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International Journal of Research in Vocational Studies (IJRVOCAS)
Published by Yayasan Ghalih Pelopor Pendidikan
ISSN : 27770168     EISSN : 27770141     DOI : https://doi.org/10.53893/ijrvocas.v1i1
Core Subject : Economy, Science, Education, Social, Engineering,
Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other
The International Journal of Research in Vocational Studies (IJRVOCAS) is a double-blind peer-reviewed journal. This journal provides full open access to its content on the principle that making research freely and independently available to the science community and the public supports a greater global exchange of knowledge and the further development of expertise in the field of vocational education and training (VET). IJRVOCAS is since the beginning independent from any non-scientific third-party funding. The establishment of the journal was supported between 2015 and 2016 with grants from the Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation). All members of IJRVOCAS work on an honorary basis. The journal is hosted by Ghalih Publishing and the publishing house of the Ghalih Academic. Scope IJRVOCAS covers all topics of VET-related research from pre-vocational education (PVE), initial vocational education and training (IVET) and career and technical education (CTE) to workforce education (WE), human resource development (HRD), professional education and training (PET) and continuing vocational education and training (CVET).
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 8 Documents
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Search results for , issue "Vol. 4 No. 2 (2024): IJRVOCAS - August" : 8 Documents clear
Battery Analysis in Off Grid Solar Power Plant as A Power Source for AC Motor Automatic Coffee Roaster Machine Capacity 20 Kg Nurhaida; Susanti, Indah; Volta, Yonki Alexander; Muzakki, M Hafiz
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.258

Abstract

Solar power plants that utilize solar energy to be converted into electrical energy have several advantages compared to other power plants, namely that they do not produce air pollution, are available continuously and are available everywhere. Coffee is a commodity in the world that is cultivated in more than 50 countries. Two species of coffee trees that are generally known are Robusta Coffee and Arabica Coffee. Processing coffee before consumption goes through a long process, namely from harvesting coffee beans that are ready to harvest. Then proceed with drying before roasting. Coffee roasting machine that uses an AC motor. The motor gets a DC power source from a solar power plant then the inverter changes the DC voltage to AC. This coffee roasting machine is equipped with IoT to control the motor rotation remotely and monitor the temperature. The battery has the function of storing electrical energy produced by solar panels in the form of direct current energy. The energy stored in the battery functions as a backup, which is usually used when the solar panels do not produce electrical energy. The greater the capacity of the battery used, the longer the battery can back up the load used.
Synthesis and Characterization of Silicon Nanoparticles from Coal Fly Ash Using Ultrasonication as a Battery Anode Robiansyah; Bow, Yohandri; Dewi, Tresna
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.282

Abstract

Fly ash, a byproduct of coal combustion, is rich in silica, alumina, and other minerals, making it a valuable resource for extracting high-purity silicon. The synthesis of silicon nanoparticles from coal fly ash involves several critical steps, including the extraction of silica (SiO2) via the sol-gel method, reduction of silica to silicon using the metallothermic method, and subsequent ultrasonication to achieve nanoscale particles. Studies have shown that fly ash can contain up to 49.21% silica, which can be further purified to 93.52% via chemical extraction methods such as acid leaching and alkali dissolution. The reduction of silica to silicon is carried out using the metallothermic method, which involves the use of magnesium-reducing agents to convert SiO2 to elemental silicon. This process produces silicon with a purity of about 61.3%, which can be further increased through ultrasonication. Ultrasonication is a technique that uses high-frequency sound waves to break particles into smaller sizes, resulting in more uniform and homogeneous nanoparticles. In this study, ultrasonication for 60 and 120 min reduced the average particle size of silicon from 208.94 nm to 58.87 nm and 20.13 nm, respectively, and increased the silicon content to 74.6% and 72.7%. X-ray diffraction (XRD) and distribution particle analyses confirmed the particle size reduction and homogeneity of silicon nanoparticles, indicating the effectiveness of ultrasonication in producing high-quality silicon nanoparticles. The synthesized silicon nanoparticles have significant potential applications, particularly as anode materials in lithium-ion batteries, due to their increased surface area and improved electrochemical properties. Furthermore, the use of fly ash as a raw material for the synthesis of silicon nanoparticles not only provides a cost-effective and environmentally friendly alternative to traditional silica sources but also helps in reducing the environmental impact of fly ash disposal. The integration of the methods and findings of this study underscores the feasibility and benefits of using coal fly ash for the sustainable production of silicon nanoparticles, which can be utilized in energy storage as anode materials in lithium-ion batteries.
Generating Hydrogen Gas with a Polyvinyl Alcohol Membrane Dry Cell Electrolyzer Using KOH Electrolyte Rohman, Abdul; Rusdianasari; Syarif, Aida
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.291

Abstract

Global environmental concerns requiring excellent air quality have prompted the development of a variety of eco-friendly energy sources. Hydrogen gas is an environmentally friendly option that may be created using an electrolysis device that converts water into hydrogen (H2) and oxygen (O2). In this study, a dry cell electrolyzer with a polyvinyl alcohol (PVA) membrane was used as a separator between two stainless steel 316 electrodes to generate a high hydrogen yield. The hydrogen gas production from the dry cell electrolyzer was determined using gas chromatography. The results showed that using a KOH electrolyte and a PVA membrane considerably enhanced the hydrogen gas composition. Hydrogen gas compositions after electrolysis using a dry cell electrolyzer without a PVA membrane and KOH electrolyte concentrations of 0 M, 0.04 M, 0.07 M, and 0.11 M being 13.70%, 25.10%, 32.50%, and 15.60%, respectively. With a PVA membrane, the hydrogen compositions were 71.50%, 89.10%, 80.50%, and 84.60%, respectively. The results of these experiments show that the most hydrogen gas was produced utilizing a dry cell electrolyzer with a PVA membrane and a 0.04 M KOH electrolyte concentration. When a PVA membrane and a KOH electrolyte are utilized in electrolysis, the hydrogen gas composition improves significantly compared to when either is utilized.
Combine Improvement for Dye-Sensitized Solar Cells: Characterization of Metal Oxide-Doped TiO2 Nanoparticles Integrated with Clitoria Ternatea Extract Ronaldo; Rusdianasari; Hasan, Abu
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.292

Abstract

Dye Sensitized-Solar Cells (DSSC) represent a third-generation solar cell technology based on photoelectrochemical principles. This study explores the use of Clitoria ternatea (butterfly pea) extract as an organic dye for DSSCs, focusing on its ability to absorb sunlight effectively. Excitation of electrons triggered by light in photocatalysis is strongly influenced by the position of the band gap. To be effective as a photocatalyst, the material must have a conduction band with a high positive potential compared to the electron accepting potential. Doping metal oxides such as CuO, MgO, Fe2O3, and ZnO into TiO2 can change the band edge properties or surface states which can increase light absorption. This research presents the synthesis of TiO2 nanoparticles as photoanodes doped using metal oxides to evaluate characteristic that can influence DSSC performance. TiO2 nanoparticles doped with metal oxide were synthesized using the solvothermal method and characterized by XRD, SEM-EDX, FTIR, and UV-Vis. Comprehensive analysis of samples doped with metal oxides significantly affects the crystal structure, morphology, elemental composition, and optical properties of the material. The results showed that Cu-doped TiO2 samples allowed for the most significant performance improvement in DSSC, followed by Fe-doped TiO2, Mg-doped TiO2, and Zn-doped TiO2, with pure TiO2 having the lowest performance potential. These results provide important insights into material optimization to improve DSSC efficiency.
Customer Segmentation Using the K-means Clustering Algorithm and Recency Frequency Monetary Model at Pharmaceutical Product Wholesaler Iqbal, Nur Muhammad; Iskandar, Yelita Anggiane; Zulvia, Ferani Eva
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.293

Abstract

PT Kimia Farma Trading and Distribution (KFTD) is a company engaged in the distribution and trading services of Indonesian health products, on a national scale. In 2022, the company aims to increase sales to be awarded as one of the top 3 national pharmaceutical product distributors by 2024. Their current strategy is to provide customers with delayed payment permission and integrated complaint services. However, the offers and services are the same for all customers which does not consider customer track record hence it is not cost-effective. One way to increase sales is by enhancing customer satisfaction and loyalty by implementing Customer Relationship Management (CRM) strategies. Several strategies can be carried out, namely analysis of associations related to pharmaceutical products, and analysis of customer segmentation and clustering of products. The method used in this study was the K-means clustering algorithm combined with the Recency Frequency Monetary (RFM) model. Experiments showed that the optimal clustering results are 4 therefore they are categorized into 4 customer segments, namely Superstar, Golden, Typical, and Occasional Customers.
Contribution of Skill-Based Approach on Reading Achievement of EFL Students Kusmartini, Sri Endah; Simanjuntak, Tiur
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.294

Abstract

People can acquire valuable information for their lives if they have reading skills. Each individual has his own unique goal in reading. Therefore, some considerations need to be made to improve the skills especially regarding the approaches that can be used. One of the approach that can be applied in teaching reading is skill-based approach. Quantitative correlational study was employed to explore the contribution of skill-based approach on reading achievement of EFL students. The number of the respondents were eighty-one which were taken randomly from the students of Sriwijaya State Polytechnic semester two on the academic year 2023-2024. The questionnaire regarding skill-based approach and their reading scores were used to collect the data; and they were analyzed by using descriptive statistic, Pearson coefficient correlation and linear regression. Students’ perception regarding skill-based approach showed that 35.80% of the respondents have moderate perception; 45.68% have high perception, and 18.52% have a very high perception. In terms of reading achievement, 9.88% of respondents were sometimes able to comprehend; 56.79% were often able to comprehend reading; and 33.33% were usually able to comprehend reading. There was a significant but moderate correlation between the variables (R=0.493). The influence was significant and the contribution was 24.3%.
Summary of Audit Judgment from Auditor Experience, Task Complexity, Professional Skepticism, and Goal Orientation Abimanyu, Putri Regina; Martini, Rita; Indriasari, Desi
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.314

Abstract

The goal of this study was to gather empirical evidence about the effects of auditor experience, task complexity, professional scepticism, and goal orientation on audit judgement. This study's population and sample included 35 respondents, all of whom worked as auditors for the South Sumatra Inspectorate. Questionnaires on a Likert scale of 1 to 5 were distributed directly to auditors to collect data. The data is analysed using Structural Equation Modelling using Partial Least Squares (PLS) and SmartPLS 4.0. The findings of this study revealed that auditor experience and professional scepticism have a favourable and significant effect on audit judgement. Meanwhile, task complexity and goal orientation have a positive but not statistically significant effect on audit judgement. Additionally, auditor experience, task complexity, professional scepticism and goal orientation influence audit judgement at the Inspectorate of South Sumatra Province by 50.6%.
Integrating Temporal and Feedforward Models for Solar Energy Prediction: LSTM and ANN Hybrid Approaches Oktarina, Yurni; Zainuddin Nawawi; Bhakti Yudho Suprapto; Tresna Dewi
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 4 No. 2 (2024): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v4i2.317

Abstract

The increasing reliance on renewable energy, particularly solar power, necessitates accurate models for predicting energy output to optimize storage and distribution systems. Traditional methods such as Long Short-Term Memory (LSTM) networks and Artificial Neural Networks (ANNs) offer unique strengths in forecasting photovoltaic (PV) system outputs. LSTM excels in capturing temporal dependencies in time-series data, while ANNs effectively model nonlinear relationships between variables. This study aims to develop and evaluate a hybrid LSTM-ANN model for improving the accuracy of PV energy output predictions, focusing on voltage, power, and irradiance. Using data collected from a solar-powered greenhouse in Talang Kemang, Indonesia, the model was trained and validated. The hybrid model demonstrated significant improvements in prediction accuracy. For voltage, the model achieved a Mean Absolute Error (MAE) of 0.1016 and a Root Mean Squared Error (RMSE) of 0.1417, while irradiance predictions resulted in an MAE of 0.0895 and RMSE of 0.1149. Power predictions also yielded strong results, with an MAE of 0.1506 and RMSE of 0.1954. These results highlight the hybrid LSTM-ANN model's effectiveness in combining temporal and nonlinear data processing capabilities, leading to superior accuracy in predicting PV system outputs. This approach can enhance the reliability of energy forecasting models, enabling better integration of solar power into electrical grids. The model holds promise for broader applications in renewable energy systems, improving their efficiency and sustainability

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