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Infotekmesin
Published by Politeknik Negeri Cilacap
ISSN : INFOTEKMES     EISSN : 26859858     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering
INFOTEKMESIN is a peer-reviewed open-access journal with e-ISSN 2685-9858 and p-ISSN: 2087-1627 published by Pusat Penelitian dan Pengabdian Masyarakat (P3M) Politeknik Negeri Cilacap. The journal invites scientists and engineers to exchange and disseminate theoretical and practice-oriented in the various topics include, but not limited to Informatics, electrical Engineering, and mechanical Engineering.
Arjuna Subject : -
Articles 636 Documents
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Optimasi Efisiensi Perawatan Air Conditioning Tipe Split dengan Penerapan Pembersih Filter Otomatis Berbasis Condition-Base Maintenance Hartman, Bemly; Mustofa Kamal, Dianta; Zainuri, Fuad
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2513

Abstract

The increasing use of split air conditioners (AC) in various sectors demands efficient maintenance solutions to ensure optimal performance and improve energy efficiency. Time-based maintenance (TBM), the commonly used method, often leads to premature or delayed maintenance, reducing system efficiency and increasing operational costs. Previous studies have not fully explored the application of condition-based maintenance (CBM) for AC filter maintenance, especially in developing automated systems. A significant research gap exists due to the lack of real-time solutions for accurately detecting filter conditions and enabling maintenance without manual intervention. This study aims to develop an automated AC filter cleaner prototype based on CBM by integrating sensors, microcontrollers, and actuators. The results show the system reduces energy consumption by up to 58%, shortens cleaning time by 75%, and eliminates water use. In conclusion, the proposed prototype offers an innovative and efficient solution for enhancing operational performance and reducing costs.
Analisis Sentimen Media Sosial X Terhadap Kenaikkan PPN di Indonesia Menggunakan Algoritme Naïve Bayes dan Support Vector Machine (SVM) Ikhsan, Ali Nur; Pungkas Subarkah; Alifah Dafa Iftinani; Alif Nur Fadilah
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2518

Abstract

One of the ways to increase state revenue is by raising the Value-Added Tax (VAT). However, implementing a VAT hike policy often elicits both positive and negative responses from the public. With the presence of social media, people can voice their opinions about government policies, including through social media platform X. This study aims to analyze public sentiment on social media X using the Naïve Bayes and Support Vector Machine (SVM) algorithms. The research compares the highest accuracy results before and after the balancing process. The dataset comprises 2,852 rows in CSV format. The findings indicate that the SVM algorithm achieves an accuracy of 98% before balancing and 97% after balancing, while Naïve Bayes achieves an accuracy of 97% before balancing and 90% after balancing. Overall, both algorithms demonstrate good and balanced performance.
Rancang Bangun Mesin Hot Press Hidrolik 10 Ton Untuk Cetakan Spesimen Bahan Uji Komposit Fiberglass jenal, Jenal Sodikin; Ariawan, Radhi; Ardiansyah Pradana, Rizky Nur; Dwi Cahyo, Rizal Agung
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2521

Abstract

Hydraulic Press Machines are also called composite molding machines, 10 ton hot hydraulic press machines are used to print fiberglass composite test material specimens, made to press FRP material into a certain shape so that it is easy to carry out further testing. In order to print test specimens for fiberglass composite test materials, the research aims to design, carry out calculations, and carry out function test of the machine. A hydraulic pressure of 10 tons was chosen to test the specimen whether at the specified maximum pressure the material could survive after further testing. The VDI 2222 engineering approach is used in machine design. Solidworks 2020 is used to get the design shape. With a compression force capacity of 10 tons, the pressure system design produces dimensions of 600 x 100 x 700 mm. consists of several parts such as a pressure gauge with a capacity of 20 tons, a set of temperature sensors, a timer, a sliding shaft, a 20 mm linear bearing, a 24 volt DC wiper motor, a 10 ton hydraulic jack, and a crank system as a transmission. Based on the test results, the pressure gauge can read the pressure produced by the jack, the temperature sensor can read the heat used, namely 110ËšC, and the wiper motor can operate up to a maximum pressure of 3 tons. The pressure system can function effectively if a manual pressure of 10 tons is applied. Tests show that using a temperature of 100ËšC for 10 minutes gives the best results.
Monitoring Konsumsi Daya Listrik Menggunakan Google Spreadsheet Zealita, Zarah; Prasetia, Vicky; Zaenurrohman
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2523

Abstract

The lack of detailed information on the daily electricity consumption of each electronic device can hinder the accurate calculation of electricity consumption costs. This can affect the accuracy and ease of access to electricity consumption data. This research aims to develop an electric power reading system using the PZEM-004T sensor, an electricity power monitoring system, and the cost of electricity usage through Google Sheets. The system is designed to measure current, voltage, power, and electricity costs with high accuracy. The test results show that the KWH meter reading system can measure electricity consumption using the PZEM-004T sensor with accuracy values of 99.805% for voltage (volts), 89.71% for current (amperes), and 99.98% for power (watts) in each test. The data from the sensor monitoring system and cost calculations can be effectively displayed on Google Sheets, which functions well for measuring and displaying data for current, voltage, power, and electricity billing.
Peran Nano Biokarbon Aktif Dari Kulit Pinang Terhadap Karakteristik Pembakaran Droplet Minyak Biji Bunga Matahari Harsanta, Bagus E.; Riupassa, Helen; Nanlohy, Hendry Y.
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2526

Abstract

Continuous exploitation of fossil fuels causes scarcity, so appropriate solutions and policies are needed. One of these solutions is to utilize vegetable oil, and one of them comes from sunflower seed oil, which contains 17% oleic fatty acid and around 73% linoleic. However, its high viscosity, making it difficult to burn, hampers its use as an alternative fuel. Therefore, efforts are made to reduce its viscosity. One of these efforts is to add a catalyst in the form of active nano bio carbons derived from areca nut skin. Droplet combustion is chosen to increase the contact area between air and fuel so that the reactivity of fuel molecules increases. The study's results showed that the quality of fuel produced from a mixture of sunflower seed oil and active nano biocarbon from areca nut skin was improved. It was found that a concentration of 1 ppm was the best compared to other concentrations (2 and 3 ppm). It can be seen that it was able to reduce the viscosity of sunflower seed oil to 11.16 cSt, reduce the flash point at 138°C, and can increase the droplet combustion rate by around 2.05 seconds.
Pengaruh Quenching Terhadap Sifat Mekanik dan Struktur Mikro Baut Connecting Rod Bekas Untuk Alat Gesek FSW Ari Putranto, Wahyu; Khaeroman; Susanto; Herdawan, Deri; Noviarianto
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2531

Abstract

One method of joining soft metals such as aluminum that is widely used is Friction Stir Welding (FSW). The friction tool is a very important part of FSW. Friction tools are usually made from hardened H13 steel. This research aims to make a friction tool from steel connecting rod bolts used in marine diesel engines. The experimental methods used include FSW tool design, heat treatment of the material at a temperature of 900oC followed by a quenching process with water and salt water cooling media, then continued with material testing (chemical composition test, hardness test, and micrographic test). The test results obtained from the chemical composition test show that the connecting rod bolts include AISI 4145 steel material. The highest hardness value obtained from the connecting rod steel in the saltwater quenching process was 52.67 HRC with a martensite phase, as seen from the micrographic test. Used steel connecting rod bolts from marine diesel engines can be used as FSW friction tool material.
Uji Performa Sistem Hidrolik Alat Peraga Mini Excavator Zhugimada Nur Esa, Suhada; Prihadianto, Braam Delfian; Anggoro Hasan, Dani; Ardean Kurnianto Prayitno, Yosephus; Septian, Miko; Nurul Hidayat, Anisa
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2532

Abstract

Practical learning activities on heavy equipment units are important because they increase understanding of work systems and provide an actual picture. The need for excavators for practicum activities in vocational education is currently hampered by price issues when commercial units are used as learning tools, therefore learning media in a more concise form are needed without ignoring important aspects. The manufacture of mini excavator props has been carried out but research related to work system testing is still rare, so performance testing of the work system is needed to ensure the performance of the props. The aim of this research is to test cylinder speed, cylinder pressure and cylinder drift using quantitative observation methods with variations in zero capacity, struck capacity and heaped capacity transport. From the test results, it was found that the cylinder speed values ​​were between 0.028–0.081 m/sec, the cylinder pressure was 17–20 bar for the boom, 65–72 bar for the arm, 24–34 bar for the bucket and the increase in length in the cylinder drift test was 0 mm
Prediksi Diabetes menggunakan Metode Ensemble Learning dengan Teknik Soft Voting Hilmi Hanif; Danang Wahyu Utomo
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2534

Abstract

Diabetes is a chronic disease characterized by high blood glucose levels due to the body's inability to produce or use insulin effectively. This disease is one of the serious global health problems, and it has a significant impact; therefore, early detection is very important. Efforts to overcome this challenge can be made by applying machine learning, which provides a new and effective approach. This study aims to predict diabetes with a higher accuracy level through the Ensemble Learning Soft Voting method. In addition, the data balancing technique using SMOTE is applied to overcome the problem of imbalance in the data set. This study also compares various classification models using Machine Learning algorithms, namely LightGBM, XGBoost, and Random Forest. The test results show that the Random Forest model achieves the highest level of accuracy at 97.20%. In comparison, the Ensemble Learning Soft Voting method that combines the three algorithms has increased the accuracy to 97.74%. This Ensemble Learning approach has proven effective in significantly improving predictions and performing better than a single model.
Deteksi Dini Gangguan Kesehatan Mental dengan Model Bert dan Algoritma Xgboost Rahmadika Putri Tresyani; Wahyu Utomo, Danang; Maldini, Naufal
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2535

Abstract

Mental health disorders are severe conditions that affect a person's thoughts, feelings, behavior, and well-being. Data from the World Health Organization (WHO) shows that more than 264 million people worldwide experience depression, one of the most common forms of mental health disorders. However, limited access to psychological services, such as lack of professionals and high costs, are major challenges in providing adequate support. Therefore, innovative technology-based solutions are needed for efficient and affordable psychological support. Efforts to improve research results to develop a mental health chatbot model by combining BERT (Bidirectional Encoder Representations from Transformers) and XGBoost (Extreme Gradient Boosting) models. The BERT model is used to understand the context of the conversation, while the XGBoost algorithm is used for text classification. The dataset used comes from Kaggle, which consists of 312 question patterns with several patterns or classes, namely 79 classes. The results of the program implementation test produced a percentage of 93.05% and output in the form of a program in the execution of the model on Google Colab..
Pengaruh Metode Penyayatan dan Kedalaman Penyayatan terhadap Dimensi dan Kekasaran Permukaan Kayu Olahan Rahmat, Bahtiar; Purwanto, Agung Ari; Fahrudin, Muhammad; Widiyanto, Wahyu
Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v16i1.2537

Abstract

The application of CNC technology in the furniture industry has already become familiar, in addition to its use in the metal and plastic industries. HMR (High Moisture Resistant) panels, which had better moisture resistance than MDF (Medium Density Fiberboard), had also started to develop. However, few studies have investigated the effects of variations in machining parameters on the cutting quality of HMR boards. This study aimed to test the effects of machining parameters (cutting method and cutting depth) on the dimensions and surface roughness of the workpiece. Four schemes of machining parameter settings, namely conventional and climb methods with cutting depths of 2 mm and 4 mm, respectively, were performed with three repetitions each. After testing, it was found that the cutting method, cutting depth, and the interaction between the cutting method and cutting depth had not significantly affected the length and width dimensions of the specimen. However, the cutting method significantly influenced the final surface roughness of the specimen. The conventional cutting method with a cutting depth of 2 mm produced the best surface roughness, measuring 26.47 µm.

Page 60 of 64 | Total Record : 636

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