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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 669 Documents
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Perbandingan Arsitektur VGG16, MobileNetV2, InceptionV3, ResNet50, dan CNN Kustom untuk Klasifikasi Gambar Furnitur Epiphany Shavna Gracia; Nurul Anisa Sri Winarsih
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.v16i1.2500

Abstract

The rapid development of technology in the current digital era is driving increased demand across various sectors, including the furniture industry. Classifying furniture images is one of the critical challenges in image processing and computer vision, mainly due to the diversity of types. This research aims to understand how pre-trained models can affect image classification accuracy using furniture dataset results. This study uses five CNN architectures and focuses on comparing the performance of a custom architecture with four pre-trained architectures, namely VGG-16, MobileNetV2, InceptionV3, and ResNet-50, using furniture images that have five classes such as chairs, tables, cabinets, sofas, and mattresses. The research results show that the models produced by the pre-trained architectures provide higher accuracy and performance, with VGG-16 reaching 97%, MobileNetV2 at 96%, and InceptionV3 and ResNet-50 at 98%. Meanwhile, the custom model only achieved an accuracy of 85%. This research shows that using pre-trained model algorithms significantly improves performance in image classification.
Studi Karakteristik Komposit Matrik Logam Al-Cu-Mg Dengan Penambahan SiC Disintesis Menggunakan Teknik Metalurgi Serbuk Diikuti Artificial Aging Suprianto; Rasyid Nasution, Bakri; Karo Karo, Junsean Christian; M. Rafli; Kurniawan Nasution, Fadly Ahmad
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.v16i1.2503

Abstract

The improvement of the characteristics of Al-Cu-Mg through SiC addition and precipitate formation can be achieved through powder metallurgy and artificial aging, which means that the correct amount of particles and holding time are important. This research aims to investigate the effect of SiC and time on microstructure change, mechanical properties, and electricity. The Al, Cu, Mg, and (1~2.0) wt.%SiC powder were mixed by horizontal milling and subsequent sintering at 500oC. The artificial aging at 180oC with (2, 4, 6) hour holding times. The hardness test, compression, electrical conductivity, and microstructural observation were carried out. The results show that the addition of SiC particles improves the strength and reduces the conductivity. The conductivity improvement obtained after aging. SiC particles tend to be dispersed between grain boundaries. Based on the data, it can be concluded that SiC and artificial aging have a positive effect on the mechanical properties of Al-Cu-Mg alloy.
Perbandingan Kinerja Djaka, Thesa Permatasari Djaka; Nurul Anisa Sri Winarsih
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.v16i1.2504

Abstract

Polycystic ovary syndrome (PCOS) is a hormonal disorder that is the most common cause of anovulation and infertility in women of reproductive age, affecting approximately 5-10% of the population, with up to 70% of cases undiagnosed. This highlights the need for early detection methods with high accuracy for timely treatment. Previous research utilized a classification method based on the K-Nearest Neighbor (KNN) algorithm, which demonstrated good performance with an accuracy of 93%, precision of 100%, recall of 82%, and F1-Score of 90%. This study proposes using an ensemble learning method with a voting classifier technique that combines several classification models: Random Forest Classifier, Logistic Regression, and XGBoost Classifier. The results show that the proposed method performs better with an accuracy of 95%, precision of 100%, recall of 85%, F1-Score of 92%, and an AUC (Area Under Curve) value of 94.34%
Potensi Serat Pelepah Nipah Sebagai Bahan Baku Binderless Fiberboard Kristiningsih, Ari; Wittriansyah, Khoeruddin; Ariawan, Radhi
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.v16i1.2507

Abstract

Fiberboard uses a lot of agro-industry waste materials combined with synthetic adhesives containing formaldehyde. The weakness of this adhesive is that it can cause health problems such as cancer and eye irritation. Lignin has properties and content similar to formaldehyde. Nipah has lignin and cellulose content that can be developed into binderless fiberboard. The purpose of this study was to analyze the potential of Nipah frond fiber to make a binderless fiberboard. The characteristics of fiberboard that will be explored include density and water content. Nipah frond binderless fiberboard is made using a press machine with a pressure of 50 bar, and a temperature of 100oC for 20 minutes. The density between 0.46-0.52 which is by the requirements of SNI 03-2105-2006 and the water content of 5.98% - 7.70% is also by the requirements of JIS 5908: 2003 and SNI 03-2105-2006. Based on these results, it can be concluded that Nipah fronds can be used as raw material for binderless fiberboard.
Designed a Waste Management Application by Applying Requirements Engineering Methods to Meet User Needs and Expectations Lisda, Lisda; Febrianto, Dany Candra; Kusumastuti, Rajnaparamitha
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.v16i1.2509

Abstract

Efforts to manage waste through recycling have been implemented frequently but continue to receive minimal attention from the public, who are daily contributors to waste generation. As a result, the volume of waste keeps increasing, leading to environmental pollution, such as ecosystem damage, unpleasant odors, and blockages in waterways. This research aims to demonstrate that waste management can be enhanced by integrating data to uncover insights that can inform new strategies for addressing excess waste. In this study, a prototype for a waste recycling application was developed, focusing on digital-based waste management using IoT technology. The system incorporates sensors capable of measuring waste volume as a supporting tool developed using the requirements engineering method. Questionnaires were distributed to 30 respondents to gather feedback on platform designs and IoT product designs. Through requirements validation testing, the results showed that 70% of the 30 respondents approved the platform design, while 63.2% approved the IoT product design.
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.
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.

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