Teknosia

THE PERFORMANCE ANALYSIS OF HORIZONTAL FRANCIS TURBINE TO DISCHARGE VARIATIONS IN THE AEK SIGEAON MICRO POWER PLANT SYSTEM

2025-09-10T04:41:59+00:00

Micro hydro power plant (PLTMH) is a small-scale power plant that uses water in small discharges as its driving source. Water that can be utilized in PLTMH technology can come from irrigation channels, rivers or natural waterfalls. In general, PLTMH has three main components, namely water, water turbines, and generators. The purpose of this study is to analyze the effect of variations in water discharge on the performance of horizontal francis turbines in the Aek Sigeaon Micro Hydro Power Plant (PLTMH) system. The main focus of this study is to observe changes in input power, output power, and turbine efficiency as a result of variations in water discharge that occur in the field. Data collection was carried out using a SCADA monitoring system to obtain operational parameters in real time such as water discharge, pressure, current, and voltage. The results showed that an increase in water discharge generally caused an increase in input and output power, but was not always directly proportional to turbine efficiency. The highest turbine efficiency of 77.8% was obtained at a water discharge of 3.48 m³/s, while the lowest efficiency of 54.65% occurred at a water discharge of 6.01 m³/s. This shows that the horizontal Francis turbine works more efficiently at low to medium discharge.

DESIGNING A BUSINESS INTELLIGENCE BASED DASHBOARD FOR INVENTORY MANAGEMENT OPTIMIZATION AT CV BALI TREASURES

2025-10-29T08:31:50+00:00

The global landscape is undergoing a digital transformation marked by the Fourth Industrial Revolution and the move toward society 5.0. Companies are expected to manage data efficiently. CV Bali Treasures, a percussion instrument manufacturer, still records wood-based production data manually using Microsoft Excel, complicating trend analysis and decision-making. This study implements a Business Intelligence (BI) dashboard using Microsoft Power BI to improve raw material inventory management. The methodology follows the BI Roadmap using data from the Processed Wood Inventory Mutation Report (LMHHKO) from March 2019 to September 2024. System evaluation was conducted through User Acceptance Testing (UAT) with the Black Box Testing method involving five users. The results show the dashboard effectively visualizes inventory data, supports data historical analysis, and speeds up decision-making. Users confirmed the dashboard met their needs and was easy to use. This BI implementation is expected to support digital transformation and enhance the company's efficiency and competitiveness.

6 DOF ROBOTIC ARM RE-DESIGN BASED ON BENCHMARKING USING 3D MODELING ON AUTODESK INVENTOR 2024

2025-05-04T11:14:34+00:00

The industrial revolution 4.0 has encouraged the development of automation systems, including the 6 DOF robotic arm to enhance industrial production efficiency and effectiveness. This study aims to redesign a 6 DOF robotic arm based on benchmarking with Fanuc M-20iA and ABB IRB 2600 models using AutoDesk Inventor 2024. The method employed is benchmarking by comparing designs and specifications, followed by redesigning the Bill of Materials (BoM), Operation Process Chart (OPC), and assembly chart. The results show modifications such as redesigning the base into a square shape, adding rubber strips to the gripper, creating a separate panel for the motor driver and controller, and replacing the electromagnetic gripper with a mechanical one. The final design produces a simpler robotic arm with a production cost (HPP) of Rp105,554,924.00, which is more economical compared to similar products. The newly designed gripper is recommended for vertical object handling and positioning. Thus, the design successfully reduces maintenance costs, enhances precision, and maintains optimal performance for industrial applications.

PERFORMANCE COMPARISON OF NAIVE BAYES ALGORITHM AND SUPPORT VECTOR MACHINE ON SENTIMENT ANALYSIS OF KIP-COLLEGE PROGRAM IMPLEMENTATION

2025-09-10T04:48:16+00:00

The selection of a suitable classification model is important in text-based sentiment analysis, especially in conditions of unbalanced data distribution. Naive Bayes and Support Vector Machine (SVM) are two algorithms that are often used in classification, but the comparison of their performance on unbalanced data still needs to be further reviewed. This study aims to compare the performance of the two algorithms in classifying public sentiment towards the Indonesia Smart Card (KIP) Lecture Program. The implementation of the KIP Lecture Program still faces challenges in the accuracy of aid distribution. This situation raises discussions and various controversies among the public, especially on the X platform. The data used were 1,644 tweets, with a distribution of negative sentiment of 1,392 tweets and positive tweets of 252. To overcome the imbalance of data class distribution, the Synthetic Minority Oversampling Technique (SMOTE) method is used. Based on the evaluation results, before SMOTE was applied, SVM obtained 92% accuracy and 91% precision, 77% recall, while Naive Bayes obtained 79% accuracy, 68% precision, and 78% recall. After the application of SMOTE, SVM performance significantly improved with accuracy, precision, and recall reaching 99%, while Naive Bayes improved to 95% on all metrics. These results show that although SVM excels in higher accuracy, Naive Bayes shows a more stable performance on the data neither after nor after the balancing process is performed.

GEOTECHNICAL AND STRUCTURAL DYNAMICS ANALYSIS FOR ABUTMENT REINFORCEMENT OF THE WAY PAGAR ALAM BRIDGE FAILURE

2025-09-25T03:23:57+00:00

The Way Pagar Alam Bridge in Tanggamus Regency experienced failure at one of its widened abutments due to a combination of weak geotechnical conditions, rainfall infiltration, and riverbank erosion. This study aims to assess the structural and geotechnical conditions of the bridge and develop an effective reinforcement design. The methodology includes visual inspection, laboratory testing of soil, structural vibration monitoring, and slope stability analysis using limit equilibrium-based software. Vibration tests indicate that the bridge superstructure remains stiff, with vertical deflection well below the allowable limit. Subsurface investigations revealed the presence of expansive clay with low bearing capacity in shallow layers. Stability analysis shows that a combined reinforcement system—comprising a retaining wall, gabion protection, and mini piles—can enhance the slope safety factor to 1.99 (static) and 1.73 (dynamic), meeting applicable engineering standards. The proposed design is considered effective and applicable for bridge rehabilitation in tropical regions with soft subgrade conditions.