Indonesian Journal of Innovation Studies
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. Accredited "S3" by the Ministry of Research-Technology and Higher Education Republic of Indonesia Abbreviation IJINS (Indonesian Journal Innovation Studies) DOI prefix 10.21070 by Citation Analysis SCOPUS | Web of Science | Dimension Index Services Google Scholar | SINTA | Dimension | Journalstories ISSN (online) 2598-9936 Publisher Universitas Muhammadiyah Sidoarjo Editor in Chief Dr. Hindarto Managing Editor Mahardhika Darmawan Kusuma Wardana Frequency 4 (four) issues per year (January, April, July and October)
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Overcoming the Challenges of Artificial Intelligence's Negative Impact on the Common Good
General Background: Artificial Intelligence (AI) has emerged as a powerful technological tool that can empower humanity while also producing deceptive and frightening consequences for shared social life. Specific Background: Recent developments in AI raise ethical concerns regarding privacy, discrimination, manipulation, and the weakening of human communication, as reflected in Pope Francis’s teachings. Knowledge Gap: While prior studies discuss ethical challenges and regulatory needs, the deeper roots of AI’s negative impacts and pathways toward the common good require further ethical-critical exploration. Aims: This literature-based research aims to examine how the challenges posed by the negative impacts of AI can be overcome for the goodness of life together. Results: The study finds that AI’s harmful consequences originate in the technocratic paradigm, the myth of unlimited progress, and the neglect of human limitations. Strategic responses include directing AI toward the common good, fostering truly human communication, developing algoretics alongside algorithms, and strengthening governance through regulation and education. Novelty: This research contributes by identifying foundational ethical roots of AI’s negative impacts and proposing an integrated framework of algoretics grounded in human dignity and shared responsibility. Implications: Ethical AI governance requires transparent, inclusive, responsible, unbiased, reliable, and secure systems supported by political commitment and education, ensuring AI serves humanity rather than undermining social justice and peace. Highlights: Negative consequences of AI are rooted in technocracy, unlimited progress myths, and ignored human limits. Ethical-critical guidance calls for algoretics to accompany algorithmic development and deployment. Regulation and education are essential pillars for directing AI toward human dignity and peace. Keywords: Artificial Intelligence, Negative Impacts,The Good of Life Together.
Copyright (c) 2026 Tri Nugroho E.W, Rema Marina, Irsasri Irsasri https://creativecommons.org/licenses/by/4.0
Cross Institutional Synergy in Regional Livestock Control Implementation
Abstract General Background: Regional policy implementation frequently encounters structural and socio-cultural barriers, particularly in regulating public order within rural governance contexts. Specific Background: The implementation of Regional Regulation Number 3 of 2022 concerning livestock control in Moutong District, Parigi Moutong Regency, demonstrates persistent issues, including weak cross-agency coordination, low public legal awareness, inconsistent sanction enforcement, limited facilities, and reactive control patterns. Knowledge Gap: Although both top-down administrative mechanisms and bottom-up community initiatives have been introduced, their interaction has not been systematically conceptualized within an integrated cross-institutional synergy framework. Aims: This study aims to analyze the formation of cross-institutional synergy through the integration of top-down and bottom-up approaches in implementing livestock control policy and to identify determining factors shaping its implementation. Results: Using a descriptive qualitative method with interviews, observations, and documentation, the findings reveal that implementation remains suboptimal due to incidental coordination, dominance of hierarchical directives, uneven sanction application, limited resources, and fragile public trust. However, emerging collaborative practices—such as village livestock task forces, digital reporting mechanisms, vulnerability-based standard operating procedures, and community monitoring—indicate the potential of structured synergy. Novelty: This study constructs a dual-model synergy scheme that integrates hierarchical policy instruments with community-based participation to bridge the gap between normative regulation and social practice. Implications: The findings highlight the necessity of institutionalized coordination, consistent law enforcement, strengthened community engagement, and adaptive governance mechanisms to achieve sustainable livestock control within decentralized regional administration. Highlights • Field coordination remains incidental with uneven sanction practices and limited operational facilities. • Public trust and local creativity shape compliance and collaborative governance capacity. • Integrated hierarchical directives and community-driven initiatives form an adaptive governance scheme. Keywords Cross Institutional Synergy; Policy Implementation; Livestock Control; Regional Regulation; Collaborative Governance
Copyright (c) 2026 Ardiansah Ardiansah, Lucyane Djaafar, Sastro M. Wantu https://creativecommons.org/licenses/by/4.0
Workload Analysis Reveals Excess Operator Capacity and Incentive Requirements
General Background: Workload measurement is a critical component in manufacturing management to ensure balanced labor allocation and cost control. Specific Background: PT. XYZ, a wooden board manufacturing company, faces high production targets requiring operators to maintain consistent productivity without additional staffing. Knowledge Gap: Although workload analysis is commonly applied to determine optimal workforce levels, limited studies explicitly connect workload measurement results with structured incentive determination in manufacturing settings. Aims: This study aims to calculate operator workload using the Workload Analysis (WLA) method and determine appropriate incentives based on workload exceeding normal capacity. Results: Work sampling revealed productive percentages of 78%–83%, and WLA calculations showed workload levels of 106%–115%, indicating overcapacity conditions. The excess workload ranged from 6% to 15%, forming the basis for incentive allocation proportional to overload levels. Novelty: This study integrates work sampling, allowance calculation based on ILO standards, and workload analysis to establish a quantitative linkage between workload percentage and incentive determination. Implications: The findings provide a managerial framework for incentive policy formulation without increasing the number of operators, supporting cost control while maintaining production targets in manufacturing operations. Keywords: Workload Analysis, Work Sampling, Operator Productivity, Incentive Determination, Manufacturing Operations Key Findings Highlights Operator capacity levels exceeded standard workload thresholds across all stations. Productive activity percentages ranged between seventy-eight and eighty-three percent. Incentive allocation was proportionally calculated from quantified overload values.
Copyright (c) 2026 Muhammad Shabirin (Author); Boy Isma Putra https://creativecommons.org/licenses/by/4.0
Santri Disciplinary Punishment Under the Child Protection Law Perspective
General Background: Islamic boarding schools play a significant role in shaping students’ moral character and discipline through structured educational practices. Specific Background: Within pesantren education systems, disciplinary punishment is commonly applied to maintain order and encourage responsibility among santri. Knowledge Gap: However, growing public concern regarding children’s rights raises questions about whether disciplinary practices in pesantren align with the legal principles of child protection. Aims: This study aims to analyze the forms of punishment implemented at Pondok Pesantren Modern Darussalam Kepahiang and examine their compatibility with the provisions of the Child Protection Law. Results: Using a qualitative descriptive approach with data collected through observation, interviews, and documentation, the study identifies three main categories of punishment: physical, psychological, and social sanctions. These disciplinary measures are generally intended to foster discipline, responsibility, and moral awareness rather than to cause harm. When implemented within educational boundaries, the practices are considered consistent with Articles 54 and 59 of the Child Protection Law, while teachers are also legally protected under Law No. 14/2005 on Teachers and Lecturers. Novelty: This research provides a pedagogical and juridical analysis of pesantren disciplinary practices by integrating perspectives of Islamic educational tradition with national child protection regulations. Implications: The findings highlight the importance of establishing clear disciplinary guidelines and providing training for educators to ensure that punishment practices remain educational, ethical, and legally compliant in pesantren environments. Highlights • Identification of three disciplinary sanction categories applied in Islamic boarding school environments • Psychological responses of students reveal varied perceptions toward institutional discipline practices • Absence of formal disciplinary guidelines indicates the need for structured regulatory frameworks Keywords Islamic Boarding School; Child Protection Law; Santri Discipline; Educational Punishment; Pesantren Education
Copyright (c) 2026 Ledian Purnanda, Adisel Adisel, Dayun Riadi https://creativecommons.org/licenses/by/4.0
H.A.R. Tilaar Multicultural Education in Inclusive Indonesian Learning
*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1" data-turn-id="b6cd8122-e31b-4f9c-a884-09d6548f0d32" data-testid="conversation-turn-2" data-scroll-anchor="true" data-turn="assistant"> General Background: Indonesia is characterized by cultural, ethnic, religious, and social diversity that requires educational strategies capable of fostering tolerance and national cohesion. In this context, multicultural education becomes an essential approach for cultivating inclusive values within the educational system. Specific Background: H.A.R. Tilaar is recognized as a prominent Indonesian thinker who conceptualized multicultural education as a philosophical and pedagogical foundation for managing diversity in education. His perspective emphasizes education as a process of humanization and liberation while promoting democratic and inclusive learning environments. Knowledge Gap: Although Tilaar’s ideas are widely discussed in educational discourse, comprehensive studies connecting his philosophical concepts with concrete learning practices in Indonesian classrooms remain limited. Aims: This study aims to analyze Tilaar’s concept of multicultural education and examine its application in the learning process. Results: Using a qualitative library research approach with descriptive analysis, the findings show that Tilaar’s multicultural education promotes dialogical pedagogy, contextual learning, and the role of teachers as transformative agents. Its application in classroom practice includes integrating local cultural values, developing inclusive learning materials, creating democratic classroom interactions, and implementing authentic assessment that considers attitudes such as empathy and tolerance. Novelty: The study provides a comprehensive perspective by integrating Tilaar’s philosophical ideas with practical strategies for implementing multicultural education in learning processes. Implications: These findings demonstrate that Tilaar’s thought offers both philosophical and practical foundations for implementing multicultural education that supports inclusive nationalism and strengthens Indonesia’s cultural resilience within a pluralistic society. Highlights • Tilaar’s perspective frames multicultural education as a process of humanization and liberation in schooling. • Dialogical pedagogy and integration of local cultural values shape democratic classroom practices. • Inclusive learning materials and authentic assessment support tolerance and cultural awareness among students. Keywords Multicultural Education; H.A.R. Tilaar; Inclusive Learning; Dialogical Pedagogy; Cultural Diversity
Copyright (c) 2026 Lonie Anggita, Jumadil Awali habibullah, Nurlaili Nurlaili https://creativecommons.org/licenses/by/4.0
Orange Data Mining Integration Improves Database Learning Scores in High School
General Background: Database learning is a fundamental component of information technology education that requires both conceptual understanding and practical abilities such as designing relational database structures and writing accurate SQL queries. Specific Background: In many classroom settings, students struggle to understand database concepts because learning methods often rely on conventional instruction with limited variation and minimal technological support. Knowledge Gap: Although interactive learning tools and data visualization software have been suggested as alternatives, empirical classroom-based evidence regarding their use in database instruction at the secondary school level remains limited. Aims: This study investigates whether the integration of interactive learning modules with Orange Data Mining software is associated with measurable changes in database learning outcomes among Grade 11 students at SMAN 3 Sidoarjo. Results: Using a quantitative pre-test–post-test design involving 20 students, descriptive statistics showed an increase in mean scores from 76.50 in the pre-test to 83.30 in the post-test. Normality testing confirmed normally distributed data, and a paired sample t-test produced a significance value of 0.011 (<0.05), indicating a statistically significant difference between the two measurements. Novelty: The study demonstrates a classroom implementation in which interactive modules are combined with visual data mining tools to support both conceptual comprehension and practical data analysis activities in database learning. Implications: These findings provide empirical evidence supporting the integration of data visualization–based learning environments in secondary information technology education and suggest that technology-supported instructional strategies may contribute to improved database learning performance and student engagement. Highlights: Mean student performance increased from 76.50 before treatment to 83.30 afterward. Statistical testing showed a significant difference between pre-test and post-test results (p = 0.011). Visual data exploration activities helped learners interpret relational data patterns and query results more clearly. Keywords: Orange Data Mining, Interactive Learning Media, Online Learning, Data Analysis.
Copyright (c) 2026 Dian Rahma Santoso, Angga Yunanto, Aditya Krisna Affandi, Silvana Desy Pamungkasari https://creativecommons.org/licenses/by/4.0
Innovative Economics Learning for 21st Century Skills
*]:pointer-events-auto scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" tabindex="-1" data-turn-id="request-WEB:59fd4916-f409-4246-963a-bbf4c65c4ba8-1" data-testid="conversation-turn-4" data-scroll-anchor="true" data-turn="assistant"> General Background: Rapid technological and economic transformation in the Industrial Revolution 4.0 era requires economics education to move beyond theoretical knowledge toward the development of 21st century skills, including critical thinking, communication, collaboration, creativity, digital literacy, and entrepreneurship. Specific Background: Recent studies show a shift from teacher-centered instruction to student-centered, experiential, and technology-based learning in economics classrooms, incorporating project-based learning, digital simulations, artificial intelligence tools, internships, and collaborative problem solving. Knowledge Gap: However, most prior research focuses on single methods or specific institutional contexts, with limited systematic synthesis integrating diverse innovative approaches, implementation challenges, and institutional readiness. Aims: This study conducts a Systematic Literature Review using the PRISMA framework to synthesize peer-reviewed articles published between 2021 and 2025 on innovation in economics learning methods and their relation to 21st century skills development. Results: Fourteen selected studies reveal five major categories of innovation: technology-based learning, experiential and project-based learning, collaborative and participatory approaches, entrepreneurship-oriented learning, and self-regulated learning, consistently associated with the development of critical thinking, communication, collaboration, creativity, digital literacy, and entrepreneurial competencies. Novelty: This review provides an integrated conceptual mapping of innovative economics learning methods and their pedagogical mechanisms within a unified analytical framework. Implications: The findings highlight the need for alignment among instructional design, institutional support, digital infrastructure, and educator readiness to advance integrated, contextually relevant economics education for contemporary professional demands. Highlights • Identification of five categories of pedagogical innovation across fourteen peer-reviewed studies. • Consistent linkage between active learning approaches and development of 4C competencies. • Emphasis on institutional readiness and digital infrastructure as enabling conditions. Keywords Economics Education; Learning Innovation; 21st Century Skills; Digital Literacy; Systematic Literature Review
Copyright (c) 2026 Fitria Rahmona, Siti Fermaisuri, Armiati Armiati https://creativecommons.org/licenses/by/4.0
ISO 23247 Digital Twin Model for JIT Supply Chain Visibility
General Background: Automotive supply chains operating under Just-in-Time (JIT) principles require high levels of supply chain visibility to maintain synchronized material flow and stable production rhythms. Specific Background: In practice, daily monitoring using the Material Information Flow Chart (MIFC) remains constrained by paper-based tools or non-integrated digital systems, resulting in information lead times of one to two weeks and limited support for real-time problem solving. Knowledge Gap: Although Digital Twin technology and ISO 23247 architecture provide a standardized digital representation framework, limited studies address structured integration of conventional MIFC with ISO 23247 for cross-supply chain material flow representation in JIT environments. Aims: This study proposes the design of an ISO 23247–based MIFC Digital Twin model (MIFCDT) to represent material flow through structured digital entities aligned with Observable Manufacturing Elements and standard information attributes. Results: The model maps seven MIFC symbols into OME Equipment and OME Process entities and formulates digital representations using identifier, characteristics, location, capacity, and dynamic status attributes capturing timestamp and quantity data. A conceptual automotive supply chain scenario demonstrates one-to-one correspondence between physical and digital entities, enabling structured monitoring of cycle time deviation and lead time delay. Novelty: The study introduces a structured digital representation model that bridges conventional MIFC practice with ISO 23247 architecture at the material flow level. Implications: The proposed model provides a conceptual foundation for real-time supply chain visibility and supports daily management in JIT-based automotive systems while opening pathways for further empirical implementation. Highlights • Structured mapping of seven MIFC symbols into ISO 23247 Observable Manufacturing Elements. • Formulation of static and dynamic digital attributes capturing timestamp, quantity, and location data. • One-to-one correspondence between physical production points and digital entities demonstrated in a conceptual automotive scenario. Keywords Digital Twin; ISO 23247; Supply Chain Visibility; Just-In-Time; Material Information Flow Chart
Copyright (c) 2026 Rudy Riyanto, Putu Dana Karningsih , Berlian Al Kindhi https://creativecommons.org/licenses/by/4.0
Toward a More Dynamic Supplier Evaluation: A Time Series Forecasting Perspective
General Background: Procurement continuity is essential for maintaining healthcare service operations, where supplier failures can disrupt service quality. Specific Background: This study evaluates supplier reliability in provincial government healthcare facilities in East Java, Indonesia, using three key performance metrics: on-time delivery (OTD), quantity fulfillment, and order lead time, based on 2023 contract data from 13 pharmaceutical suppliers. Knowledge Gap: Traditional supplier evaluation is often static, limiting the ability to detect temporal performance shifts and future reliability risks. Aims: This research aims to develop a dynamic supplier evaluation framework by integrating time series forecasting methods. Results: Historical performance showed moderate–high reliability (OTD ≈ 80.04%, quantity fulfillment ≈ 79.3%, lead time ≈ 20 days). Forecasting with exponential smoothing and Theta methods indicated declining OTD and quantity fulfillment, alongside improved lead time performance (≈ 10 days). Forecast errors were MAE ≈ 25% and RMSE ≈ 32% for service metrics, and MAE ≈ 8 days and RMSE ≈ 9 days for lead time. Novelty: The study advances supplier evaluation by combining multimetrical reliability assessment with forecasting-based temporal detection, moving beyond one-time performance scoring. Implications: This dynamic approach supports healthcare procurement managers in prioritizing resilient suppliers, adapting sourcing strategies, and mitigating operational risks in uncertain environments. Highlights: Supplier performance exhibited fluctuating reliability patterns across monthly contract periods. Forecasting results revealed decreasing delivery and fulfillment rates with shorter shipment durations. Service compliance metrics were strongly correlated, while lead time remained relatively independent. Keywords: Public Healthcare Procurement, Supplier Evaluation, Supplier Performance Forecasting, Supplier Reliability
Copyright (c) 2026 Muhammad Naufal Fikri, I Nyoman Pujawan, Putu Dana Karningsih https://creativecommons.org/licenses/by/4.0
SQC and Fuzzy FMEA Reveal Defect Priorities in Fairy Tale Book Printing
General Background Quality control is a critical requirement in the printing industry to ensure products conform to predetermined standards and maintain visual and functional quality. Specific Background PT XYZ, a large-scale printing company in Indonesia, records fairy tale books as the product with the highest defect rate across Web Printing, Sheetfed Printing, and Finishing processes. Knowledge Gap Existing quality control practices at the company are predominantly focused on final inspection, creating a gap between quality standards and actual process conditions, while empirical applications of integrated SQC and Fuzzy FMEA in the printing industry remain limited. Aims This study aims to analyze defect characteristics and determine priority causes of defects in fairy tale book production using Statistical Quality Control (SQC) and Fuzzy Failure Mode and Effect Analysis (Fuzzy FMEA). Results SQC analysis identified dominant defects, namely dirty paper appearance (21.3%), color mismatch (17.9%), fold mismatch (17.8%), varnish crack (15.4%), floy (15.3%), and staple reject (12.3%). Fuzzy FMEA results indicate that fold mismatch caused by unstable temperature and humidity conditions in the production environment has the highest risk priority with an FRPN value of 3.42, followed by operator inaccuracy, improper machine settings, inconsistent raw material quality, and weak supervision. Novelty This research presents an integrated application of SQC and Fuzzy FMEA specifically within fairy tale book printing operations. Implications The findings provide a structured basis for prioritizing corrective actions through environmental control, operator training, machine adjustment, and raw material inspection to reduce defect levels in printing processes. Highlights: Dirty paper appearance represents the largest proportion of defects in fairy tale book production. Fold mismatch associated with production environment conditions shows the highest risk priority. Integrated analytical methods enable systematic prioritization of defect causes in printing processes. Keywords: Defects, Fairy Tale Books, Fuzzy FMEA, Quality, Statistical Quality Control
Copyright (c) 2026 Ananta Oktaviya, Enny Aryanny https://creativecommons.org/licenses/by/4.0
ABC–FSN Min–Max Method to Reduce Lubricating Oil Inventory Cost
General Background: Inventory control is a critical operational function to maintain cost efficiency and balance between stockout and overstock conditions in spare parts management. Specific Background: PT XYZ, a port heavy equipment spare parts provider, experienced excessive lubricating oil orders, leading to overstock levels of up to 21.2% and increased total inventory costs. Knowledge Gap: Prior studies on ABC–FSN and min–max stock primarily rely on historical data, resulting in static inventory parameters that insufficiently address future demand fluctuations. Aims: This study aims to control lubricating oil inventory by integrating ABC–FSN classification, min–max stock policy, and time series forecasting to minimize total inventory costs. Results: ABC–FSN analysis identified two Fast-A items, CC-0442 and CC-0444, as priority products. The company’s method generated total inventory costs of Rp 22,195,200, whereas the min–max stock method reduced costs to Rp 16,936,576, yielding savings of Rp 5,258,624 (23.69%). Forecasting for January–December 2026 produced average monthly demands of 2,439 liters for CC-0442 and 1,413 liters for CC-0444, resulting in order quantities of 1,000 liters every 8 days and 600 liters every 9 days, with projected total costs of Rp 15,416,000. Novelty: The integration of ABC–FSN classification with forecasting-based min–max parameters provides a more adaptive inventory control framework. Implications: The proposed approach supports systematic prioritization, cost minimization, and responsive inventory planning for lubricating oil management. Highlights: Fast-A prioritization identified CC-0442 and CC-0444 as critical high-turnover, high-value items. Cost comparison revealed savings of Rp 5,258,624 (23.69%) versus the existing practice. Forecast-based planning established 8-day and 9-day replenishment cycles for 2026. Keywords: ABC-FSN, Forecasting, Inventory Control, Min Max Stock
Copyright (c) 2026 Nazwa Rifqi Armevia, Enny Aryanny https://creativecommons.org/licenses/by/4.0
Lagrange Multiplier Inventory Optimization for Constrained Head Truck and Crane Tire Warehousing
General Background: Inventory management in multi-item systems with limited warehouse capacity requires mathematical optimization to control ordering and holding costs while maintaining operational continuity. Specific Background: PT XYZ, a supplier of port heavy equipment spare parts, experienced overstock of head truck and crane tires due to fluctuating demand and a warehouse capacity limited to 25 m³, resulting in total inventory costs of Rp134,142,000 and storage requirements exceeding capacity at 29.5 m³. Knowledge Gap: Prior studies predominantly addressed manufacturing or retail settings with relatively stable demand, while applications in port heavy equipment spare parts characterized by fluctuating demand and actual capacity constraints remain limited. Aims: This study aims to determine optimal order quantities for three tire types using the Lagrange Multiplier method to minimize total inventory cost under warehouse capacity constraints, integrating time series forecasting for the January–December 2026 period. Results: The Lagrange Multiplier model produced optimal order quantities of 60, 33, and 8 units, requiring 24.6 m³ and reducing costs to Rp127,643,500 compared with the company method. Forecast-based optimization recommended 58, 32, and 9 units with ordering intervals of 16, 24, and 18 days, occupying 24.75 m³ and generating total inventory costs of Rp125,985,500. Novelty: This study integrates multi-item Lagrange Multiplier optimization with Single Exponential Smoothing forecasting and Moving Range Chart verification in a port spare parts warehousing context. Implications: The findings provide a quantitative decision framework for capacity-constrained inventory planning, supporting cost minimization and structured warehouse utilization in heavy equipment spare parts management. Highlights: Mathematical optimization generated lower total stock expenditure compared with the existing ordering approach. Forecast-integrated planning maintained storage usage within the 25 m³ limit. Defined replenishment intervals of 16, 24, and 18 days supported structured procurement scheduling. Keywords: Inventory, Lagrange Multiplier, Tire
Copyright (c) 2026 Rangga Dhika Syahputra, Enny Aryanny https://creativecommons.org/licenses/by/4.0
Supplier Performance Prioritization Using Analytical Hierarchy Process Framework
General Background: Supplier evaluation is a critical component of supply chain management to ensure operational continuity and procurement quality. Specific Background: Organizations require structured decision-making tools to assess multiple criteria in selecting and evaluating suppliers objectively. Knowledge Gap: Although the Analytical Hierarchy Process (AHP) has been widely applied, its structured implementation for supplier performance prioritization in the observed company context has not been systematically documented. Aims: This study aims to determine priority criteria and identify the best supplier alternative using the AHP framework. Results: The analysis produced weighted criteria rankings, verified consistency ratios below the acceptable threshold, and generated a final supplier priority order based on global weights. Novelty: The study presents a comprehensive hierarchical structuring of criteria and sub-criteria aligned with company-specific procurement conditions. Implications: The findings provide a structured decision support basis for managerial policy in supplier selection and contribute to applied research in supplier performance measurement using multi-criteria decision-making methods. Keywords: Analytical Hierarchy Process, Supplier Evaluation, Multi-Criteria Decision Making, Supply Chain Management, Decision Support System Key Findings Highlights Criteria weighting identified dominant factors in supplier assessment. Consistency ratio confirmed reliable pairwise comparison judgments. Final ranking determined a priority supplier based on global synthesis weights.
Copyright (c) 2026 Yoga Rachmawan, Hana Catur Wahyuni (Author) https://creativecommons.org/licenses/by/4.0
Technology Contribution Coefficient and Strategic Position of Knife Manufacturing IKM
General Background: Technology capability plays a critical role in transforming raw materials into value-added products within small and medium manufacturing enterprises. Specific Background: Krian Custom Tools, a knife manufacturing IKM established in 2013, relies on technoware, humanware, infoware, and orgaware components to maintain product quality and production consistency. Knowledge Gap: The technological components had not previously been quantitatively measured to determine their contribution level and corresponding strategic direction. Aims: This study aims to calculate the Technology Contribution Coefficient (TCC) using the technometric method and formulate strategic recommendations through SWOT analysis. Results: The overall TCC value reached 0.805, categorized as very good and modern. Component sophistication values were 0.689, 0.880, 0.858, and 0.847, and all components were positioned in Quadrant I of the SWOT diagram. Novelty: The study integrates technometric evaluation and SWOT positioning within a knife manufacturing IKM context. Implications: The findings provide a structured basis for strategic technology development and decision-making in small-scale manufacturing enterprises. Keywords: Technology Contribution Coefficient, Technometric Method, SWOT Analysis, Technology Components, Small Medium Enterprise Key Findings Highlights Aggregate coefficient indicates advanced technological classification level All evaluated elements positioned in aggressive strategic quadrant Quantitative assessment supports structured development planning
Copyright (c) 2026 Muhammad Naufal Maulana, Hana Catur Wahyuni (Author) https://creativecommons.org/licenses/by/4.0
Rotational Speed Variation Governs Impact Strength in HDPE Friction Stir Welding
General Background: Friction Stir Welding is increasingly applied in polymer joining due to its solid-state mechanism and ability to produce stable joints without melting. Specific Background: High-Density Polyethylene requires appropriate process parameters to obtain optimal mechanical performance, particularly under impact loading. Knowledge Gap: Previous studies have discussed process parameters in metal and polymer welding, yet limited studies specifically address the relationship between rotational speed variation and impact strength characteristics in HDPE joints. Aims: This study aims to analyze the effect of spindle rotational speed variation on the impact strength and microstructural characteristics of HDPE joints produced by Friction Stir Welding. Results: The experimental findings demonstrate that rotational speed variation significantly alters impact strength values and joint morphology, where certain rotational settings generate more homogeneous structures and higher resistance to impact loading. Novelty: The study provides a focused experimental evaluation of rotational speed parameters on HDPE joints using impact testing and metallographic observation within a controlled setup. Implications: These findings contribute to parameter optimization strategies in polymer-based Friction Stir Welding and provide practical guidance for improving joint reliability in engineering applications. Keywords: Friction Stir Welding, High-Density Polyethylene, Rotational Speed, Impact Strength, Microstructure Key Findings Highlights Rotational parameter selection determines joint toughness performance. Homogeneous internal morphology correlates with higher absorbed energy values. Controlled spindle settings produce more stable polymer joint characteristics.
Copyright (c) 2026 Mohammad Hanif Firmansyah (Author); Iswanto https://creativecommons.org/licenses/by/4.0
Cylinder Overhaul Restores Dimensional Accuracy and Emission Compliance
General Background: Multi Purpose Vehicles require proper engine maintenance to sustain operational reliability and emission compliance. Specific Background: Cylinder wear in MPV engines leads to loss compression, reduced power, and inefficient fuel combustion, requiring overhaul procedures involving inspection, oversize machining, component replacement, and emission testing. Knowledge Gap: Quantitative documentation of dimensional changes in cylinder blocks, pistons, and piston ring end gaps before and after overhaul in MPV engines remains limited. Aims: This study aims to analyze the cylinder overhaul process in an MPV engine and evaluate dimensional measurements and exhaust gas emissions after repair. Results: Initial measurements showed cylinder diameter reduction from the 72.00 mm standard to an average of 71.91 mm and piston wear below standard limits. After oversize machining and component replacement, cylinder diameter reached 72.48 mm and piston diameter 72.50 mm, while piston ring gaps returned within standard ranges. Emission testing indicated CO at 0.05%, HC at 25 ppm, and CO2 at 14.7%, meeting regulatory thresholds. Novelty: The study presents integrated dimensional measurement and emission validation within a single overhaul analysis. Implications: The findings provide practical technical guidance for accurate cylinder overhaul procedures in MPV maintenance. Keywords: Cylinder Overhaul, MPV Engine Maintenance, Dimensional Measurement, Piston Ring Clearance, Exhaust Emission Test Key Findings Highlights Pre-repair measurements identified significant wear beyond tolerance limits Post-repair machining achieved conformity with manufacturer specifications Exhaust parameters satisfied regulatory requirements after reassembly
Copyright (c) 2026 Fakhrudin (Author); Mulyadi https://creativecommons.org/licenses/by/4.0