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INDONESIA
Indonesian Journal of Innovation Studies
Published by Universitas Muhammadiyah Sidoarjo
ISSN : -     EISSN : 25989936     DOI : https://doi.org/10.21070/ijins.v17i
Core Subject : Science, Education, Social, Engineering,
Computer Science & IT Education Engineering Law, Crime, Criminology & Criminal Justice
Indonesian Journal of Innovation Studies (IJINS) is a peer-reviewed journal published by Universitas Muhammadiyah Sidoarjo four times a year. 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 concerning new innovation on all aspects. IJINS is available in online version. Language used in this journal is Indonesia or English.
Arjuna Subject : Umum - Umum
Articles 923 Documents
 88   89   90   91   92 
Benson And Guided Imagery Combination In Gastritis Pain Reduction: Kombinasi Terapi Benson Dan Guided Imagery Pada Nyeri Gastritis Khasanah, Tia Meilana Uswatun; Sukarmin, Sukarmin; Siswanti, Heny
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1849

Abstract

General Background: Gastritis is a common gastrointestinal disorder frequently accompanied by epigastric pain that interferes with patient comfort and daily functioning. Specific Background: Non-pharmacological nursing interventions such as Benson relaxation therapy and guided imagery have been individually applied to manage pain in gastritis patients, particularly in primary healthcare settings. Knowledge Gap: However, empirical evidence examining the combined application of Benson therapy and guided imagery as a structured intervention in community health centers remains limited. Aims: This study aimed to examine the outcomes of a combined Benson therapy and guided imagery intervention on pain levels among gastritis patients at a primary healthcare center. Results: Using a quasi-experimental pretest–posttest control group design with 32 participants, the intervention group demonstrated a marked shift from moderate–severe pain to predominantly mild pain after the intervention, while the control group receiving pain management education showed a smaller reduction. Statistical analysis indicated significant pre–post differences within the intervention group and significant differences between groups after intervention. Novelty: The novelty of this study lies in the standardized combination of Benson relaxation and guided imagery implemented as a single nursing intervention package in a primary care context. Implications: These findings support the integration of combined Benson therapy and guided imagery into routine nursing care as a feasible, safe, and low-cost non-pharmacological approach for managing gastritis-related pain in primary healthcare services. Highlights • Demonstrated pain level shift toward mild categories following combined relaxation intervention• Showed significant differences between intervention and education-only groups• Supported structured non-pharmacological nursing care in primary health centers Keywords Benson Therapy; Guided Imagery; Gastritis Pain; Non Pharmacological Nursing; Primary Health Care
Risk Detection System for Children Putting Objects into Mouth Based on Computer Vision using YOLOv11n: Sistem Deteksi Risiko Anak Memasukkan Benda ke dalam Mulut Berbasis Computer Vision menggunakan YOLOv11n Ramadan, Nofri; Muhtadi, Muis; Rafi, Muhammad Zulfiqar; Waluyo, Rinakit Estu
Indonesian Journal of Innovation Studies Vol. 26 No. 4 (2025): October
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v26i4.1851

Abstract

Background: Young children commonly place objects near or into their mouths, creating safety concerns that require constant supervision. Specific Background: Advances in computer vision enable real-time recognition of hands, faces, and objects, allowing automated identification of behaviors that may lead to hazardous mouth-related interactions. Knowledge Gap: Few systems combine object detection and human pose estimation specifically to assess risks related to toddler hand–mouth–object interactions in real-time environments. Aims: This study develops a risk detection system using YOLOv11n to recognize hands, faces, and objects while classifying conditions into safe or risky based on Euclidean distance between hand and mouth keypoints. Results: The system produces 92% accuracy in scenarios without objects and 74% in scenarios with objects, demonstrating its capability to differentiate between safe and risky conditions. Novelty: This research introduces an integrated spatial analysis approach that evaluates real-time proximity among hands, mouth, and objects, rather than detecting these elements independently. Implication: The system provides practical potential for real-time child safety monitoring, offering earlier awareness of mouth-related object risks in various activity settings. Highlights • The system identifies hand–mouth proximity to classify safe and risky situations.• Integrated pose estimation and object detection enable spatial risk assessment in real time.• The model supports early awareness of mouth-related object risks during toddler activities. Keywords Object Detection, Pose Estimation, Computer Vision, YOLO, Child Safety Monitoring
Application of YOLOv8 in Computer Vision-Based Facial Expression Detection of Toddlers: Penerapan YOLOv8 dalam Deteksi Ekspresi Wajah Balita Berbasis Computer Vision Waluyo, Rinakit Estu; Muhtadi, Muis; Ramadan, Nofri; Rafi, Muhammad Zulfiqar
Indonesian Journal of Innovation Studies Vol. 26 No. 4 (2025): October
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v26i4.1853

Abstract

Background: Facial expressions are a primary form of nonverbal communication for toddlers whose verbal abilities are still developing. Specific background: Advances in computer vision and deep learning have enabled real-time facial expression detection; however, most existing systems are designed using adult facial datasets and pretrained models. Knowledge gap: Research focusing on toddler facial expression detection using models trained exclusively on toddler data without pretrained weights remains limited. Aims: This study applies YOLOv8 to detect happy, sad, and neutral facial expressions of toddlers in real time using a model trained from scratch. Results: The proposed system achieved an average detection accuracy of 86%, with precision of 0.944, recall of 0.933, and mean Average Precision at 0.5 of 0.966, demonstrating stable real-time performance under varying lighting conditions. Novelty: The study demonstrates that YOLOv8 can learn toddler-specific facial expression patterns without relying on pretrained weights derived from adult facial data. Implications: The findings indicate the feasibility of deploying real-time toddler facial expression detection systems to support emotional monitoring in childcare and early education environments. Highlights Real-time detection of toddler facial expressions using YOLOv8. Model training conducted entirely from scratch using toddler facial datasets. Consistent detection performance observed in natural and varied environments. Keywords Facial Expression Detection, Toddler, YOLOv8, Computer Vision, Real-Time System
Character Education Values in the Novel Sanggarguri for High School Literature Learning: Nilai Pendidikan Karakter dalam Novel Sanggarguri untuk Pembelajaran Sastra di SMA Fazlina, Sri Ayu; Saharudin; Aswandikari; Sirulhaq, Ahmad; Burhanudin; Mahyudi, Johan
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1854

Abstract

Background: Character education is a fundamental component of formal education, particularly in addressing moral and social challenges among students in contemporary society. Specific background: Literary texts grounded in local culture provide concrete representations of character values through narratives, traditions, and social interactions, as reflected in the novel Sanggarguri by Lalu Agus Fathurrahman. Knowledge gap: Previous studies on Sanggarguri have largely emphasized cultural and symbolic dimensions, while systematic analysis of character education values in relation to high school literature learning remains limited. Aims: This study aims to identify character education values embedded in the novel Sanggarguri and to describe their use within high school literature learning. Results: The analysis reveals five dominant values: respect, responsibility, tolerance, cooperation, and courage, manifested through characters’ attitudes, cultural rituals, and moral decision-making. Novelty: This study positions Sanggarguri as a local literary text that integrates Sasak cultural wisdom with character education values. Implications: The findings support the use of local novels as contextual teaching materials for high school literature learning, particularly in developing moral awareness, empathy, and cultural understanding in line with curriculum objectives. Highlights Identification of five core character education values in Sanggarguri. Representation of Sasak local wisdom through literary narratives and traditions. Suitability of the novel for high school literature learning contexts. Keywords Character Education, Novel Sanggarguri, Sasak Culture, High School Literature Learning, Local Wisdom
Evaluation of YOLOv8n, YOLOv10n, and YOLOv11n for Early Detection of Seizures in Infants: Evaluasi YOLOv8n, YOLOv10n, dan YOLOv11n untuk Deteksi Dini Kejang pada Bayi Rafi, Muhammad Zulfiqar; Muhtadi, Muis; Ramadan, Nofri; Waluyo, Rinakit Estu
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1855

Abstract

Background: Infant epilepsy is a serious neurological condition that is difficult to recognize visually because seizure manifestations often resemble normal infant reflexes. Specific background: Advances in computer vision and deep learning have enabled image-based seizure detection as a non-invasive approach for early identification in infants. Knowledge gap: Comparative evaluations of different YOLO model generations under identical experimental settings for infant seizure detection remain limited. Aims: This study evaluates and compares the performance of YOLOv8n, YOLOv10n, and YOLOv11n in detecting seizure activity from infant image data. Results: Using a dataset of 645 images across seizure and neutral classes, YOLOv11n achieved the highest precision, recall, and mean average precision at stricter localization thresholds, while YOLOv10n demonstrated the fastest inference time. Novelty: This study provides a systematic cross-generation evaluation of YOLO nano variants for infant seizure detection using uniform training parameters. Implications: The findings support informed selection of YOLO architectures for non-invasive, image-based early seizure detection systems in clinical and real-time monitoring contexts. Highlights • YOLOv11n shows the most stable detection performance for infant seizure images• YOLOv10n achieves the fastest inference time under identical training settings• Cross-version evaluation reveals clear trade-offs between detection stability and processing speed Keywords YOLO, Epilepsy, Computer Vision, Object Detection, Infant Seizure Detection
Genetic Algorithm Driven Route Innovation for Minimizing Gym Dumbbell Distribution Distance and Cost: Inovasi Rute Berbasis Algoritma Genetika untuk Meminimalkan Jarak dan Biaya Distribusi Alat Gym Dumbel Aryadinata, Rafi; Aryanny, Enny
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1856

Abstract

General Background: Efficient distribution planning is essential to ensure timely delivery with reasonable operational costs. Specific Background: PT. ABC distributes gym equipment, with dumbbells as a high-demand product, yet its current route planning is not optimal, leading to longer travel time and higher distribution costs using pick-up trucks. Knowledge Gap: Prior route optimization approaches in similar contexts often emphasize distance reduction without explicitly incorporating vehicle load capacity, reducing realism for heavy-goods delivery. Aims: This study aims to determine an optimal capacitated distribution route for gym dumbbell deliveries at PT. ABC using a Genetic Algorithm within a Capacitated Vehicle Routing Problem (CVRP) framework to minimize total travel distance and distribution cost. Results: The proposed Genetic Algorithm solution produced four delivery routes totaling 174 km compared with the company’s 253.3 km, reducing distance by 79.3 km (31.3%) and lowering total distribution cost from IDR 313,300 to IDR 234,000, a reduction of IDR 79,300 (25.3%). Novelty: Vehicle load capacity is treated as an additional decision variable, making the optimized routes more representative of actual dumbbell distribution conditions. Implications: The findings support managerial decision-making for route planning, operational cost control, and transport fleet productivity, and demonstrate the suitability of Genetic Algorithms for CVRP-based distribution route optimization with realistic capacity considerations. Highlights: Total travel distance decreased by 79.3 km with 31.3% savings versus the existing routing approach. Total delivery expenditure declined by IDR 79,300, equivalent to 25.3% cost savings. Capacity-constrained routing produced four feasible delivery routes aligned with pick-up load limits. Keywords: Genetic Algorithm, Distribution Costs, Capacitated Vehicle Routing Problem, Optimal Route
Cloud-Based Digital Invoice Automation Improves Accuracy and Efficiency for Small and Medium Enterprises: Otomatisasi Invoice Digital Berbasis Cloud Meningkatkan Akurasi dan Efisiensi Usaha Kecil dan Menengah Wicaksono, Ryan Dwi; Soraya, Dila Umnia
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1860

Abstract

Manual invoice management in SMEs often leads to delays, recording errors, and difficulty tracking documents. CV Mata Timur Nusantara still uses spreadsheets without a centralized system, making the administration process less efficient. This study developed a cloud-based digital invoice automation system to improve transaction accuracy and efficiency. The development method used the Waterfall model, including analysis, design, implementation, and testing. The system was designed using Laravel, React, and n8n workflow automation integration to automatically create and send PDF invoices through various communication channels. Test results showed that this solution was able to accelerate processes, reduce recording errors, and improve the consistency of document distribution. These findings prove that cloud-based automation is effective in SMEs to support faster and more accurate administration processes. Highlights• Accelerates invoice processing and distribution for SMEs• Reduces manual recording errors through automated workflow• Improves consistency and reliability of document delivery KeywordsDigital Inovice; Workflow Automation; Cloud Computing; Information System; Application Integration
Polynomial Regression Budget Prediction for Minahasa Fire Department: Prediksi Anggaran Dinas Pemadam Kebakaran Kabupaten Minahasa Sondakh, Inggried Rillya; Santa, Kristofel; Moningkey, Efraim Ronald Stefanus
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1861

Abstract

General Background: Public sector budget planning requires data-driven approaches to support service sustainability, particularly for emergency institutions such as regional fire departments. Specific Background: The Minahasa Regency Fire Department budget planning has relied on historical allocations that exhibit fluctuating and non-linear trends across expenditure categories. Knowledge Gap: Previous planning practices have not fully utilized non-linear statistical modeling to interpret historical budget dynamics and medium-term projections. Aims: This study aims to analyze historical budget trends and predict expenditure needs for the 2025–2027 period using a second-order polynomial regression model. Results: Using budget data from 2019–2024, the model successfully captured non-linear expenditure patterns, including a sharp increase in personnel and capital expenditures in 2024, with coefficients of determination of 0.448 for personnel expenditures and 0.409 for capital expenditures, while total projected expenditures approach IDR six billion by 2027. Novelty: This research integrates second-order polynomial regression with an interactive Streamlit-based application for visualizing and interpreting public sector budget projections. Implications: The findings provide an analytical basis for local governments to anticipate medium-term budget requirements, prioritize expenditures, and strengthen data-based financial planning for fire service operations. Highlights • Second-order polynomial modeling captures non-linear expenditure patterns across budget categories• Historical personnel expenditure spikes shape medium-term fiscal projections• Streamlit-based visualization supports data-driven public budget planning Keywords Polynomial Regression; Budget Prediction; Fire Department; Historical Data; Streamlit Application
Kabar Sunda Program Reduces Aggressive Behavior in Elementary Students: Program Kabar Sunda Menurunkan Perilaku Agresi Siswa Sekolah Dasar Nurrahmah, Rara; Pratiwi, Anggia Suci; Lestari, Asti Tri; Dewi, Rikha Surtika
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1862

Abstract

General Background: Aggressive behavior among elementary students disrupts learning activities and hinders social-emotional development in classroom environments. Specific Background: This condition was found in a third-grade student at SDN 1 Puspahiang, exhibiting physical, verbal, emotional, and hostile aggression, requiring contextual interventions aligned with Sundanese cultural values. Knowledge Gap: Although character education and cultural-based learning are theoretically recommended, practical implementation in schools remains limited, particularly programs integrating Kaulinan Barudak Sunda for behavioral regulation. Aims: This study aims to identify forms of aggression demonstrated by the student and to apply the Kabar Sunda (Kaulinan Barudak Sunda) Program as a strategy for reducing aggressive behavior. Results: A qualitative case study was conducted using participatory observation, in-depth interviews, and documentation over five traditional game sessions. Findings indicate aggressive behavior across dimensions conceptualized by Buss and Perry, triggered by internal emotional frustration and external disharmonious interactions, with aggression reduction reaching approximately 70–80% and improvement in rule compliance, participation, cooperation, and social interaction. Novelty: This research introduces a culturally grounded intervention through traditional Sundanese games as a contextual, engaging mechanism for behavioral regulation in early education settings. Implications: The outcomes offer a practical alternative for schools to employ local cultural assets as sustainable character-building strategies, reinforcing values of silih asih, silih asah, and silih asuh while fostering a conducive learning climate. Highlights Aggressive behavior decreased progressively across five sessions of traditional Sundanese games. Cultural values integration supported improvements in compliance, cooperation, and interaction. Localized educational programs created a meaningful alternative for character development. KeywordsAggressive Behavior; Elementary Students; Kabar Sunda Program; Traditional Games; Local Culture
Genetic Algorithm-Based Web Scheduler Enhances Fairness in Duty Allocation: Aplikasi Penjadwalan Berbasis Algoritma Genetika untuk Meningkatkan Keadilan Distribusi Piket Onibala, Rahellea Joiby; Kumajas, Sondy Campvid; Moningkey, Efraim Ronald Stefanus
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1863

Abstract

This study aims to design and build a website-based application for scheduling fire and rescue personnel on duty at the Minahasa Regency Fire Department by implementing genetic algorithms. The main problem encountered is the manual scheduling process, which causes imbalances in schedule distribution, delays in information, and difficulties in adjusting when personnel changes occur. The system was developed using the Rapid Application Development (RAD) method thorugh the stages of needs identification, design, implementation, and testing. Genetic algorithms are used as an optimization mehod to produce a fair, efficient, and conflict free schedule. The system also provides a permit submission mechanism and automatic notifications to support officer communication and coordination. The results of User Acceptance Testing (UAT) showed an average score of 4.5 (versy good category), indicating that the system is easy to use and meets operational needs. Thus, this application contributes to improving the efficiency, accuracy, and transparency of the on-duty scheduling process at the Minahasa Regency Fire Department. HIGHLIGHTS • Ensures fair and conflict-free duty schedules using genetic algorithm optimization.• Improves communication and coordination with automated permit and notification features.• Achieves high usability with 4.5 UAT score, supporting operational readiness. KEYWORDS Genetic Algorithm; Scheduling System; Firefighters; Web-Based Application; Optimization

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