cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Wilarso
Contact Email
wilarso@umci.ac.id
Phone
+628119202134
Journal Mail Official
wilarso@umci.ac.id
Editorial Address
https://jurnal.sttmcileungsi.ac.id/index.php/tekno/editorial
Location
Kab. bogor,
Jawa barat
INDONESIA
TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Published by Universitas Muhammadiyah Cileungsi
ISSN : 20873336     EISSN : 27214729     DOI : https://doi.org/10.37373/tekno.v13i2
Core Subject :
Aim and Scope Aim The aim of this journal publication is to disseminate the fundamental ideas or ideas that have been accomplished and the study findings in technology, science and informatics. In terms of community sector study outcomes, the Journal of Technoscience primarily reports on the main issues. Scope Science issues Scopes related to this topic include: Agriculture, Climate, Mathematics & Statistics, Applied Physics, Fundamental Science in Engineering, Bioscience & Biotechnology. Engineering and Technology issues Scopes related to this topic include: Mechanical & Structures, Electrical, Communications & Systems, Fuel and Energy, Material, Termal Management, Safety System and Technology, Maintenance Technology, Automotive . Information and Technology issues Scopes related to this topic include: Artificial Intelligence, Computer Science, E-learning & Curriculum, Information Science, Multimedia, Science Technologies, Information Networks, Internet & Mobile Computing, Machine Learning, Information Science.
Arjuna Subject : -
Articles 222 Documents
 16   17   18   19   20 
Analysis of the accuracy of the sarimax model in forecasting cocoa production in Central Sulawesi Nursuci Rafailah Arsya; Wellie Sulistijanti
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1622

Abstract

Cocoa production in Central Sulawesi is among the highest in Indonesia and plays a crucial role in supporting national export needs. Cocoa production trends have shown a significant decline over the past two years. This decline is thought to be caused by various factors, including shrinking cultivated land due to land conversion and climate uncertainty, reflected in erratic rainfall patterns, resulting in unstable cocoa supply. Therefore, a scientific and data-driven approach to cocoa production forecasting is crucial for proper planning and monitoring of production and for anticipating imbalances between demand and supply. This study utilized the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) method, considered superior for its ability to capture seasonal patterns while simultaneously accommodating the influence of exogenous variables such as rainfall and land area, resulting in more accurate forecasting. The data used are cocoa production data as endogenous variables and rainfall and land area as exogenous variables for the period January 2020 to December 2023. The analysis stages include SARIMA model identification, pre-whitening, transfer function analysis, and evaluation of model accuracy using Mean Absolute Percentage Error (MAPE). The results of the study show that the best model is SARIMAX (1,1,1)(0,1,0), with land area variables at lag-5 being significant to cocoa production, producing a MAPE value of 3.29%, so this model can be used to predict future cocoa production.
Student satisfaction survey at XYZ Campus using the Slovin formula method and mwater application Nurkholis; Pria Sukamto; Fia Dhatul Prima Kusuma
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1642

Abstract

The progress of an institution as a learning process organizer on a campus is a key organizational goal, as it fosters competitiveness and enhances benefits for the organizatio. However, in the process of achieving this progress, it is necessary to measure student satisfaction, whether they are satisfied or not, which is the problem in this study. The purpose of this study is to measure student satisfaction with each campus resource that has been provided, whether it has reached the expected student satisfaction category or not. The method used to measuring this satisfaction is the Slovin method and the MWater application, which method is a method for collecting data and opinions from customers or students regarding the products or services received. In this case, a student satisfaction survey can be used to determine the level of student satisfaction and interest in services and facilities on campus. This student satisfaction survey can be packaged in the form of questions related to new student services, such as information regarding new student admissions (PMB), administrative services and available campus facilities. With the MWater application, we can create survey forms and collect survey answers quickly and efficiently, while the Slovin formula is used to determine the number of samples needed from the population of the number of new students in each faculty. The results of the study using the Slovin formula and the Mwater application showed that 77.8% of students were satisfied with the campus service, while 5.6% were dissatisfied, 5.6% were dissatisfied, and 11.1% were very satisfied. The results of this survey can then be used as a reference for the campus in planning future promotional strategies and university policies.
A comparative study of tree-based machine learning algorithms for artificial lift optimization Geovanny Branchiny Imasuly; Marcia Rikumahu
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1663

Abstract

The selection of an appropriate artificial lift method is critical in the oil and gas industry to ensure production continuity as reservoir pressure declines. However, current selection processes still largely rely on technical expertise and conventional heuristic approaches, which are often insufficient for handling the complexity of reservoir characteristics and dynamic operational conditions. This study aims to evaluate the performance of three tree-based machine learning algorithms—Decision Tree, Random Forest, and Gradient Boosting—in predicting the optimal artificial lift method. Historical field data, including fluid flow rate, temperature, API gravity, and artificial lift method labels, were used to train the models. The data underwent preprocessing steps such as data cleaning, encoding, and splitting into training and testing sets before being modeled using the Scikit-learn library. The performance of the three models was evaluated using standard classification metrics, including accuracy, precision, recall, and F1-score. The results indicate that the Decision Tree algorithm achieved an accuracy of approximately 81%, Random Forest yielded the highest accuracy at around 94% (with a validation accuracy of 93.67%), while Gradient Boosting performed the least effectively with an accuracy of about 64%. Feature importance and SHAP analysis revealed that temperature was the most influential variable in selecting the artificial lift method, followed by API gravity and fluid flow rate. In conclusion, Random Forest was the most effective model, offering the best combination of accuracy and stability in predicting the optimal artificial lift method.
Seawater evaporation using natural flow solar still Andika Cahya Putra Pratama; Dan Mugisidi; Oktarina Heriyani
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1664

Abstract

One-third of the world's population, including coastal communities in Indonesia, experiences a shortage of clean water for daily needs. By 2050, it is estimated that around 25% of the world's population will be affected by the clean water crisis. This research is directed at examining the role of natural airflow in a solar still system in determining the evaporation rate during the seawater desalination process. Water temperature has a significant influence on solar still performance, where increasing water temperature and airflow velocity within the system will increase the evaporation rate. This research focuses on measuring the evaporation rate of seawater in a solar still device that relies on natural flow as its working mechanism. The desalination process is equipped with a condenser that functions to convert water vapor into liquid. In addition, there is a measurement system that includes temperature parameters and airflow velocity to ensure effective operation and precise data monitoring. Evaporation data was collected periodically every 15 minutes during a two-day observation period, to conduct a comprehensive analysis of the desalination system's performance. Research results show that the use of solar energy with natural flow can effectively accelerate the evaporation rate. The average experimental result is 231 grams and the theoretical result is 174 grams, with a percentage of 57%. This system has the potential to increase the efficiency of the desalination process, especially if developed according to local climate conditions that affect the overall performance of the device
Utilization of ferronicle slag for the manufacture of rotary kiln lining refractories Muhammad Ridwan Septiawan; Angga Tegar Setiawan; Muhammad Alfian; Jumaddil Hair; Joko Sulistyo
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1694

Abstract

Ferronickel slag waste from the nickel ore processing industry can be used as a refractory raw material for the inner wall lining of rotary kilns. However, the use of this waste still needs to be studied for its properties to meet the standards for its use in the industry. The purpose of this study was to find the optimal composition of a refractory mixture consisting of ferronickel slag, magnesium oxide (MgO), and aluminum oxide (Al2O3). The percentage composition of ferronickel slag and MgO was changed, while Al2O3 remained constant. The characterization of the refractories that had been made was carried out through a series of tests consisting of chemical composition testing using X-ray Fluorescence (XRF), porosity testing, bulk density, permanent linear change (PLC), and cold crushing strength (CCS). The results of the analysis showed that the ferronickel slag used as the main material in this study contained silica (SiO₂), magnesium oxide (MgO), and iron oxide (Fe₂O₃) which supported the properties of the refractories that had been made. The optimal refractory composition is 90% slag and 10% MgO, resulting in a porosity of 25.56% and a bulk density of 1.74 g/cm³, indicating a balance between strength and thermal insulation. The PLC green value of -0.8667% and the PLC dried value of -0.1177% indicate good dimensional stability. The CCS test for the best composition produces a cold compressive strength of 1.44 MPa. The study indicate that refractories have thermal and mechanical resistance that supports their use as rotary kiln lining materials.
Performance analysis of a 2.4 MW biogas power plant from palm oil mill liquid waste in the Sei Mangkei special economic zone Bona Sahala Purba
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1695

Abstract

The Biogas Power Plant (PLTBG), located in the Sei Mangkei Special Economic Zone (KEK), North Sumatra, is an effort to develop environmentally friendly renewable energy and has the potential to reduce greenhouse gas emissions. The PLTBG's performance during its first two years of operation was influenced by several factors, including electricity production, wastewater input capacity, output power, generation efficiency, and its economic value compared to PLN electricity. This study aims to process operational data of the Sei Mangkei SEZ Biogas Plant liquid waste/Palm Oil Mill Effluent (POME) Power Plant that utilizes the existing Sei Mangkei PKS liquid waste related to Performance including the capacity of the input of liquid waste/Palm Oil Mill Effluent (POME), output power. This study uses a performance approach method, stages of work activities that include several stages, namely the survey stage, data compilation stage, analysis stage, and calculation stage, data processing and conclusion. This technical analysis method uses analytical tools in the form of theoretical quantitative and qualitative models, the concept of minimizing Discharge and Waste, and the need for biogas plant environmental studies. The results of this study show that the capacity of the Sei Mangkei POM is 75 tons of FFB per hour or 325,255 tons of FFB per year. Based on fluctuations in FFB production over a 2-year period (2022-2023) in Sei Mangkei, the average production projection is 325,255 tons per year, with POME producing 65% of the average FFB production of 211,416 tons per year using the Covered In Ground Anaerobic Reactor (CIGAR) processing model.
Technical evaluation of kVar import anomalies on main transformer number 2 at Siman Hydroelectric Mohamad Farel Firmansyah; Arya Kusumawardana; Royb Fatkhur Rizal; Soraya Norma Mustika; Hafidz Malkanz Chaironi; Ruth Nike Dauhan
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1726

Abstract

An issue of reactive power import (negative kVar) was identified in Main Transformer No. 2 at PLTA Siman, resulting from mismatched voltage ratios and impedance values among parallel-operated transformers. This mismatch induced a circulating current and led to reactive power being absorbed from the external grid, increasing energy losses and operational costs. This study aims to investigate the root cause of the anomaly, propose technical solutions, and evaluate their effectiveness. The analysis was conducted out through system simulation using ETAP software, testing three technical scenarios: installation of a 569.9 kVar capacitor bank, implementation of a Standard Operating Procedure (SOP) for PMT disconnection during standby conditions, and replacement of the transformer with one that matches the specifications of the other units. The simulation results revealed that SOP implementation eliminated kVar import by 100% during standby, the capacitor bank reduced it by approximately 70%, and transformer replacement fully eliminated the circulating current. The findings suggest that a combined approach involving SOP and capacitor installation offers an optimal solution without major infrastructure replacement.
Enhancing rice plant disease detection through transfer learning and image segmentation with YOLOv11 Muhammad Reza Redo I Islami; Sylvia; Atika Arpan; Rizka Permata; Dwi Handoko; Rima Maulini; Dwirgo Sahlinal
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1754

Abstract

Rice is a staple food globally, yet its productivity is often threatened by diseases such as blast and brown spot. Traditional diagnostic methods relying on human observation are prone to delays and inaccuracies. This study introduces an automated detection system that utilizes YOLOv11-seg to improve the accuracy and efficiency of rice disease identification. The model integrates object detection and instance segmentation, is trained on over 6,000 annotated images covering six categories (five disease types and healthy leaves), and leverages transfer learning from COCO weights. Experimental results show that the model achieved a bounding box mAP@50 of 0.607 and a segmentation mAP@50 of 0.564, with F1-scores of 0.62 and 0.59, respectively. The highest detection accuracy was recorded for healthy leaves (86%), while segmentation performance declined on visually similar classes such as Brown Spot and Sheath Blight. Overfitting was observed during training, with a 15–20% gap between training and validation metrics. These findings demonstrate the model's potential for real-time field application in precision agriculture. Future improvements should focus on enhancing spatial accuracy and robustness through synthetic data generation and architectural optimization.
Design and structural analysis of a 100 kg/h palm frond shaving machine using SolidWorks Dicky Septri Anugrah; Achmad Jusuf Zulfikar; Ibnu Hajar; Suardi
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1755

Abstract

This study presents the design and structural analysis of a palm frond shaving machine with a production capacity of 100 kg/hour, aimed at improving the efficiency of the traditional manual process used by craftsmen. The manual method is time-consuming and labor-intensive, limiting production to approximately 2 kg/hour. To address this issue, a mechanical design was developed using SolidWorks 2017 software. The research involved consumer surveys to identify user requirements, followed by concept generation, technical and economic evaluation, and simulation analysis of the selected design. Among three design variants, the second concept—featuring a stone grinder cutter system, UNP steel frame, V-belt transmission, and gasoline engine—was selected as optimal based on combined technical and economic scores. Structural simulation results indicate that the frame, made from UNP 50 steel profiles, exhibits acceptable stress, displacement, and safety factor levels under an applied load of 10 kg. This study offers a viable solution for small-scale industries to process palm fronds into usable sticks efficiently. Future work may include prototype development and extended performance testing. The machine’s application is expected to contribute to local economies by utilizing agricultural waste and increasing the production of palm stick-based handicrafts.
Analysis of market positioning and generic strategy map of gelato products in Indonesia market place M Ali Pahmi; Miftahul Imtihan; Mastang
TEKNOSAINS : Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika
Publisher : LPPMPK- Universitas Muhammadiyah Cileungsi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37373/tekno.v13i1.1795

Abstract

This study investigates the market potential, positioning, and strategic formulation for milk-based gelato products in Indonesia. Literature analysis reveals that ice cream holds a special place among Indonesian consumers, with 69.2% expressing strong preference and only 0.6% disliking it. The Indonesian ice cream market recorded USD 527 million in revenue in 2019, with a CAGR of 15.97% from 2015 to 2019, and consumption volume reaching 105.3 million kilograms. Future projections indicate a continued positive growth trend at a CAGR of 7.18% between 2020 and 2025, driven by rising disposable incomes, urbanization, and lifestyle shifts favoring premium dairy products such as gelato. The market positioning analysis of the top 10 gelato brands shows diverse competitive strategies: Bonico offers the most competitive price per gram, Batavia leads in flavor variety, and Powder Aja and Toffin excel in packaging weight for B2B segments like cafés and restaurants. Furthermore, generic strategy analysis identifies four limitations faced by the industry: high-volume market demands, intense price competition, operational cost efficiency, and medium-to-large-scale dominance. The proposed generic strategy map includes rigid consequences, strategic choices, and flexible consequences. These interconnected strategies provide MSMEs and industry players with a comprehensive framework to build competitive, sustainable, and innovative milk-based gelato businesses aligned with evolving market dynamics in Indonesia.

Page 18 of 23 | Total Record : 222

 16   17   18   19   20 

Filter by Year

2020 2026


Reset
Filter By Issues
All Issue Vol 14 No 1 (2027): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 13 No 2 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 13 No 1 (2026): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 12 No 2 (2025): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 12 No 1 (2025): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 11 No 2 (2024): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 11 No 1 (2024): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 10 No 2 (2023): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 10 No 1 (2023): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 9 No 2 (2022): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 9 No 1 (2022): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 8 No 2 (2021): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 8 No 1 (2021): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 7 No 2 (2020): TEKNOSAINS: Jurnal Sains, Teknologi dan Informatika Vol 7 No 1 (2020): Teknosains : Jurnal Sains, Teknologi dan Informatika More Issue