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Challenges and Solutions for Inclusive Education in Primary Schools Literature Review Yusli Yusli; Zohaib Hassan Sain
Al Hikmah: Journal of Education Vol 6, No 2 (2025): Al Hikmah: Journal of Education
Publisher : Lembaga Pendidikan Hikmatun Najah Blora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54168/ahje.v6i2.419

Inclusive education in Elementary schools has become an urgent need to ensure access and quality education for all students, including those with special needs. This research aims to identify the challenges and solutions of inclusive education in elementary school through a literature review. The findings reveal that the primary challenges include a lack of teacher training, inadequate facilities, social stigma, and an inflexible curriculum. Proposed solutions encompass continuous teacher training, the provision of accessible infrastructure, community awareness campaigns, and a curriculum adapted to the diversity of students. This study concludes that inclusive education in elementary school requires collaboration among stakeholders, including schools, government, and communities, to create an equitable and supportive learning environment. The findings provide implications for educational policy in Indonesia to strengthen the implementation of inclusion at the primary level.

Exploring the Impact of ICT Resources and Organisational Support on Job Satisfaction: A Work-Life Balance Perspective in Private Banks Aji Dwi Saputro; Zohaib Hassan Sain
BUSMI : Journal of Business and Management Innovations Vol. 1 No. 3 (2025): BUSMI : Journal of Business and Management Innovations
Publisher : Asosiasi Riset Ekonomi dan Akuntansi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

This study explores how Information and Communication Technology (ICT) resources and Perceived Organisational Support (POS) influence employee job satisfaction, with a focus on the mediating role of Work-Life Balance (WLB). The object of research is the workforce within digitally-enabled private banks in Indonesia, where digitalisation and human resource management practices intersect in shaping employee experience. The study addresses the emerging issue where technological flexibility, while beneficial, contributes to blurred work-life boundaries and emotional fatigue. At the same time, organisational support is not always aligned with employees’ evolving needs. Therefore, the objective is to examine both direct and indirect relationships between ICT, POS, WLB, and job satisfaction. A quantitative approach was applied through a structured survey conducted among 125 employees working in private banks located in Central Java and Yogyakarta. Data were analysed using Partial Least Squares–Structural Equation Modelling (PLS-SEM) to test the hypothesised relationships. Findings confirm that both ICT resources and POS significantly affect job satisfaction, with WLB playing a mediating role. POS emerged as a stronger predictor than ICT. The results validate Social Exchange Theory as an explanatory framework and show how organisational support and digital tools jointly influence employee well-being. This study concludes that sustainable job satisfaction in digital banking environments requires a dual focus on technological advancement and empathetic organisational practices. Work-life balance should be treated as a strategic component of human resource policies in the digital era.

Text mining and semantic modeling of literary corpora: a machine learning–based study of Indonesian fiction Rinda Widya Ikomah; Zohaib Hassan Sain
Lingua Technica: Journal of Digital Literary Studies Vol. 2 No. 1 (2026): Literature and computation: Mapping, modeling, and mediation
Publisher : Asosiasi Relawan dan Pengelola Jurnal LPTNU (ARJUNU)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64595/lingtech.v2i1.133

Background: The large-scale digitization of Indonesian literary works has produced extensive textual corpora that challenge conventional close-reading approaches and call for systematic, data-driven methods capable of capturing thematic, semantic, and affective patterns in fiction. Objective: This study aims to examine how text mining and semantic modeling can reveal lexical salience, intertextual relations, and narrative emotion in Indonesian fiction across different thematic orientations. Method: Using a quantitative corpus-based design, the study analyzes 36 Indonesian literary texts published between 1980 and 2022 through TF–IDF–based lexical analysis, document-level semantic embeddings with cosine similarity and clustering, and sentence-level sentiment analysis. Results: The findings show distinct lexical signatures that differentiate thematic clusters, coherent semantic groupings reflecting intertextual proximity, and sentiment trajectories dominated by neutral-to-negative polarity with strategically placed affective peaks across narrative progression. Implication: These results demonstrate that computational methods can empirically support literary analysis without displacing interpretive criticism. Novelty: The study integrates lexical, semantic, and affective modeling within a unified framework for Indonesian fiction, offering a scalable and replicable approach to digital literary studies.

Ethical Implications of Artificial Intelligence in Lifelong Learning: An Empirical Mixed-Methods Study on Educational Equity Human Capital Development Zohaib Hassan Sain; Anni Rahimah; Nurulannisa Abdullah; Nurhana Fakhriyah Imtinan; Chanda Chansa Thelma
Journal of Information Systems and Technology Research Vol. 5 No. 2 (2026): May 2026
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v5i2.1486

The rapid integration of Artificial Intelligence (AI) into lifelong learning creates a range of opportunities and challenges, especially for educational equity and human capital development. AI applications in educational environments have the potential to enable personalized learning, expand access, and improve outcomes. Yet, these advantages raise important issues regarding privacy, bias, and human oversight in education. The main aim of this research is to investigate how AI can support educational equality in lifelong learning environments. The research aims to recognise and respond to ethical issues, such as bias, privacy, and implications for autonomy in learning. The study employs a mixed-methods design that includes quantitative surveys, qualitative interviews, and document analysis to assess these concerns. Descriptive statistics and regression analysis are employed for quantitative data, while thematic analysis is conducted for qualitative data to identify major patterns related to ethical considerations. Results demonstrate that AI integration is significantly and positively associated with perceived educational equity (β=0.45, p=0.001), while Data Privacy Concern (β=−0.30, p=0.003) and Algorithmic Bias Concern (β=−0.25, p=0.042) show significant negative moderating effects. Qualitative analysis identifies regulatory need (90%), data privacy (75%), and algorithmic bias (60%) as dominant stakeholder concerns. The study underscores the imperative of robust ethical governance frameworks to ensure AI technologies advance educational equity equitably and sustainably

PENGARUH BEBAN KERJA, LINGKUNGAN KERJA, DAN KOMPENSASI TERHADAP KINERJA KARYAWAN PADA PT. PRIMAYUDHA MANDIRIJAYA KABUPATEN BOYOLALI Rosiana Al Hakim; Hari Purwanto; Zohaib Hassan Sain; Listyowati Puji Rahayu; Unna Ria Safitri
EKOBIS Vol 14 No 1 (2026): JURNAL EKOBIS
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/ekobis.v14i1.1470

Tujuan penelitian ini untuk menganalisa pengaruh beban kerja, lingkungan kerja, dan kompensasi terhadap kinerja karyawan pada PT. Primayudha Mandirijaya Kabupaten Boyolali baik secara persial maupun secara simultan dengan menggunakan metode kuantitatif melalui teknik pengumpulan data dengan kuesioner 100 responden karyawan PT. Primayudha Mandirijaya Kabupaten Boyolali. Alat analisis yang digunakan adalah beberapa uji statistik, uji t, uji F, koefisien determinasi R2 dan analisis linier berganda. Dari hasil penelitian ini menunjukkan bahwa variabel beban kerja, lingkungan kerja secara persial tidak berpengaruh terhadap kinerja karyawan, dan untuk variabel kompensasi berpengaruh secara persial terhadap kinerja karyawan serta secara simultan beban kerja, lingkungan kerja, dan kompensasi berpengaruh terhadap kinerja karyawan pada PT. Primayudha Mandirijaya Kabupaten Boyolali, sehingga total pengaruh ketiga variabel tersebut sebesar 20,3%.

PENGARUH KOMITMEN, DISIPLIN KERJA, DAN BUDAYA KERJA TERHADAP KINERJA ANGGOTA KPPS PADA PPS DESA PENGGUNG KECAMATAN BOYOLALI KABUPATEN BOYOLALI PEMILU 2024 Latiful A'la; Hari Purwanto; Alean Kistiani Hegy Suryana; Zohaib Hassan Sain; Unna Ria Safitri
EKOBIS Vol 13 No 2 (2025): Jurnal Ekobis
Publisher : Universitas Boyolali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36596/ekobis.v13i2.1539

Tujuan dari penelitian ini untuk mengetahui pengaruh komitmen, disiplin kerja, dan budaya kerja terhadap kinerja anggota KPPS pada PPS Desa Penggung Kecamatan Boyolali Kabupaten Boyolali PEMILU 2024. penelitian ini menggunakan penelitian deskriptif dengan pendekatan kuantitaif, populasi dalam penelitian ini adalah anggota KPPS Desa Penggung pada PEMILU tahun 2024, diambil secara purposive sampling diperoleh sampel sebanyak 63 orang. Teknik pengumpulan data penelitian menggunakan kuesioner. menggunakan analisis regresi liner berganda, uji asumsi klasik dan uji hipotesis. Hasil penelitian menunjukkan bahwa disiplin kerja dan budaya kerja berpengaruh secara signifikan teerhadap Kinerja anggota KPPS desa Penggung pada pemilu tahun 2024 yang ditunjukkan dengan nilai signifikansi (p value) < 0,05, sedangkan komitmen tidak berpengaruh secara signifikan terhadap kinerja anggota KPPS Desa Penggung pada pemilu tahun 2024 yang ditunjukkan dengan nilai signifikansi (p value) > 0,05. komitmen, disiplin kerja, dan budaya kerja secara bersama-sama mempengaruhi kinerja sebesar 72% dan selebihnya sebesar 28% dipengaruhi faktor lain diluar model penelitian ini.

Text mining and semantic modeling of literary corpora: a machine learning–based study of Indonesian fiction Rinda Widya Ikomah; Zohaib Hassan Sain
Lingua Technica: Journal of Digital Literary Studies Vol. 2 No. 1 (2026): Literature and computation: Mapping, modeling, and mediation
Publisher : Asosiasi Relawan dan Pengelola Jurnal LPTNU (ARJUNU)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64595/lingtech.v2i1.133

Background: The large-scale digitization of Indonesian literary works has produced extensive textual corpora that challenge conventional close-reading approaches and call for systematic, data-driven methods capable of capturing thematic, semantic, and affective patterns in fiction. Objective: This study aims to examine how text mining and semantic modeling can reveal lexical salience, intertextual relations, and narrative emotion in Indonesian fiction across different thematic orientations. Method: Using a quantitative corpus-based design, the study analyzes 36 Indonesian literary texts published between 1980 and 2022 through TF–IDF–based lexical analysis, document-level semantic embeddings with cosine similarity and clustering, and sentence-level sentiment analysis. Results: The findings show distinct lexical signatures that differentiate thematic clusters, coherent semantic groupings reflecting intertextual proximity, and sentiment trajectories dominated by neutral-to-negative polarity with strategically placed affective peaks across narrative progression. Implication: These results demonstrate that computational methods can empirically support literary analysis without displacing interpretive criticism. Novelty: The study integrates lexical, semantic, and affective modeling within a unified framework for Indonesian fiction, offering a scalable and replicable approach to digital literary studies.

Organizational Justice as a Key Driver of Organizational Citizenship Behavior in the Banking Industry Fauzan Muttaqien; Zohaib Hassan Sain
Business and Applied Management Journal Vol. 4 No. 1 (2026)
Publisher : Al-Qalam Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61987/bamj.v4i1.2073

This study examines the effects of distributive, procedural, and interactional justice on organizational citizenship behavior (OCB), with workplace spirituality serving as a mediating variable within the banking sector. The research is based on how multidimensional organizational justice influences OCB through workplace spirituality especially in highly structured and performance-oriented industries such as banking. This study employed a quantitative research approach involving 126 banking employees in East Java, Indonesia. Data were collected using a structured questionnaire distributed through a convenience sampling technique and analyzed using SEM-PLS with SmartPLS 4.0. The findings indicate that distributive justice significantly affects OCB (β = 0.255; p < 0.05) and workplace spirituality (β = 0.285; p < 0.05). In contrast, procedural justice (β = 0.096; p > 0.05) and interactional justice (β = 0.073; p > 0.05) do not demonstrate significant direct effects on OCB. However, procedural justice (β = 0.334; p < 0.05) and interactional justice (β = 0.337; p < 0.05) significantly influence workplace spirituality, while workplace spirituality significantly enhances OCB (β = 0.642; p < 0.001). Workplace spirituality significantly mediates the relationships between distributive justice, procedural justice, interactional justice, and OCB. The findings contribute to the organizational justice literature by demonstrating that workplace spirituality serves as an important psychological mechanism through which perceptions of justice translate into positive discretionary behavior among banking employees.

Exploring the Impact of Chat GPT on Higher Education: Advantages, Hurdles, and Prospective Research Avenues Zohaib Hassan Sain; Victa Sari Dwi Kurniati
TAMANSISWA INTERNATIONAL JOURNAL IN EDUCATION AND SCIENCE Vol 5 No 1 (2023): October 2023
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/tijes.v5i1.16274

This article explores the potential advantages and obstacles associated with the utilization of the generative AI model, Chat GPT, within the realm of higher education, considering the constructivist theory of learning. In this analytical study, five positive aspects of Chat GPT are discussed, including its capacity to facilitate adaptive learning, offer personalized feedback, support research and data analysis, provide automated administrative services, and contribute to the creation of innovative assessments. Conversely, the article highlights five challenges, such as concerns about academic integrity, issues related to reliability, the difficulty in evaluating and reinforcing graduate skill sets, limitations in assessing learning outcomes, and the potential presence of biases and falsified information in information processing. The argument presented emphasizes the need for caution among tertiary educators and students when employing Chat GPT for academic purposes to ensure its ethical, dependable, and efficient use. To address these concerns, the article puts forth several recommendations, such as prioritizing education on the responsible and ethical use of Chat GPT, devising new assessment strategies, tackling bias and falsified information, and integrating AI literacy into graduate skills. By carefully considering both the potential benefits and challenges, the integration of Chat GPT has the potential to enhance the overall learning experiences of students in higher education.

Niki's Moonchild Album: A Study of Figurative Language Adhi Kusuma; Verisa Rania Nurfitri; Ima Widyastuti; Victa Sari Dwi Kurniati; Zohaib Hassan Sain
TAMANSISWA INTERNATIONAL JOURNAL IN EDUCATION AND SCIENCE Vol 5 No 2 (2024): April 2024
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/tijes.v5i2.16340

The study aims to identify the specific types of figurative language employed in Niki's chosen songs, as well as the most prevalent types of figurative language observed in those songs. The researchers utilized a descriptive qualitative research methodology to examine and analyze the song lyrics. This research focuses on analyzing the selected song lyrics from Niki's Moonchild album. Through this investigation, various forms of figurative language have been recognized within the context of Kennedy, X.J. and Gioia, D.'s theory. The following are examples of figurative language: personification, metaphor, simile, hyperbole, synecdoche, irony, contradiction, repetition, apostrophe, and allegory. Furthermore, it unveiled the prevailing form of metaphorical language that was employed universally. The lyrics chosen from Niki's Moonchild album employ metaphors extensively, representing the most often recognized type.

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