CN categories using axial brain scans.• Demonstrated stable training dynamics validated through loss convergence and receiver operating characteristics.• Implemented an interactive artificial intelligence platform with sub-five-second prediction time. KeywordsAlzheimers Disease; Convolutional Neural Networks; MRI Classification; Deep Learning; Clinical Decision Support System
VSM Reduces Lead Time in Fabrication Material Warehouse Operations: VSM Mengurangi Waktu Tunggu dalam Operasi Gudang Bahan Baku Manufaktur Regan Fitra Ramadhan; Dira Ernawati; Isna Nugraha
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13491

Abstract

General Background Global competition has increased the strategic role of warehousing within supply chain management, particularly in supporting production reliability and logistics performance. Specific Background Fabrication material warehouses in engineering and construction companies often experience inefficiencies caused by non-value-added activities, excessive inventory, transportation constraints, and waiting time. Knowledge Gap Empirical studies that systematically integrate Value Stream Mapping, Process Activity Mapping, and the Waste Assessment Model to quantify and prioritize waste in fabrication material warehouses remain limited. Aims This study aims to identify dominant waste types and redesign warehouse activities using a lean warehousing approach at a fabrication material warehouse of PT XYZ. Results The current state analysis shows a total lead time of 891 minutes with 557 minutes of value-added time and 11 non-value-added activities. The future state Value Stream Mapping reduces lead time to 689 minutes, indicating a 23% improvement in warehouse activity performance through reduced delay and non-value-added processes. Novelty This study combines Value Stream Mapping, Process Activity Mapping, and the Waste Assessment Model to provide an integrated and structured waste identification framework for fabrication material warehousing. Implications The findings offer practical guidance for warehouse layout management, inventory control, and activity synchronization, supporting more efficient material flow and improved operational reliability in fabrication warehouse operations. Highlights: Non-value-added activities dominated delay and material handling processes within warehouse operations. Integrated mapping and waste analysis enabled measurable time reduction across storage and loading stages. Structured improvement recommendations supported better coordination of material flow and documentation processes. Keywords: Lean Warehousing, Process Activity Mapping, Waste Assessment Model, Fabrication

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