cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Muhammad Ghalih
Contact Email
ghalih081092@gmail.com
Phone
+628125156396
Journal Mail Official
ijrvocas@gmail.com
Editorial Address
Ghalih Foundation Office Kh. Dewantara RT.07 RW.02, Angsau, Pelaihari, Tanah Laut, Kalimantan Selatan, Indonesia. Code Pos 70814.
Location
Kab. tanah laut,
Kalimantan selatan
INDONESIA
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 252 Documents
 22   23   24   25   26 
Predicting the Compressive Strength of Ultra-high Strength Geopolymer Concrete Using Multiple Linear Regression Marini, Lelly
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 5 No. 4 (2026): IJRVOCAS - Special Issues - Hybrid International Conference on Construction, Ma
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v5i4.483

Abstract

The growing demand for sustainable yet high-performance construction materials has intensified research into alternatives to Ordinary Portland Cement (OPC), whose production accounts for approximately 7–8% of global CO₂ emissions. Geopolymer Concrete (GPC), synthesized through the alkali activation of aluminosilicate-rich industrial by-products, has emerged as a promising low-carbon binder. However, the design of Ultra-High-Performance Geopolymer Concrete (UHGC), typically characterized by compressive strengths exceeding 120 MPa, remains highly complex due to the strong sensitivity of mechanical performance to mix composition, activator chemistry, and reinforcement parameters. This study proposes a transparent, data-driven framework for predicting and optimizing UHGC compressive strength using Multiple Linear Regression (MLR). A comprehensive dataset comprising 72 UHGC mixtures (122.9–168.8 MPa) was compiled, incorporating key variables including precursor ratio, Si/Al ratio, steel fiber volume fraction, superplasticizer content, and water-to-binder ratio. The MLR model demonstrated excellent predictive accuracy and generalization, achieving R² values of 0.944 and 0.921 for training and testing datasets, respectively, with low RMSE (~4.5 MPa). Statistical analysis confirmed the dominance of the Si/Al ratio and water-to-binder ratio as the most influential parameters governing UHGC strength. Experimental validation using nine independently designed UHGC mixtures further confirmed the robustness of the model, yielding a high correlation between predicted and measured strengths (R² = 0.954) with a mean absolute percentage error below 1%. The optimal formulation achieved a compressive strength of 168.8 MPa at a Si/Al ratio of approximately 6.0 with 1.0% steel fiber content. Compared to more complex machine learning models, the proposed MLR approach offers competitive accuracy while retaining full interpretability, enabling rational mix design and informed decision-making. This study demonstrates that interpretable predictive modeling can effectively bridge geopolymer chemistry and UHGC mix optimization, providing a practical and sustainable pathway for the development of next-generation ultra-high-performance construction materials.
Evaluation of Structural Dynamic Parameters of the Old Truss Bridges Using Smartphone-Embedded Sensors Faisal, Muhammad Hanif; Putranto, Alan; Ismah, Julia Nurzata; Rayani, Annisa Dwi
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 5 No. 4 (2026): IJRVOCAS - Special Issues - Hybrid International Conference on Construction, Ma
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v5i4.484

Abstract

Bridges are critical components of transportation infrastructure that experience continuous dynamic loading from traffic and environmental factors, leading to gradual deterioration of structural performance. Conventional Structural Health Monitoring (SHM) systems are often constrained by high cost and operational complexity. This study evaluates the application of smartphone-embedded accelerometers combined with the Ambient Vibration Test (AVT) method to identify the dynamic parameters of old steel truss bridges in Ketapang, West Kalimantan. A non-destructive and cost-effective approach was employed by utilizing daily traffic as a natural excitation source. Several bridges were selected based on service age, visible deterioration, and operational condition. Vibration data were collected using the Resonance Android application, which records acceleration and processes it into frequency spectra. Dominant frequencies and damping ratios were extracted and analyzed to assess the dynamic response of the structures. Field measurements on the Pawan 1 and Pawan 2 bridges revealed that several parameters—such as natural frequency, displacement, and damping ratio—exceeded standard thresholds, indicating potential structural degradation. These findings demonstrate that smartphone-based monitoring can serve as an effective preliminary diagnostic tool, providing valuable insights to support maintenance decisions and guide further detailed structural assessments.
Characterization of Hydrogen Gas Flow Rate on Efficiency and Specific Fuel Consumption in a Fuel Cell-Based Electric Vehicle Sigit Suseno; Hilma Khoirunnisa; Iqo Yovie Rachman; Muhammad Fadhel Hidayat; Margana; Yusuf Dewantoro Herlambang
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 6 No. 2 (2026): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v6i2.445

Abstract

The significant increase in carbon emissions from the transportation sector, which has risen by 108% in under five years, has intensified the need for sustainable alternative energy sources. Hydrogen energy, utilized through fuel cells in electric vehicles, presents a promising solution for achieving environmentally friendly transportation. This technology facilitates an electrochemical reaction between hydrogen and oxygen to produce electrical energy, with heat and water as the only byproducts. This research aims to characterize the effect of varying hydrogen gas flow rates on the efficiency and Specific Fuel Consumption (SFC) of a fuel cell-based electric vehicle. The study was conducted by integrating a fuel cell system into an electric car equipped with a 96 V, 50 Ah battery for energy storage. The primary investigation involved testing the system at three distinct hydrogen gas flow rates: 1 l/min, 1.5 l/min, and 2 l/min. Data on the fuel cell's power output was collected to calculate the resulting efficiency and SFC. The results demonstrate a clear and significant correlation between the hydrogen flow rate, efficiency, and SFC. It was established that a greater hydrogen gas flow rate leads to lower SFC values and consequently higher fuel cell efficiency. Specifically, at a flow rate of 1 l/min, the fuel cell's efficiency increased by 52.37% with a corresponding SFC decrease of 34.25%. Increasing the flow rate to 1.5 l/min resulted in a more substantial efficiency gain of 58.76% and an SFC reduction of 38.3%. At the highest tested flow rate of 2 l/min, the efficiency saw an increase of 59%, while the SFC value decreased by 14.17%. This data proves that the SFC value is inversely proportional to the fuel cell's efficiency. In conclusion, this research confirms that optimizing the hydrogen gas flow rate is a critical factor in maximizing the performance of fuel cell electric vehicles, reinforcing the potential of hydrogen as a viable and efficient energy source for future transportation.
Sustainable Reuse of Formula Milk Tin Waste for Enhancing Concrete Confinement Anis Aulia Ulfa; Mifta Amalia Putri; Lilik Damayanti; Wahyu Yusuf Rio; Ezra Hartarto Pongtuluran
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 6 No. 2 (2026): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v6i2.508

Abstract

Concrete columns play a vital role in structural systems due to their ability to resist axial and lateral loads. Enhancing column performance through confinement has been widely studied, particularly using steel tube confined concrete (STCC). In parallel, the growing amount of metal waste highlights the need for innovative and sustainable reuse strategies. One type of waste with a geometry similar to steel tubes is formula milk tins, which are commonly discarded household products. This study investigates the potential use of formula milk tin waste as external confinement for concrete specimens. Concrete cylinders confined with formula milk tins (13 cm in diameter and 16 cm in height) were compared with standard cylindrical specimens (15 cm × 30 cm). Two types of confinement were examined: plain tins and corrugated tins. All specimens were prepared using K200-grade concrete and subjected to two curing methods, namely water curing and air curing, for 28 days. Compressive strength tests were conducted in accordance with relevant standards, and correction factors were applied to account for non-standard specimen dimensions. The results show that specimens confined with formula milk tins exhibited higher compressive strength than unconfined specimens. Corrugated tin confinement provided the greatest strength enhancement, improved stiffness, and more controlled failure behavior. While water curing resulted in higher compressive strength than air curing, the confinement effect was found to be more influential than the curing method. These findings demonstrate that formula milk tins have significant potential as an alternative external confinement material for simple concrete columns, offering both structural performance improvement and a sustainable solution for reducing metal waste.
Characterization of Cassava Sludge and Tofu Wastewater as Anaerobic Digestion Substrates for Biogas Production Daya Wulandari; Riztamala Diana; Laras Niti Mulyani; Julien Alpa Harzon; Mella Aulia
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 6 No. 2 (2026): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v6i2.528

Abstract

The increasing generation of organic waste from the food processing industry has created opportunities for converting biodegradable residues into renewable energy. Cassava sludge and tofu wastewater contain biodegradable organic matter and may serve as substrates for anaerobic digestion. This study aimed to characterize the initial physicochemical properties of cassava sludge and tofu wastewater and assess their characteristics and endpoint gas profiles under different substrate formulations. Four formulations were evaluated: cassava sludge (S1), cassava sludge mixed with tofu wastewater (S2), tofu wastewater (S3), and cassava sludge supplemented with a microbial inoculum (S4). Activated Effective Microorganisms 4 (EM4) was applied to all formulations. Initial characterization included pH, temperature, total nitrogen (TN), total suspended solids (TSS), turbidity, chemical oxygen demand (COD), and biochemical oxygen demand (BOD). Reactor pH and temperature were monitored every three days for 21 days batch digestion period, followed by endpoint gas composition analysis. Cassava sludge exhibited the highest initial COD and BOD concentrations, at 19,409 and 8,640 mg/L, respectively, with TSS and TN concentrations of 680 and 270 mg/L. The cassava sludge tofu wastewater formulation showed COD and BOD concentrations of (13,355 mg/L and 6,028 mg/L), respectively, whereas tofu wastewater showed values of (6,644 mg/L and 2,974 mg/L). S4 exhibited lower initial COD and BOD concentrations of 389 and 175 mg/L, respectively, reflecting the initial characteristics of the formulation containing additional microbial inoculum. During the digestion period, temperatures ranged from (25.1–32.2 °C). while pH generally increased across the formulations. At the end of the 21 days digestion period, S4 showed the highest CH₄ reading (65.4%LEL), followed by S1 (9.7%LEL), S3 (4.7%LEL), and S2 (3.9%LEL). The observed results indicate differences in endpoint gas characteristics among the substrate formulations under the experimental conditions. Overall, the initial physicochemical characteristics and endpoint gas profiles provide a basis for assessing cassava sludge and tofu wastewater as substrates for anaerobic digestion.
Ultrasonic-Assisted Alkaline Pretreatment for Enhanced Bioethanol Production from Water Hyacinth (Eichhornia crassipes) Biomass Alya Fazza; Rizky Dwi Ramadhon; Sahrul Effendy; Yohandri Bow; Zurohaina
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 6 No. 2 (2026): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v6i2.529

Abstract

Water hyacinth (Eichhornia crassipes) is an abundant lignocellulosic biomass with strong potential as a feedstock for bioethanol production, but its relatively high lignin content limits the accessibility of cellulose and inhibits the subsequent hydrolysis process. This study aims to analyze the effect of ultrasonic-assisted pretreatment duration and NaOH concentration on the lignocellulosic composition and the resulting bioethanol yield from water hyacinth biomass. Pretreatment was carried out at 60°C and 60 W power with time variations of 10, 15, 20, 25, and 30 minutes and NaOH concentrations of 1 M and 2 M. The pretreated samples were analyzed for lignin, cellulose, and hemicellulose content using the Chesson method, then hydrolyzed with 3% H2SO4, fermented for 120 hours using Saccharomyces cerevisiae, distilled, and characterized. The results showed that the optimum pretreatment condition was obtained at a treatment time of 25 minutes with 2 M NaOH, which reduced the lignin content from 12.1% to 5.4%, reduced the hemicellulose content to 10.8%, increased the cellulose content from 56.0% to 75.1%, and produced the highest glucose content of 8.2%. Under these optimum conditions, the resulting bioethanol had an ethanol content of 14%, a density of 0.980 g/mL, a pH of 6.5, and a distillate volume of 42 mL. Gas chromatography-mass spectrometry analysis further confirmed ethanol as the dominant compound in the distillate, supporting the validity of the refractometric measurement. Beyond 25 minutes of pretreatment, however, the lignin content, cellulose content, and bioethanol yield all showed a slight decline, indicating that excessively prolonged ultrasonic exposure can degrade part of the biomass structure and reduce process efficiency. Overall, these results indicate that ultrasonic pretreatment combined with 2 M NaOH effectively enhances delignification and improves the potential for bioethanol production from water hyacinth biomass, although further optimization is still required to achieve a fuel-grade ethanol content.
Biobattery Products from Kepok Banana Peel and Key Lime Extract Using MgSO4 and CaCl2 Electrolytes with ABC Biobattery Standards of AA Size Oloan Surya Jaya S; Sofiah; Syariful Maliki; Fena Retyo Titani; Fia Dhatul Prima Kusuma; Yuniar
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 6 No. 2 (2026): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v6i2.530

Abstract

This study aims to investigate the potential of kepok banana peel (Musa paradisiaca L.) and key lime (Citrus amblycarpa) as raw materials for biobattery production and to evaluate the effects of KOH activation concentration and the addition of the ionic salts CaCl₂ and MgSO₄ on biobattery performance. Kepok banana peel was dried, ground into powder, and chemically activated using KOH solutions with concentrations ranging from 0.2 M to 1.0 M. The electrolyte was prepared by mixing key lime extract with 15 g of either CaCl₂ or MgSO₄, followed by the addition of activated banana peel powder. The resulting electrolyte mixture was packed into empty AA battery casings to fabricate the biobattery cells. The fabricated biobatteries were evaluated for pH, output voltage, loaded voltage, and operating time using a 2.2 V LED load. The results showed that the biobattery activated with 0.6 M KOH and supplemented with MgSO₄ exhibited the best performance, producing a maximum output voltage of 3.01 V (two cells connected in series), a loaded voltage of 1.75 V, and an operating time of 10 h 31 min. In contrast, activation concentrations that were either too low (0.2 M) or too high (1.0 M) reduced biobattery performance because insufficient or excessive ions hindered the electrochemical reactions. Furthermore, MgSO₄ was more effective than CaCl₂ in improving electrolyte conductivity and ionic stability. These findings indicate that organic waste, such as kepok banana peel and key lime, has considerable potential as a raw material for environmentally friendly biobatteries.
Deep Learning and N8N-Based Soybean Defect Recognition and Traceable Quality Grading System Rafie Hamizan Al Hafiz; Pola Risma; Hsien-Wei Tseng; Chun-Chieh Fan
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 6 No. 2 (2026): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v6i2.532

Abstract

Soybean is an important food commodity whose market value is strongly influenced by seed quality. However, quality inspection in many small and medium agro-industries is still performed manually, making the process slow, subjective, and poorly documented. This study develops an automated soybean inspection system that combines deep-learning-based defect recognition with traceability-supported quality reporting through workflow automation. A YOLOv11n model was trained on a self-collected dataset of 344 annotated images covering five classes, namely Intact, Broken, Skin Damaged, Spotted, and Immature, which was expanded to 1,032 images through augmentation. The model runs on a Raspberry Pi 5 inspection station, where accumulated detection results are converted into a defect rate that determines the quality grade of each batch. An n8n workflow then forwards every inspection result to the Gemini 2.5 Flash large language model to generate a narrative quality-control report, and each batch is stored in an SQLite database that can be accessed through a history viewer to support traceability. Validation results show a precision of 92.73%, a recall of 90.71%, an mAP@0.50 of 96.54%, and an mAP@0.50–0.95 of 88.67%. Functional testing demonstrates that the system produces consistent grades, accumulates detections from multiple captures into a single batch, and generates reports automatically, while still producing a rule-based report when the language model service is unavailable. The proposed system therefore offers an automated, low-cost, and traceability-supported approach to soybean quality inspection that is suitable for deployment on edge devices.
Array Antenna for IoT and Satellite Network Integration in Real-Time Disaster Prevention Monitoring Dita Anies Munawwaroh; Yusuf Dewantoro Herlambang; Irfan Mujahidin; Roni Apriantoro
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 6 No. 2 (2026): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v6i2.535

Abstract

Natural disasters pose significant risks to human life, infrastructure, and environmental sustainability, particularly in geographically isolated regions where communication infrastructure is limited or unavailable. The lack of reliable connectivity in such areas often delays disaster detection, information dissemination, and emergency response. This study proposes the development of a multi-access array antenna system designed to support the integration of Internet of Things (IoT) sensing networks and satellite communication for real-time disaster prevention monitoring. The proposed system aims to provide a robust communication framework capable of transmitting environmental monitoring data from remote sensor nodes to centralized monitoring platforms through satellite-based connectivity. The research focuses on the design, fabrication, and evaluation of a microstrip-based array antenna operating in the 2.4 GHz band, optimized to achieve high gain, improved directivity, and stable signal propagation suitable for hybrid IoT–satellite communication environments. The antenna array is designed using electromagnetic simulation tools to analyze key performance parameters, including return loss, voltage standing wave ratio (VSWR), radiation pattern, and antenna gain. The fabricated prototype is integrated with an AIoT-based monitoring platform that collects environmental data from multiple disaster-related sensors, such as rainfall sensors, anemometers for storm detection, soil moisture sensors for landslide monitoring, and ultrasonic sensors for flood detection. The data are transmitted through a satellite-enabled network infrastructure, allowing continuous monitoring even in areas lacking terrestrial communication networks. Experimental evaluation demonstrates that the proposed antenna array significantly enhances communication reliability and coverage compared to conventional single-element antennas, enabling stable data transmission in remote environments. The integration of multi-access antenna technology with AIoT and satellite networks offers an effective solution for real-time environmental monitoring and early disaster warning systems. This research contributes to the advancement of adaptive antenna technology and hybrid communication systems, providing a scalable framework for disaster mitigation infrastructure in geographically isolated regions.
Reduction of Phenol Levels in Textile Wastewater Using ZnO-NiFe2O4 Photocatalysts with Variations in Mass and Contact Time Yuniar; Yulianto Wasiran; Rizky Brillian; Irani Pinanti; Vita Rahmawati; Nursilvia Syahnaz
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 6 No. 2 (2026): IJRVOCAS - August
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v6i2.536

Abstract

The textile industry in Indonesia has an important role in the economy, but the presence of phenol is also one of the main causes of environmental pollution. Therefore, innovative solutions are needed to reduce this problem. By using Zinc Acetate Dihydrate you can obtain ZnO compounds, which are included in the category of photocatalyst compounds. ZnO has the potential as a catalyst in chemical reactions to break down organic and inorganic compounds that are harmful to the environment. Apart from that, this research also uses the NiFe2O4 compound synthesized from NiCl2 and FeCl3 as a doping agent which can reduce the ZnO band gap, thereby increasing the efficiency of photodegradation of dangerous compounds such as phenol. The research methods used consisted of ZnO synthesis and ZnO-NiFe2O4 synthesis and photocatalyst activation testing with variations in contact time of 0, 60, 120, 180 minutes and variations in the weight of the ZnO-NiFe2O4 photocatalyst of 0.5; 0.75; 1 gram. The characteristics of the resulting ZnO-Zeolite show a crystal size of 24.98 nm and absorption bands of Zn-O/Ni-O and Fe-O at wave numbers of 455 cm-1 and 580 cm-1. To determine the effect of the effectiveness of the ZnO-zeolite photocatalyst on textile liquid waste, pH, Chemical Oxygen Demand (COD), Total Suspended Solid (TSS) analysis and reduction in the concentration of phenolic compounds were carried out. Results Reduction of TSS value from 235 mg/L to 25.3 mg/L with a reduction percentage reaching 89.3% and degradation of phenol content from 3.625 mg/L to 0.067 mg/L which occurred at a mass variation of 0.75 grams and a contact time of 180 minutes.

Page 25 of 26 | Total Record : 252

 22   23   24   25   26 

Filter by Year

2021 2026


Reset
Filter By Issues
All Issue Vol. 6 No. 2 (2026): IJRVOCAS - August Vol. 5 No. 4 (2026): IJRVOCAS - Special Issues - Hybrid International Conference on Construction, Ma Vol. 5 No. 3 (2025): IJRVOCAS - December Vol. 5 No. 2 (2025): IJRVOCAS - August Vol. 5 No. 1 (2025): IJRVOCAS - April Vol. 4 No. 4 (2024): IJRVOCAS - Special Issues - International Conference on Science, Technology and Vol. 4 No. 3 (2024): IJRVOCAS - December Vol. 4 No. 2 (2024): IJRVOCAS - August Vol. 4 No. 1 (2024): IJRVOCAS - April Vol. 3 No. 4 (2024): IJRVOCAS - Special Issues - International Conference on Science, Technology and Vol. 3 No. 3 (2023): IJRVOCAS - December Vol. 3 No. 2 (2023): IJRVOCAS - August Vol. 3 No. 1 (2023): IJRVOCAS - April Vol. 2 No. 4 (2023): IJRVOCAS - Special Issues - International Conference on Science, Technology and Vol. 2 No. 3 (2022): IJRVOCAS - December Vol. 2 No. 2 (2022): IJRVOCAS - August Vol. 2 No. 1 (2022): IJRVOCAS - April Vol. 1 No. 4 (2022): IJRVOCAS - Special Issues Vol. 1 No. 3 (2021): IJRVOCAS - December Vol. 1 No. 2 (2021): IJRVOCAS - August Vol. 1 No. 1 (2021): IJRVOCAS - April More Issue