Abstract:This study aims to analyze students’ experiences in conducting self-assessment using the Duolingo Speak application in speaking skills learning at a higher education institution in Indonesia. The focus of this research covers…
covers five main aspects, namely: students’ self-assessment strategies, increased speaking confidence, improved vocabulary mastery, challenges encountered while using Duolingo Speak, and the enhancement of learner autonomy. This study employs a qualitative approach with a case study method, which aims to gain an in-depth understanding of students’ experiences in utilizing Duolingo Speak as a self-assessment tool in speaking learning. Data were collected through semi-structured interviews and documentation involving five students selected through purposive sampling, namely students who had used Duolingo Speak for at least one semester. The data were analyzed using thematic analysis through data organization, coding, theme identification, and conclusion drawing. The findings show that the use of Duolingo Speak provides positive learning experiences for students. The application helps students apply various self-assessment strategies, increases speaking confidence, enriches vocabulary mastery, and fosters learner autonomy. However, several challenges were also found, such as limitations in speech recognition accuracy and feedback that is not yet sufficiently detailed to support optimal reflective learning. Overall, Duolingo Speak can serve as an effective supporting tool in speaking skills instruction when combined with structured self-assessment guidance from lecturers, thereby enhancing the effectiveness of English as a Foreign Language (EFL) learning.
Abstract:This study systematically reviews the development of Total Quality Management (TQM) practices in relation to Green Quality Intelligence Capabilities (GQIC), Circular Process Innovation (CPI), and Sustainable Operational…
Performance (SOP). Responding to the need for a clearer review method and a more focused novelty, this article applies the PRISMA 2020-based Systematic Literature Review approach. Articles were identified from the Scopus database using keyword combinations related to TQM, quality management practices, green capability, green innovation, circular economy, circular process innovation, Industry 4.0, Quality 4.0, and sustainability performance. After identification, screening, eligibility assessment, and quality appraisal, 27 articles published between 2016 and 2026 were included in the final synthesis. The findings show that TQM literature has shifted from traditional quality control and customer satisfaction toward digital, green, and sustainability-oriented quality management. Soft TQM dimensions, such as leadership, employee involvement, training, and quality culture, and hard TQM dimensions, such as process management, quality tools, continuous improvement, and data-based decision making, remain dominant. However, prior studies still frequently use general mediators, including knowledge management, organizational culture, innovation capability, and competitive advantage. This review proposes CPI as a more specific mediation mechanism that translates TQM and GQIC into sustainable operational outcomes through waste reduction, resource efficiency, material reuse, energy efficiency, and circular process redesign. The study contributes by offering an integrated conceptual model and propositions for future empirical research on quality management, green intelligence, circular innovation, and sustainable operations.
Abstract:Artificial intelligence (AI) integration in language education offers new opportunities to address challenges in English as a Foreign Language (EFL) contexts. This study examines the effectiveness of Copilot in enhancing…
academic English literacy among Indonesian undergraduates. Using a quantitative quasi-experimental design with a pre-test and post-test control group, 60 students were divided into experimental and control groups. Instruments included comprehension tests, learner autonomy questionnaires, and rubric-based writing assessments. Results showed significant improvements in the experimental group. Academic text comprehension increased, particularly in vocabulary mastery (+12%), rhetorical structures (+15%), and recognition of formal registers (+10%). Copilot usage positively predicted learner autonomy, with gains in goal-setting (+14%), strategy selection (+11%), and self-evaluation (+13%). Writing performance also improved, especially in coherence (+13%), argumentation (+16%), and adherence to conventions (+12%). The findings confirm Copilot’s role as both corrective aid and developmental partner, fostering academic literacy and learner autonomy. Implications suggest integrating AI tools into EFL curricula to strengthen academic discourse and independent learning.
Abstract:Research is the systematic and planned process of collecting, processing, and analyzing data in accordance with scientific principles to seek truth, solve problems, or discover new knowledge. Conducting research often serves…
rves as a final project for undergraduate students to complete their studies; for Educational Technology undergraduates, in particular, development research is highly recommended. Development research—or Research and Development (R&D)—is a scientific method used to create new products or improve existing ones, as well as to test their effectiveness. These products may take the form of media, models, modules, or tools. Specifically for Educational Technology undergraduates, this type of research involves a scientific approach to designing, producing, and testing the feasibility of instructional products—such as interactive media, learning models, or digital modules—to address learning challenges. The primary objective of R&D for Educational Technology undergraduates is to produce instructional products that are valid, practical, and effective in solving learning problems and enhancing the quality of the learning process and performance. The benefits of such research include improved skills in creating instructional products, the ability to solve real-world learning problems, and the development of a professional portfolio.
Abstract:Pemilihan Ketua Badan Eksekutif Mahasiswa (BEM) merupakan proses penting dalam menentukan mahasiswa yang memiliki kompetensi terbaik untuk memimpin organisasi kemahasiswaan. Namun, proses seleksi yang masih bergantung pada…
da popularitas dan penilaian subjektif berpotensi menghasilkan keputusan yang kurang optimal. Penelitian ini bertujuan membangun Sistem Pendukung Keputusan (SPK) menggunakan metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) untuk membantu proses pemilihan Ketua BEM secara objektif. Data penelitian diperoleh melalui wawancara dengan pembina BEM untuk menentukan kriteria dan bobot penilaian. Lima kriteria yang digunakan meliputi kepemimpinan, kemampuan komunikasi, pengalaman organisasi, integritas, dan indeks prestasi kumulatif (IPK). Tahapan metode MOORA terdiri atas penyusunan matriks keputusan, normalisasi, perhitungan nilai optimasi, dan proses perangkingan. Hasil penelitian menunjukkan bahwa alternatif K1 memperoleh nilai optimasi tertinggi sebesar 0,473 sehingga direkomendasikan sebagai Ketua BEM terpilih. Penerapan metode MOORA mampu menghasilkan proses pengambilan keputusan yang lebih objektif, sistematis, transparan, dan akurat sehingga dapat dijadikan sebagai alat bantu dalam menentukan Ketua BEM berdasarkan kriteria yang telah ditetapkan.
The selection of the Student Executive Board (BEM) President is an important process in determining the most qualified student to lead the student organization. However, conventional selection processes often rely on popularity and subjective judgments, which may lead to less optimal decisions. This study aims to develop a Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to support a more objective selection process. Research data were collected through interviews with BEM advisors to determine the assessment criteria and their corresponding weights. Five criteria were used, namely leadership, communication skills, organizational experience, integrity, and grade point average (GPA). The MOORA method consists of decision matrix construction, normalization, optimization value calculation, and ranking. The results indicate that candidate K1 achieved the highest optimization value of 0.473 and was therefore recommended as the selected BEM President. The implementation of the MOORA method provides a more objective, systematic, transparent, and accurate decision-making process, making it an effective tool for supporting the selection of the most suitable BEM President based on predetermined criteria.
Abstract:The rapid integration of Artificial Intelligence (AI) into organizational systems has transformed workplace dynamics, employee responsibilities, and patterns of human labor. Although AI implementation improves operational…
l efficiency and productivity, it also creates psychological and professional challenges for employees adapting to technological change. This study aims to explore the lived experiences, emotional responses, and adaptation strategies of employees in South Sulawesi companies undergoing AI-driven digital transformation. This research employed a qualitative phenomenological approach. Data were collected through in-depth semi-structured interviews with 20 participants from the banking, manufacturing, retail, technology, and service sectors in South Sulawesi, Indonesia. Participants were selected using purposive sampling based on direct exposure to AI systems and a minimum of 1.5 years of work experience. The data were analyzed using thematic analysis to identify recurring patterns and meanings related to employee adaptation. The findings revealed six major themes: AI as a tool for improving efficiency and productivity, fear of job displacement and career uncertainty, the importance of continuous learning and digital skill development, the role of organizational support and leadership communication, the emergence of human–AI collaboration, and varied psychological responses to technological change. Employees who received organizational support and training demonstrated greater adaptability and confidence in responding to AI implementation. The study emphasizes the importance of human-centered change management strategies that prioritize psychological safety, transparent communication, and continuous digital training. This research contributes to the limited phenomenological literature on AI adaptation in Indonesia and provides practical implications for human resource management and organizational behavior in the era of digital transformation.
Abstract:This study examines the implementation of the Quality Control Circle (QCC) system to enhance employee engagement and productivity at Contemporary Amperex Technology Co., Limited (CATL) headquarters and its Indonesian branch.…
nch. As a global leader in lithium-ion battery manufacturing, CATL integrates innovative technology with employee participation to improve work processes and operational performance. QCC is applied as a structured approach that empowers employees to identify workplace problems, develop solutions, and collaborate in continuous improvement activities using quality management tools and the PDCA cycle. The research employs a case study and comparative analysis method to explore differences between the standardized QCC system at CATL headquarters and the more flexible, localized implementation in Indonesia. The study involved permanent employees from both organizations using saturated sampling, with a total of 10 respondents. In addition, a five-day productivity training program was conducted in China and Karawang through lectures, case studies, and project-based learning, evaluated using pre-test and post-test assessments. The findings indicate that QCC significantly improves employee understanding of productivity management, strengthens communication, enhances product quality, reduces quality-related costs, and increases employee engagement, motivation, and organizational commitment in both operational environments
Abstract:This study explores how the Salatiga City Government operationalizes principles of good governance and implements the Government Internal Control System (GICS), as reflected in the 2024 Local Government Financial Report–…
�� LKPD. The research also assesses how these mechanisms contribute to achieving Sustainable Development Goal (SDG) 16. Employing a descriptive qualitative approach, this study analyzes secondary data 2024 LKPD, performance accountability reports, and related internal control evaluations. This is complemented by triangulated insights from interviews with key government personnel. The findings reveal that Salatiga City has embedded core governance principles-transparency, accountability, and participatory engagement-within its financial reporting processes. The city's internal control system has reached Maturity Level 3 (Defined), indicating that control mechanisms are well-documented, institutionalized, and consistently applied. The use of digital reporting tools and community-based oversight further supports a culture of openness and accountability. The case of Salatiga City provides actionable insights for other local governments seeking to enhance financial governance. These practices directly support Indonesia's commitment to SDG 16, by fostering public trust and institutional integrity. This study adds to the emerging literature by integrating GICS analysis with local-level governance outcomes, not only to meet compliance standards but also to advance broader, effective, accountable, and inclusive development goals.
Abstract:The rapid proliferation of AI-powered marketing technologies in emerging markets poses a fundamental challenge to culturally-grounded micro, small, and medium enterprises (MSMEs): how can algorithmic imperatives be reconciled…
ciled with indigenous value systems that define not only business practice but collective identity? Despite growing research on both AI adoption in SMEs and indigenous knowledge preservation, scholarship rarely examines how traditional values actively mediate rather than merely moderate commercial technology adoption. This study addresses that gap by investigating how MSMEs in Makassar City, Indonesia, negotiate AI marketing integration while preserving siri’ na pacce, the Bugis-Makassar philosophical framework centred on dignity (siri’) and solidarity (pacce). Employing interpretive phenomenology integrated with Community-Based Participatory Research (CBPR), the study conducted 23 in-depth interviews and three focus group discussions with 44 MSME owners and key personnel across traditional culinary, artisan craft, ethnic fashion, and digital service sectors. Template analysis generated four overarching themes: (1) value-based technology discernment, wherein siri’ na pacce operates as an active epistemological filter for evaluating AI tools; (2) strategic selective adoption, wherein enterprises accept algorithmically aligned functions while rejecting culturally incompatible features; (3) cultural indigenization of technology, wherein AI systems are actively reoriented toward communal rather than individualistic ends; and (4) constrained agency under platform power, wherein algorithmic visibility systems penalise cultural non-conformity with market exclusion. These findings challenge technological determinism and advance decolonial computing theory by demonstrating that indigenous values simultaneously enable epistemological agency and are constrained by structural power asymmetries, a duality insufficiently theorised in prior technology adoption frameworks. The study calls for regulatory frameworks establishing indigenous data sovereignty, participatory AI co-design with local communities, and cooperative digital infrastructure as conditions for authentic, rather than performative, cultural integration.
Abstract:This study develops a practical framework for evaluating AI-generated brand visuals in a marketing communication context. Using a qualitative case study of an Indonesian sustainable startup (I-NewBee), the research employs…
ys photo-elicitation interviews to compare consumer evaluations of brand assets generated by three text-to-image tools (Midjourney, Neural Love AI, and Leonardo AI). Twelve target-market participants assessed anonymized visual sets (A/B/C) produced under a standardized prompt structure, using a semi-structured protocol informed by attention-stage cues from the AISAS model. Expert input from a visual communication design practitioner was used to triangulate judgments on visual quality and brand fit. Data were analyzed through iterative coding and thematic synthesis to identify recurring evaluation dimensions and decision cues. The findings suggest that perceived brand fit is shaped by visual realism, compositional clarity, brand-consistent signals, and message interpretability, while prompt ambiguity and inconsistent visual cues reduce credibility. The paper contributes an actionable evaluation framework expressed as evaluation dimensions and prompt-design considerations for startups seeking to deploy generative AI responsibly in brand communication