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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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Rancang Bangun Pembangkit Listrik Tenaga Surya Off-Grid dan On-Grid Sebagai Media Pembelajaran Mahasiswa Anggara, Jeffry; Assiddiq S, Hasbi; Ahmad Rizal; Ahmad Padli
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.3103

Abstract

This study examines the performance of solar photovoltaic (PV) systems with off-grid and on-grid configurations as practical learning media at Politeknik Kotabaru. The testing was conducted on AC loads with parameters including solar radiation intensity, voltage, current, and the power stored in the battery. Monocrystalline and polycrystalline solar panels were used to compare energy conversion efficiency. The results show that monocrystalline panels perform better than polycrystalline panels, with average differences in power and efficiency of 1,30 W and 0,50% in the off-grid system, and 1,11 W and 0,44% in the on-grid system. Solar radiation intensity significantly affects output power and conversion efficiency, with the highest power of 49,28 W obtained at the maximum radiation intensity of 1015 W/m². This study confirms that the PV system trainer can serve as an effective learning medium to enhance students’ competence in understanding the differences between off-grid and on-grid systems.
Komparasi Paduan Ethanol dan Dietyl Ether (DEE) pada Gasoline Terhadap Performa Spark Ignition (SI) Engine Sanjaya, Firman Lukman; Faqih Fatkhurrozak; Nur Aidi Ariyanto; Sigit Setijo Budi; Andre Budhi Hendrawan; Syarifudin
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.3105

Abstract

The limited availability of fossil fuels and the growing demand for energy have led to a global energy crisis. Ethanol and DEE can be used as alternative energy to replace fossil fuels. Ethanol and DEE have high RON and oxygen content, as well as low viscosity, which accelerates the flame, thereby increasing torque and SI engine power. DEE is still rarely used as a gasoline blend, but its chemical characteristics can improve engine combustion. This study aims to compare the use of gasoline-ethanol and gasoline-DEE blends on SI engine performance. The test results prove that the DEE15 blend produces the highest torque value of 4.37 N.m or an increase of 28% compared to pure gasoline. The E15 blend produces the highest SI engine torque value of 4.31 N.m or an increase of 26% compared to pure gasoline. In addition, SI engine power increases by 28% in DEE15 and 26% in E15 compared to pure gasoline. From these test results, the use of a gasoline-DEE blend can improve SI engine performance better than gasoline-ethanol.
Studi Perbandingan Kinerja Support Vector Machine Pada Klasifikasi Diabetes Mellitus Menggunakan Fitur Regular Expression dan Non-Regular Expression Prasetya, Nur Wachid Adi; Wanti, Linda Perdana; Purwanto, Riyadi
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.3125

Abstract

Diabetes mellitus is a rapidly progressing non-communicable disease that significantly affects quality of life. Clinical information in electronic medical records, such as prescriptions and laboratory results, often appears as unstructured text and therefore requires text-mining techniques for accurate classification. This research compares the performance of the Support Vector Machine (SVM) classifier on diabetes mellitus data processed with and without feature extraction using Regular Expressions (Regex). The workflow includes data preprocessing, feature extraction, TF-IDF weighting, model training, and evaluation using accuracy, precision, recall, and F1-score. Results show that both approaches achieve high accuracy (98.8–98.9%), with the non-Regex model performing slightly better at 98.93% compared to 98.83% for the Regex-based model. These findings indicate that SVM is effective for classifying text-based clinical data, while Regex provides potential benefits but requires further optimization to ensure its suitability for various medical text contexts.
Pembuatan Briket Berbahan Arang Bambu dan Batok Kelapa sebagai Energi Alternatif Faisal, Muhammad; Assiddiq, Hasbi; Anggara, Jeffry; Husni Mubarak; Indra; Wisnu Khawirian
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.3149

Abstract

The utilization of biomass as a renewable energy source represents a strategic alternative to reduce dependence on fossil fuels while promoting the sustainable use of organic waste. This study aims to evaluate the effect of varying ratios of bamboo charcoal and coconut shell charcoal, with coconut husk charcoal and binder composition kept constant, on the combustion characteristics of biomass briquettes, including ignition time, burning duration, and maximum combustion temperature. The research was conducted experimentally through biomass pyrolysis at a temperature of 300 °C for 10 hours, followed by material mixing, briquette molding, and combustion testing. The results indicate that variations in raw material composition significantly influence briquette combustion behavior. Briquettes with higher bamboo charcoal content exhibit faster ignition, whereas those dominated by coconut shell charcoal produce longer burning duration and higher combustion temperatures. The observed combustion behavior is qualitatively discussed based on differences in biomass characteristics as reported in the literature. These findings demonstrate that blending biomass with different combustion properties can achieve more balanced briquette performance.
Analisis Kinerja Sistem Distribusi Energi Listrik dan Optimalisasi Beban Berbasis Pengukuran Lapangan Suryadi, Fransiskus Xaverius; Lisapaly, Leonard; Sinambela, Rismen; Saputra, Tri Hannanto
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.2903

Abstract

This study analyzes the performance of an electrical energy distribution system and load optimization in a low-voltage distribution network with dynamic load characteristics. Common problems in such systems include phase load imbalance, power losses, and power quality issues that may reduce operational efficiency. Previous studies have mainly focused on utility networks or conventional industrial installations, resulting in limited measurement-based evaluations at the institutional scale. This research aims to assess distribution system performance through direct field measurements, identify phase-current imbalance, evaluate power quality, and formulate load-optimization strategies. Measurements were conducted using a power quality analyzer under normal operating conditions for 30 minutes with a 1-minute recording interval. The results indicate that the distribution transformer operates at an average loading level of 47.4%, with a phase current imbalance of 14.89%, active power losses of 532.5 W, and an average power factor of 0.94. Overall, the findings show that improving load management and power quality plays a more significant role in enhancing system performance than increasing equipment capacity.
Evaluasi Desain Struktur Kursi Kerja Kayu Menggunakan Simulasi Finite element method (FEM) Ramadhan Fitrianto, Taufik; Muhammad, Atdfal; Prakoso, Galih
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.2998

Abstract

Existing office chair designs often inadequately consider user anthropometry and structural strength, which may reduce comfort and compromise user safety. This study aims to redesign an office chair based on employees’ anthropometric data and to validate improvements in its structural performance using the Finite Element Method (FEM). Numerical simulations were conducted in Autodesk Inventor under incremental static loads ranging from 500 to 2000 N applied to the seat, with an additional backrest load equal to 40% of the seat load. The results indicate that the original chair design could withstand a maximum load of approximately 2,038 N, with a maximum deformation of 3.91 mm and a minimum factor of safety of 1.02. In contrast, the redesigned chair sustained loads up to approximately 7,651 N, with a maximum deformation of 4.21 mm and a factor of safety of 3.83. This represents an improvement in load-bearing capacity of about 3.7 times. The enhancement was primarily achieved through structural optimization, including increased wooden cross-sections and fewer joints. The findings demonstrate that integrating ergonomic design with FEM-based structural analysis provides a reliable engineering approach to improve the performance of wooden office chairs prior to fabrication.
Desain dan Pengujian Predictive Maintenance Agitator Berbasis Internet of Things untuk Sistem Pengolahan Air Widikda, Aris Puja; Angga Debby Frayudha
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.3004

Abstract

Agitators play an important role in the mixing, coagulation, and flocculation processes in the water treatment industry. An Internet of Things (IoT)-based predictive maintenance system was designed for early detection of agitator anomalies, including shaft imbalance/misalignment, bearing degradation, slip/RPM drop due to overload, and motor overheating. The system uses ESP32 as an edge device with an SW-420 (vibration pulse) sensor, a DS18B20 (motor temperature) sensor, and a Hall effect sensor (RPM). Data is sent via MQTT to the cloud server for real-time visualization on the dashboard. Validation against the reference instrument showed a MAPE of 0.518% and a correlation of 0.999. Anomaly warnings are triggered when the temperature is 69.5–70°C (critical 72°C) and vibration exceeds the 3σ threshold (warning 410 pulses; critical 550 pulses).
Pengaruh Ketebalan Orifis Terhadap Karakteristik Hidrodinamik Oksigen Terlarut pada Microbubble Generator Tipe Porous-Orifis Santoso, Agus; Ariawan, Radhi; Girawan, Bayu Aji; Pisti Cikarge, Ghia
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.3038

Abstract

This study aims to analyze the effect of orifice thickness on the performance of a porous-orifice microbubble generator (MBG) in aeration processes, particularly concerning the enhancement of dissolved oxygen (DO) concentration and the volumetric oxygen mass transfer coefficient (KLa). The primary issue identified is the limited number of studies that explicitly address the role of orifice thickness as a critical geometric parameter influencing microbubble formation and oxygen transfer efficiency. The research was conducted experimentally under controlled laboratory conditions using two orifice thickness variations, 1.5 mm and 9 mm, with different water and air flow rates, QL and QG. The findings reveal that increasing air flow rate (QG)  correlates positively with higher KLa values for both orifice types; however, the thinner orifice consistently demonstrates superior KLa performance. This behavior is attributed to a steeper pressure gradient and stronger shear forces that promote finer bubble fragmentation and greater gas–liquid interfacial area. Overall, the thin-orifice MBG proved more efficient in enhancing aeration performance compared to the thick-orifice configuration.
Evaluasi Performa YOLOv12 untuk Deteksi Plat Nomor Kendaraan Real-Time pada Citra Closed-Circuit Television (CCTV) Dicky Aristyanto; Yani Parti Astuti
Infotekmesin Vol 17 No 1 (2026): Infotekmesin: Januari 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/infotekmesin.v17i1.3097

Abstract

License plate detection is a crucial component of intelligent transportation systems. Deep learning methods still face limitations in detecting small-sized plates under low-light conditions and complex backgrounds. This study evaluates YOLOv12's performance for license plate detection in CCTV imagery containing small objects with great visual detail. Unlike YOLOv11, which focuses on detection efficiency for larger objects, YOLOv12 integrates attention mechanisms to enhance sensitivity to fine-grained spatial features. Model evaluation was conducted using precision, recall, and mean average precision (mAP) metrics on traffic image datasets with daytime and nighttime lighting conditions and CCTV viewing angles. Results show the model achieves mAP@0.5 of 87.2% and precision of 89.5%, comparable to previous YOLO-based studies. However, performance drops to 47.9% at mAP@0.5:0.95, indicating limitations in bounding-box localization precision under visually complex conditions. This study highlights opportunities for future improvement through dataset expansion and parameter optimization for training.

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