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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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DATA ANALYSIS AND MACHINE LEARNING APPLICATIONS IN ENVIRONMENTAL MANAGEMENT Majeed, Dilovan Asaad; Ahmad, Hawar Bahzad; Hani, Ahmed Alaa; Zeebaree, Subhi R. M.; Abdulrahman, Saman Mohammed; Asaad, Renas Rajab; Sallow, Amira Bibo
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 2 (2024): Volume 8, Nomor 2, December 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i2.32769

Abstract

The rapid expansion of data on air contaminants and climate change, particularly concerning public health, presents both opportunities and challenges for traditional epidemiological methods. This study aims to address these challenges by exploring advanced data collection, pattern identification, and predictive modeling techniques in the context of air pollution research. The focus is leveraging data mining and computational methods to enhance the understanding of air pollution's impact on public health, specifically ozone exposure. A comprehensive review of the scientific literature was conducted, utilizing databases such as Professor, Scholar, Embl, and Nih to identify relevant studies on air pollution epidemiology. The review highlights the integration of data mining, machine learning, and spatiotemporal modeling to improve the detection, analysis, and forecasting of air pollution-related health issues. The findings reveal a growing trend in applying data mining techniques within the field of air pollution epidemiology. Advanced methods, such as spatiotemporal analysis and geographic data mining, enable more precise tracking and forecasting of pollution-related health risks. Continuous advancements in artificial intelligence and the development of more sophisticated sensors and data storage technologies are enhancing the accuracy and reliability of air quality monitoring and public health predictions. This study highlights the transformative potential of integrating data mining and AI techniques into air pollution epidemiology. Exploring emerging technologies like spatiotemporal mining and next-generation sensors paves the way for more accurate, timely, and scalable solutions to monitor air quality and predict its impact on public health, opening new avenues for research and policy interventions.
COMPARATIVE ANALYSIS OF STATE-OF-THE-ART CLASSIFIERS FOR PARKINSON'S DISEASE DIAGNOSIS Hani, Ahmed Alaa; Sallow, Amira Bibo; Ahmad, Hawar Bahzad; Abdulrahman, Saman Mohammed; Asaad, Renas Rajab; Zeebaree, Subhi R. M.; Majeed, Dilovan Asaad
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 2 (2024): Volume 8, Nomor 2, December 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i2.32771

Abstract

Parkinson's disease (PD) presents a growing global health challenge, with early detection being crucial for effective management and treatment. This study seeks to develop an innovative machine learning (ML) framework for the early detection of PD by integrating advanced techniques for data preprocessing, dimensionality reduction, feature selection, and ensemble classification, aiming to significantly improve detection accuracy and timeliness. The research employs a robust ML pipeline, beginning with data preprocessing using mean imputation, standardization, min-max scaling, and SMOTE (Synthetic Minority Over-sampling Technique) to handle imbalanced data. Dimensionality reduction is achieved through Principal Component Analysis (PCA), while feature selection is performed using SelectKBest coupled with the ANOVA F-test to identify the most relevant features. Four ensemble methods—Random Forest, Gradient Boosting, XGBoost, and Support Vector Machine (SVM)—are evaluated for classification. Among the classifiers tested, the Gradient Boosting model stands out with an impressive accuracy of 0.9487, demonstrating its superior performance in PD detection. Integrating multiple preprocessing, dimensionality reduction, and feature selection techniques proves essential in optimizing model performance, highlighting the importance of a multifaceted approach in handling complex datasets. This research introduces a comprehensive ML framework that combines multiple advanced techniques in a streamlined process, significantly improving the early detection of Parkinson's disease. Ensemble methods, combined with strategic feature selection and data balancing techniques, offer a novel approach that could be applied to other neurodegenerative disorders, expanding its potential impact beyond PD detection.
SENSORLESS SPEED ESTIMATION OF THREE PHASE INDUCTION MOTORS BASED ON DYNAMIC MODEL Pjetri, Alfred; Bardhi, Astrit; Dume, Gentian
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 2 (2024): Volume 8, Nomor 2, December 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i2.32862

Abstract

In speed control systems of induction motor electrical drives, real-time speed monitoring is necessary. Speed monitoring can be done using the direct method, which uses a mechanical sensor mounted on the motor shaft, or the indirect method, which is based on estimation, mainly from the dynamic model of the motor. Speed estimation based on the dynamic model of the motor in orthogonal coordinates is the most widespread method in sensorless speed control systems of three-phase squirrel cage induction motor electrical drives, especially those of high accuracy. This paper presents the open-loop speed estimator used for speed estimation in three-phase induction motors. The proposed speed estimators are based on the orthogonal coordinate’s dynamic model of an induction motor in a stator reference frame. This technical solution is simple and has a low cost. The currents and voltages of the two motor phases are the input variables of the estimator, while the output variable is the induction motor speed. The speed estimator model is built using LabVIEW software. The dynamics and accuracy of the estimator proposed in this paper have been tested experimentally. The speed measured by the industrial incremental encoder is compared with that of a speed estimator modeled in LabVIEW software. The obtained experimental results show a good match between the measured and estimated speeds under the step torque load changes of the induction motor.
EXPLORING THE IMPACT OF AGE AND MOTIVATION ON SELF-DETERMINATION: INSIGHTS FROM INFORMAL SECTOR MOTHERS Heriberta, Heriberta; Zulfanetti, Zulfanetti; Setiawati, Rike
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 1 (2024): Volume 8, Nomor 1, June 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i1.32880

Abstract

This groundbreaking research explores the intricate interplay between age factors, motivation to work, and the self-determination of mothers engaged in the informal employment sector, a demographic often overlooked in scholarly investigations. Employing a mixed-method approach characterized by a sequential exploratory design, this study pioneers a comprehensive examination of the multifaceted dynamics shaping maternal self-determination. Leveraging purposive sampling, data collection unfolds through a meticulously orchestrated blend of orally administered questionnaires and in-depth interviews, ensuring a holistic understanding of the subject matter. Analytically, the research employs a dual-pronged strategy encompassing descriptive and inferential statistical analyses, complemented by Miles & Huberman's framework for interview analysis. The study unveils a significant nexus between age, motivation, and maternal self-determination through rigorous statistical scrutiny, filling a conspicuous void in extant literature. This research's novelty lies in its explicit focus on delineating the intricate correlations and synergies between age and motivation factors vis-a-vis self-determination, particularly within the context of working mothers operating within informal economies, an underexplored realm in academic discourse. The implications of this study reverberate far beyond academia, offering tangible insights that can inform the development of targeted support programs tailored to empower and uplift mothers navigating the informal employment sector. Ultimately, this research represents a pioneering stride towards fostering a more inclusive and equitable ecosystem for working mothers, underpinned by a nuanced understanding of their unique challenges and aspirations.
A SYSTEMATIC REVIEW OF INDONESIAN HIGHER EDUCATION STUDENTS' AND GRADUATES' WORK READINESS Nugroho, Novianto Eko; Irianto, Jusuf; Suryanto, Suryanto
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 1 (2024): Volume 8, Nomor 1, June 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i1.33073

Abstract

This literature review aims to determine the work readiness of undergraduate graduates to meet the qualifications required by employers in the world of work. The method used in this paper involved searching for all studies that examined work readiness and were published from 2019 to 2023. 5 out of 200 studies found on Google Scholar and Scopus were included in this review. Research findings show that programs in higher education, including internships and soft skills training, play an important role in increasing graduates' work readiness, demonstrating that the MBKM Program has effectively developed the skills and competencies required by the world of work. Research discussions highlight that these programs, including internships and soft skills training within the MBKM Program, are crucial for ensuring the relevance of education to job market needs. This research presents novelty by exploring and identifying the factors that influence the job readiness of prospective undergraduate graduates after participating in the Independent Campus Learning Program (MBKM), thus offering a new perspective in the context of higher education in Indonesia. The implications of this research are significant for curriculum development and learning programs in universities, which must continue to develop programs that support the development of soft skills and hard skills to increase graduates' work readiness.
HONEY PUMPKIN STEM BORER, Apomecyna saltator FABRICIUS (COLEOPTERA: CERAMBYCIDAE) CAN BE CONTROLLED WITH PHOSPHORUS AND POTASSIUM FERTILIZER Wilyus, Wilyus; Nurdiansyah, Fuad; Irianto, Irianto; Asniwita, Asniwita; Oktavia, Sella
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 2 (2024): Volume 8, Nomor 2, December 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i2.33717

Abstract

Apomecyna saltator, a notorious pest of honey pumpkin plants, poses a significant threat to both vegetative and generative phases, leading to considerable production losses. Despite its agricultural impact, there are limited studies on effective management strategies for this pest. This research investigates the effect of combined phosphorus and potassium fertilization on controlling A. saltator infestations in honey pumpkin plants. The study was conducted at the Teaching and Research Farm of the Faculty of Agriculture, Jambi University. A randomized block design with five treatments and five replications was used, testing different combinations of SP-36 phosphorus and potassium chloride (KCl) fertilizers: no fertilization (p0), SP-36 0.67 g/plant + KCl 1.25 g/plant (p1), SP-36 1.00 g/plant + KCl 1.88 g/plant (p2), SP-36 1.34 g/plant + KCl 2.51 g/plant (p3), and SP-36 1.67 g/plant + KCl 3.13 g/plant (p4). The variables observed included stem diameter, larval population, percentage of plant damage, number of attacked plant segments, fruit weight, and overall production. Data were analyzed using ANOVA and Duncan's Multiple Range Test (DMRT). The results indicated that combining phosphorus and potassium fertilizers significantly increased stem diameter, fruit weight, and yield while reducing larval populations, plant damage, and affected segments. The study demonstrates that phosphorus and potassium strengthen honey pumpkin plants and negatively impact A. saltator infestations. This research highlights a novel approach to pest control, showing that targeted fertilization promotes plant health and suppresses the honey pumpkin stem borer (A. saltator). This dual benefit of nutrient application provides a sustainable and efficient pest management strategy, offering a fresh perspective on integrated crop protection.
BREADFRUIT PEEL AS THE MOST POTENT RADICAL SCAVENGERS FOR SKIN PROTECTION Syamsurizal Syamsurizal; Elisma Elisma; Puspa Dwi Pratiwi
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 1 (2024): Volume 8, Nomor 1, June 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i1.33966

Abstract

The sun's ultraviolet radiation causes erythema, premature aging, sunburn, hyperpigmentation, inflammation, and dry skin. For this purpose, sunscreen with an SPF value of over 15 is needed to protect the skin against UV rays. Breadfruit peel containing flavonoids may protect against free radicals and UV radiation. This study aims to increase SPF value from breadfruit fractionate by combining niacinamide and alpha-tocopherol. The ABTS and BSLT methods were used to screen potent free radical scavengers in n-hexane, dichloromethane, ethyl acetate, and methanol extracts. The dichloromethane extract had the highest potential as a free radical scavenger, with IC50 20,90 more or less 0,54, and the lowest toxicity, with LC50 234,42 more or less 1,06. Then, the scavenging activities and selective index of fractionates of dichloromethane were evaluated to show that the DM2 fraction had the strongest free radical scavenging activity and the lowest toxicity, with the highest selective index value of 46.08. The main active ingredient was DM2, combined with niacinamide and alpha-tocopherol into five compositions. The results of the lotion dosage forms revealed that the fifth formula, F5, met the requirement SNI standards and was stable during storage, with an SPF value of 20.61 more or less than 0.75, which was three times higher than the positive control with an SPF value of 6.67 more or less 1.28.
ENHANCING COMPETITIVENESS OF PERUVIAN TEXTILE MSES THROUGH QUALITY MANAGEMENT: A FOCUS ON LEADERSHIP, TRAINING, AND CONTINUOUS IMPROVEMENT Munive, Marco Antonio Ledesma
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 2 (2024): Volume 8, Nomor 2, December 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i2.33967

Abstract

This study examines the impact of quality management on the competitiveness of micro and small enterprises (MSEs) in the Peruvian textile clusters, a sector that is a significant driver of local economic activity. Unlike previous studies, this research provides a comprehensive analysis of the combined influence of leadership, employee training, customer orientation, continuous improvement, and benchmarking on MSE competitiveness. Utilizing a robust quantitative research design, data were collected from 347 participants through a structured survey. The findings reveal a high level of engagement in quality management practices among the surveyed MSEs, with the identified factors significantly contributing to improved productivity, customer satisfaction, and market presence. The originality of this study lies in its in-depth exploration of these quality management dimensions within the specific context of Peruvian textile clusters, offering new insights into their role in driving competitiveness. The implications are particularly relevant for business owners, managers, and policymakers seeking to enhance the sustainability and competitive advantage of textile MSEs in a highly dynamic market environment.
QUALITY OF LIFE: THE SPIRITUALITY AND SPIRITUAL WELLBEING OF ELDERLIES IN MALAYSIA Yahya, Fatimah Binti; Hassan, Hafizah Che; Panduragan, Santhna Letchmi; Mat, Samsiah
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 2 (2024): Volume 8, Nomor 2, December 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i2.34273

Abstract

With an increasing aging population worldwide, there is a need for greater focus on the spirituality of older people, to better support them and lead them to an enhancement of their inner peace. This study used a qualitative with exploratory sequential design approach (with semi-structured interviews) in exploring spirituality with older people in community of Federal Territory of Kuala Lumpur, which is related to a sense of personal belief and connection that helped them in their daily lives. The research involved a rigorous exploratory process. The fifteen (15) participants provided information about their rich experiences and their connections in four domains: (1) Faith, (2) Belief, (3) Practice and (4) Emotion. Results: The reliability of the dimensions was all high as the Cronbach’s Alpha coefficients were above 0.90. Therefore, this spirituality measurement tool can be considered highly reliable. Conclusion: This paper has developed as well as validate the spirituality measurement tool. It was used to construct a profile of elderly in Malaysia, and it may be applied to profile elderly in other countries.
SELF-EFFICACY REDUCES RELAPSE IN DRUG ABUSE WITH COGNITIVE BEHAVIOUR THERAPY Susanti, Meri; Dania, Ira Aini; Ibarra, Florante
Jurnal Ilmiah Ilmu Terapan Universitas Jambi Vol. 8 No. 2 (2024): Volume 8, Nomor 2, December 2024
Publisher : LPPM Universitas Jambi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/jiituj.v8i2.34358

Abstract

Maladaptive substance abuse (NAPZA) can lead to clinically significant disorders. According to the National Narcotics Agency (BNN) states that around 90 percent of former drug addicts who undergo the rehabilitation process experience a relapse and return to abusing drugs. The research results show that cognitive Behaviour Therapy (CBT) is an effective intervention method in treating drug abuse. This research aims to test the effectiveness of cognitive behavior therapy to increase self-efficacy to reduce the risk of relapse in drug abusers. The study used a pre-posttest experimental method with a control group. Research respondents were selected using a purposive sampling technique with a sample size of 30 people. Both groups were given the Drug Abstinence Self-Efficacy Scale (DASES) measurement to see the effectiveness of applying cognitive behavior therapy in increasing self-efficacy in addicts who have participated in the rehabilitation program. The change in self-efficacy in both groups from medium to high was 66.7% after the intervention. A comparison between the two groups was made before the intervention, where the significance value was p = 0.399, and after the intervention, there was a change in the score between the two groups to 0.001. There was a significant difference between the two groups before and after the intervention, with a value of p = 0.001. Meanwhile, there was no substantial change in the control group in p=0.177. CBT is effective in increasing abstinence self-efficacy in drug addicts as an effective therapy to reduce the risk of relapse in drug addicts in rehabilitation programs

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