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Jurnal Ilmiah Ilmu Terapan Universitas Jambi
Published by Universitas Jambi
ISSN : 25802240     EISSN : 25802259     DOI : https://doi.org/10.22437/jiituj.v6i2
Core Subject : Education, Engineering,
Education Engineering Industrial & Manufacturing Engineering
JIITUJ publish the result of research on applied science and education (Research of applied science and education) such as: the research result on applied science and education such as curriculum development and learning, character education, technology and instructional innovation, and learning evaluation. the research result on applied science and technology such as the development of applied technology and applied arts, appropriate technology, designing information systems, the research result on applied science and economic development the research result on applied science and public health. JIITUJ is a double-blind peer-reviewed journal, published three (3) times a year by Research Institutions and Community Service (LPPM), Universitas Jambi, Indonesia. JIITUJ is open to academic circles and university researchers, research institutes, librarians, graduate and postgraduate students to share information on research results.
Arjuna Subject : Kimia(semua kategori) - Kimia (Lain-Lain)
Articles 340 Documents
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EARLY DETECTION OF ACADEMIC DEPRESSION USING SMARTPHONE-BASED MACHINE LEARNING MODELS Edi Surya Negara; Latius Hermawan; Hastari Mayrita; Desy Arisandy; Mohamad Farozi; Rahmat Ramadan; Sunda Ariana; Ria Andryani
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.46375

Abstract

Mental health in developing countries is a common and complex problem. The problem continues to increase and is closely related to low self-confidence, negative interpersonal relationships, and academic depression. This can affect students' ability to complete academic assignments on a university scale. An AI-based early detection application can potentially improve mental health services related to treatment access. This system can help identify users who may be depressed based on the language used, especially for those who are reluctant to seek professional solutions due to the negative stigma of mental health. This study uses a qualitative descriptive method involving observation, in-depth analysis of group conversations, and early detection of academic depression by identifying conversation patterns between students and counselors as the basis for developing a smartphone-based application. This study produced a dataset of 395 depression-level data entries used as training data to develop a machine-learning model. A prototype of an academic depression detection application has been developed as a mobile-based application.
DEVELOPMENT OF A DEEP LEARNING MODEL: CONTEXTUAL STRATEGIES FOR IMPROVING THE PROFILE OF PANCASILA HIGH SCHOOL STUDENTS Samsul Bahri; Sutikno; Wan Nor Jazmina Wan Arifin; Hadi Widodo
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.46608

Abstract

A deep learning-based learning model was developed to enhance students' reflective and contextual understanding of learning materials while internalizing the values of the Pancasila Student Profile. This study aimed to create a contextual learning model for high school students in science class, employing a quasi-experimental design with a non-equivalent control group. Data were collected via questionnaires and analyzed using descriptive statistics and inferential tests, including the Independent Samples t-Test and Paired Samples t-Test, to evaluate the model's effectiveness in improving student learning outcomes. The results revealed a significant difference in the experimental group, as the Paired Samples t-Test indicated a notable difference between the pre-test score (68.47) and the post-test score (83.20), with a t-value of -9.127 and p = 0.000 (p < 0.05). Additionally, the Independent Samples t-Test demonstrated that the average post-test score of the experimental group (83.20) was significantly higher than that of the control group (74.13), with a t-value of 4.213 and p = 0.000 (p < 0.05). These findings indicate that the local wisdom-based model effectively improves student learning outcomes compared to the conventional approach. This study highlights the importance of implementing an immersive learning model in high schools, emphasizing contextual strategies that engage students in critical and reflective thinking to internalize the values of the Pancasila Student Proficiency Profile. However, the limitations of this model, such as time and space constraints, suggest the need for further longitudinal research across various educational settings to comprehensively evaluate its effectiveness and adaptability.
UTILIZING INTERACTIVE ARTIFICIAL INTELLIGENCE IN ENGLISH LANGUAGE AND SCIENCE IN SELECT SOUTHEAST ASIAN CLASSROOMS Joseph A Villarama; Lyan Mae Micah V Dela Cruz; Karen Jean Barcelita; Irma Fitriani; Somsak Techakosit
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.40293

Abstract

The proliferation of interactive artificial intelligence (AI) in the academic sphere maneuvers the steering of teaching and learning processes, which transfigures the roles of teachers and learners today. This study explored the perspectives and experiences of teachers and students in select Southeast Asian countries on the challenges and opportunities they faced in utilizing interactive AI. A qualitative narrative research approach was employed, following a series of scheduled semi-structured hybrid interviews, using a set of 10 content-validated interview guide questions, with 60 participants chosen through a non-probability sampling technique. After a rigorous thematic-narrative analysis, findings revealed capitalizing on the essential presence of interactive AI in education; however, there is a strong drive to establish clear policy guidelines that address ethical and fair access to AI in classrooms. Further, interactive AI customized learning and managed teachers’ workloads; nevertheless, both should balance the utilization of interactive AI in their work. In view of equitable and inclusive education, ensuring equity in personalized learning with the use of interactive AI must be fostered. Conversely, problems included unequal access, ethical issues, and over-reliance on technology—all of which call for thoughtful planning and policy-making. Unless carefully implemented, interactive AI risks exacerbating existing inequities or undermining human contacts that lie at the heart of quality teaching and learning. This study underlines the need to blend the strengths of interactive AI with the irrepressible value of teacher-student interaction and tradition-based approaches. By promoting equity, transparency, and collaboration, interactive AI complements, but does not replace, the significant role of educators.
TEACHERS’ VOICES ON THE DEVELOPMENT OF STUDENTS’ NATIONAL IDENTITY THROUGH THE EMBEDDING OF LOCAL CULTURE Ella Masita; Marzul Hidayat; Fortunasari Fortunasari
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.43544

Abstract

This paper investigates how Indonesian English language and science teachers in Jambi municipality perceive the relationship between national identity and local culture in English and Science teaching. Through thematic analysis, the study explores teachers’ understanding toward the role of national identity in English and Science teaching as well as the challenges and strategies teachers encounter in integrating national identity into their teaching practices by the inclusion of local culture, emphasizing the importance of Jambi cultural context in the teaching. The research results reveal a number of findings such as teachers’ beliefs that exploring national identity in the classroom can help students develop a sense of belonging and awareness of their place in a multicultural world. However, they express varying degrees of emphasis on national identity, with some advocating for a bigger portion of context of local culture, while others may prioritize students’ development of English mastery no matter what culture is embedded. Teachers also report challenges and strategies employed, for instance the conduction of collaborative learning to help students learn from each other’s perspectives, designing inclusive teaching materials to include diverse perspectives of national identity, and enhancing teachers’ understanding of cultural sensitivity and identity issues. To conclude, it is recommended to build adequate support for a balanced English and Science teaching designs that respect and celebrate national identity while, at the same time, be able to prepare students for global engagement. By fostering the integration of local and global perspectives, English and Science education in Indonesia will be able to create English and Science teaching environment that empowers students as both national and global citizens.
STUDENT CONTRIBUTION INDEX (SCI) IN SCIENCE: A MEASURE OF CONTRIBUTION TO MITIGATING SOCIAL LOAFING AND FREE-RIDING IN TEAM PROJECTS Burhanuddin Yasin; Omar K Burhan; Faisal Mustafa; Ika Apriani Fata; Endang Komariah
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 3 (2025): Volume 9, Nomor 3, September 2025
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v9i3.42064

Abstract

In this study, we introduce the Student Contribution Index (SCI) to measure these contributions. The purpose of this quantitative study is to test the validity of SCI as a measure of task identifiability and to determine the student satisfaction with SCI-based assessments. To collect the data, 52 students were split into high and low identifiability conditions. Both groups worked on a project and completed SCI once (LI group) and twice (HI group). We measured the SCI variability using an F-test at the significance level of 0.05. Furthermore, a group project of 113 students was assessed using SCI. Students completed an evaluation form to measure procedural fairness, distributive fairness, and satisfaction. We then analyzed the correlations between these variables using Pearson's Correlation. The results show that the variability in SCI of the HI group was negligible (SD = 0), indicating that all students contributed equally to the project. Meanwhile, a variability was observed in the LI condition (SD = 0.08), suggesting that SCI was a valid measurement. Additionally, students were generally satisfied with the assessment (M = 4.40), and a significant correlation was observed between the variables. This study presents a novel method for assigning grades to group members in group projects, taking into account each member’s individual contribution. As a result, fairness in grading can be achieved, and educators can discourage social loafing and free-reading behavior.
EFFECTS OF DIGITAL PROGRAMS ON THE LEVEL OF FORMATION OF DIGITAL SKILLS OF THE STUDENTS Baitasheva, Gaukhar; Mussina, Aitzhamal; Medeuova, Galiya; Umbettulla, Ayaulym; Zhamanbayeva, Karlygash
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 4 (2025): Volume 9, Nomor 4, December 2025
Publisher : LPPM Universitas Jambi

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Abstract

Global changes in information, communication, professional, and other spheres of modern society necessitate several adjustments in educational practices. In preparing integrated tasks, students are taught to apply knowledge from various subjects to solve specific problems. One of the most important conditions for enhancing the effectiveness of the educational process is the development of students’ research and digital skills, which in turn fosters their creative and logical thinking abilities. This study employed a quasi-experimental research design. The sample consisted of 46 second-year chemistry-biology students (23 in each group) from the Kazakh National Women’s Teacher Training University during the second semester of the 2022-2023 academic year. The experimental and control groups were randomly selected. Key findings include a 7.7% improvement in digital skills among the experimental group compared to the control group (a high level of 48.3% in the experimental group, compared to 40.6% in the control group). The verification of integrated tasks indicates that digital skills involve understanding the purpose, conditions, and means of action. These skills are aimed at researching and clarifying specific processes, facts, and phenomena, while effectively utilizing knowledge and life experience. This research contributes novel insights by demonstrating how integrated tasks enhance digital competency within a chemistry-biology curriculum. The findings suggest that incorporating such methodologies into educational frameworks can bridge the gap between theoretical knowledge and practical application, ultimately improving students' readiness for the digital economy and research-oriented careers.
THE POTENTIAL OF LOCAL BRANDING IN THE ECONOMIC PERFORMANCE OF AGRO-PROCESSING INDUSTRIES AND AGROTOURISM IN VLORA, ALBANIA Polaj, Edvina; Kadiu, Edmond; Pepkolaj, Lekë
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 4 (2025): Volume 9, Nomor 4, December 2025
Publisher : LPPM Universitas Jambi

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Abstract

This study investigates the influence of branding on the economic performance of agricultural-livestock agro-processing industries and agrotourism enterprises in the Vlora region, emphasizing two performance indicators: Performance 1 (revenue growth) and Performance 2 (financial improvement). The research aims to verify the relationship between the agro-processing sector and the development of agritourism by analyzing how branding and the marketing of locally indicated products enhance economic outcomes. Data were collected from over 100 agro-processing industries and agrotourism businesses and analyzed using the STATA software. The findings reveal that branding has a significant positive effect on financial performance, with revenue increasing from 1,111 to 2,593 after implementing branding strategies. Furthermore, the marketing of branded products is linked to a notable rise in tourist numbers—an average of 2,815 compared to 2,640 in non-branded businesses—demonstrating that brand identity strengthens the competitiveness and attractiveness of agrotourism destinations. The novelty of this study lies in its integration of branding analysis within the dual framework of agro-processing and agritourism, highlighting branding as both an economic and cultural lever for rural development. Unlike previous studies that examined these sectors separately, this research provides empirical evidence of branding’s role as a bridge between local product identity and sustainable tourism growth. These results underscore the strategic importance of investing in brand development to enhance rural economic resilience, promote value-added agricultural products, and stimulate regional economic development through the synergy of agriculture, industry, and tourism.
ASSESSING THE IMPACT OF EU INTEGRATION ON ECONOMIC GROWTH FORECASTS USING ARTIFICIAL NEURAL NETWORK MODELS Caushi, Andi
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 4 (2025): Volume 9, Nomor 4, December 2025
Publisher : LPPM Universitas Jambi

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Abstract

This study investigates the interplay of endogenous and exogenous factors influencing GDP growth in Albania and Serbia, two nations at different stages of EU integration. Key variables examined include consumption, education, exports, foreign direct investment (FDI), imports, savings (all relative to GDP), and urbanization rates, with a focus on the impact of high-technology exports. To analyze the World Bank dataset from 1993 to 2023 at a 95% confidence level, this study employs an Artificial Neural Network-Multilayer Perceptron Model (ANN-MLP), designated as H (1;1). The dataset is systematically divided into two subsets: the first subset comprises 70% of the observations, while the second subset contains the remaining 30%. The initial subset is utilized to optimize forecasting accuracy, allowing the model to adjust its parameters accordingly. Once the parameters have been optimized, they are applied to the second subset to assess the model's performance. This procedure yields a forecast error of less than 0.3%, demonstrating the model's efficacy. The novelty of this study lies in forecasting GDP growth in Albania and Serbia using ANN-MLP models, with a particular focus on the role of high-technology exports. It emphasizes the distinct importance of exports in Albania versus consumption and FDI in Serbia, offering nuanced insights into country-specific growth mechanisms. This tailored, context-sensitive approach provides valuable implications for policymakers aiming for EU integration, filling a gap in existing literature by explicitly contrasting the economic drivers in these neighboring, yet economically distinct, national contexts.
THE IMPACT OF DISTANCE ON WILLINGNESS TO EAT OUT: EVIDENCE FROM SAMARKAND, UZBEKISTAN Makhmadieva, Charos; Turdibekov, Khasan; Amiriddinova, Muslima; Toyirova, Shokhista; Yuldosheva, Latofat; Mahmudova, Zarrina; Abdukhamidov, Sarvar; Makhmudova, Aziza; Rofeeva, Rukhshona; Vafokulova, Mekhruza; Bakri, Rizal; Sobirov, Bobur
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 4 (2025): Volume 9, Nomor 4, December 2025
Publisher : LPPM Universitas Jambi

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Abstract

This study investigates the determinants influencing participation in gastronomic tourism in Samarkand, Uzbekistan, focusing on the role of distance, price satisfaction, and demographic characteristics. Using data collected from 303 respondents, logistic regression and decision tree analyses were applied to assess key behavioral predictors of culinary travel. The results reveal that distance is the most significant factor influencing willingness to engage in gastronomic tourism—individuals willing to travel farther are substantially more likely to seek authentic food experiences. In contrast, satisfaction with food prices and demographic factors such as age, gender, and expenditure levels were found to be statistically insignificant. These findings highlight that logistical accessibility outweighs demographic variables in shaping tourism participation. The study contributes to the literature by providing empirical evidence from an emerging destination, emphasizing the importance of mobility and access in gastronomic decision-making. Practical implications include the need for policymakers to improve transportation infrastructure, enhance culinary destination visibility, and promote authentic local food experiences. By strengthening these elements, Uzbekistan can better position itself as a prominent culinary tourism destination in Central Asia. The research also opens opportunities for future studies to explore psychological, cultural, and digital factors influencing food tourism behavior.
ASYMMETRIC EFFECTS OF EXCHANGE RATE VOLATILITY ON TRADE AND INVESTMENT: A NONLINEAR APPROACH Amraoui, Karima; Harrak, Soukaina Alami; El-Khodary, Mohammed
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 9 No. 4 (2025): Volume 9, Nomor 4, December 2025
Publisher : LPPM Universitas Jambi

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Abstract

Exchange rate movements play a central role in shaping external competitiveness, yet their effects are rarely symmetric and are often underestimated in studies that rely on linear models. This article examines how real effective exchange rate (REER) appreciations and depreciations influence the external sector in Morocco, focusing on foreign direct investment (FDI), exports, and imports over 1988–2023. Annual data from the World Development Indicators are analyzed using a Nonlinear Autoregressive Distributed Lag (NARDL) model, which decomposes REER into appreciation and depreciation components. Cointegration is assessed through bounds testing, while Wald statistics evaluate the presence of short- and long-run asymmetries. The results show that appreciations have sharper and more immediate impacts than depreciations across all channels. In the short run, appreciation reduces FDI and exports while boosting imports, though some of these effects are later corrected. Depreciation produces weaker and delayed responses, reflecting the economy’s dependence on imported inputs for exports and essential goods. Over the long run, imports display significant asymmetry, exports respond largely symmetrically, and FDI reveals a delayed rebound after appreciation, highlighting the credibility effect of currency stability. The novelty of this study lies in combining a long horizon with a nonlinear approach rarely applied to Morocco, uncovering dynamics overlooked by linear models, most notably the rebound of FDI and exports following appreciation and the structural rigidity of imports. These findings suggest that sustaining competitiveness requires more than exchange rate management; export diversification, financial deepening, and industrial upgrading are crucial to mitigating appreciation shocks and enhancing resilience.

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