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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.
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Articles 707 Documents
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Text Extraction and Structurization of Indonesian Laws for Semantic and Relational Analysis Muhammad Harist Murdani; Fikri Hadi
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Indonesia is struggling with too many overlapping laws which is reflected in the number of judicial review cases the Constitutional and Supreme Court received. There is a need to develop a more systematic way to analyze legal reasoning. This study suggests a tech-driven framework for digital laws, which could help with national legal reforms in line with SDG 16. This study compares Tesseract OCR, PyMuPDF and  the Gemini API to extract text from PDFs. Gemini API accuracy tops other methods, thus it is used for the rest of study. Then the text is cleaned and turned into structured JSON which gets plugged into ChromaDB for analyzing semantic similarities and ArangoDB for mapping out legal relationships. The result is a machine-readable version of Indonesian laws. The whole approach shows a scalable method for taking complex legal documents and turning them into a structured knowledge base. The experimental results demonstrate that the Gemini API significantly outperforms conventional methods, achieving 97% text accuracy, 95% structural accuracy, and only 3% Word Error Rate, compared to 78% and 90% for Tesseract and PyMuPDF, respectively.
Analisis Kinerja dan Reduksi Emisi Karbon pada Mesin Pemipil Jagung Berbasis Energi Surya Toni Okviyanto; Hendradinata Hendradinata; Firdaus Firdaus; Tri Satya Ramadhoni; Agis Fika Wulandari; Indra Syahputra; Stevan Juliandro Aruan
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Agricultural post-harvest operations require technological innovations that enhance productivity while reducing dependence on fossil fuels and environmental impacts. Although solar energy has been increasingly applied in agricultural mechanization, previous studies have primarily focused on technical performance or energy consumption, with limited attention to integrating machine performance evaluation and carbon emission reduction. This study aimed to evaluate the performance of a solar-powered corn sheller and assess its carbon emission reduction potential compared with a gasoline-powered sheller. A comparative experimental method was employed by analyzing shelling capacity, shelling efficiency, energy consumption, kernel damage, and carbon emissions using the Intergovernmental Panel on Climate Change (IPCC) emission factor. The results showed that the solar-powered sheller achieved a shelling capacity of 65 kg h⁻¹ and a shelling efficiency of 90%, which were comparable to the gasoline-powered sheller (69.67 kg/h and 91.67%, respectively). Moreover, the solar-powered system produced no direct operational carbon emissions, whereas the gasoline-powered sheller emitted 0.5082 kg CO₂ per 10 kg of processed corn. The novelty of this study lies in integrating technical performance evaluation with IPCC-based carbon emission analysis. This study provides a comprehensive evaluation framework to support the development of low-carbon agricultural mechanization based on renewable energy.
Analisis Kegagalan Pada Ducting Primary Air Fan Menggunakan Metode RCA, CFD, dan FEA Djia Hamdali Suherman; Budi Triyono; Yogi Baskoro; Setyo Wibawono
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

This study analyzes the causes of recurrent cracking in the Primary Air Fan (PAF) ducting of a Circulating Fluidized Bed (CFB) boiler and develops improvement recommendations. The methods comprise field crack mapping, Root Cause Analysis (RCA) using Ishikawa and Fault Tree Analysis, Computational Fluid Dynamics (CFD), and Finite Element Analysis (FEA). Cracks were concentrated at panel edges, stiffener terminations, welded joints, and heat-affected zones. CFD revealed non-uniform flow and vortices at elbow/transition regions, while FEA showed maximum stress increasing from 142 MPa at 40 °C to 224 MPa at 50 °C. A 100 mm panel-edge radius reduced stress from 145 MPa to 36 MPa, or 75.2%. The novelty lies in integrating field evidence, RCA, CFD, and FEA to explain the failure mechanism comprehensively. The findings support more targeted repair strategies to improve PAF ducting reliability and service life.
Analisis Deviasi Specific Fuel Consumption (SFC) Dan Efisiensi Termal Turbin Gas Kondisi Baseline Serta Implikasinya Terhadap Biaya Bahan Bakar Alviansyah Putra Wahyudi; Arifia Ekayuliana; Gun Gun Ramdlan Gunadi; Fathan Mubina Dewadi
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Gas turbine performance degradation caused by changes in ambient temperature and compressor deterioration can increase Specific Fuel Consumption (SFC), reduce thermal efficiency, and increase fuel costs. Previous studies have investigated the influence of ambient temperature and compressor washing on gas turbine performance; however, most have evaluated these factors separately without relating them to deviations from the manufacturer’s baseline and their economic implications under relatively constant operating load conditions. This study proposes an integrated evaluation approach by combining the effects of ambient temperature, compressor condition before and after compressor washing, performance deviation from the manufacturer’s baseline, and its impact on fuel cost. The study aims to analyze the deviations in Specific Fuel Consumption (SFC) and thermal efficiency from the manufacturer’s baseline and to evaluate their implications for fuel cost using actual operating data based on the Brayton cycle approach. The results show that the SFC deviation decreased from 4.64–4.72% before compressor washing to 3.56–3.79% after compressor washing, while the thermal efficiency deviation improved from −1.29% to −1.66% to −0.85% to −1.12%. These performance improvements were accompanied by a 0.84–1.06% reduction in fuel cost under all operating conditions. The findings provide quantitative evidence that deviation evaluation based on the manufacturer’s baseline can be used as an effective approach to assess the effectiveness of compressor washing and to support condition-based maintenance decision-making for gas turbines.
Pengaruh Variasi Media Quenching pada Solution Treatment Paduan Al–Si Hasil Remelting piston terhadap Kekerasan dan Struktur Mikro Titiek Deasy Saptaryani; Muhammad Munawir Lasiyono
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Recycled aluminum–silicon (Al–Si) alloys produced from remelted automotive pistons are increasingly utilized in the casting industry because of their cost-effectiveness, recyclability, and environmental benefits. However, the remelting process may degrade material quality through microstructural changes, porosity formation, and deterioration of mechanical properties. Studies investigating the influence of different quenching media on remelted Al–Si piston alloys remain limited. The novelty of this study lies in evaluating the relationship between quenching media, microstructural evolution, and hardness characteristics of remelted Al–Si piston alloys. This study aimed to investigate the effect of different quenching media after solution treatment on the hardness and microstructure of remelted Al–Si alloys. Used automotive pistons were remelted, cast into metal molds, and machined into standard test specimens. The specimens were heated from room temperature to 550 °C in approximately 30 min, held at 550 °C for 90 min, and quenched in water, oil, or air. Hardness was evaluated using the Brinell hardness test, while the microstructure was examined by optical microscopy. The highest hardness was obtained in the specimen without quenching (63.3 HB), followed by water quenching (62.6 HB), oil quenching (59.6 HB), and air cooling (51.6 HB). Water quenching produced a finer and more homogeneous distribution of silicon particles than oil and air cooling. These findings provide a scientific basis for selecting an appropriate quenching medium to optimize the heat treatment of recycled Al–Si alloys for sustainable casting applications.
Simulation-Based Analysis for Optimizing ID Card Holder Injection Molding Using Autodesk Fusion Adinda Rahmah Shalihah; Edwin Sahrial Solih; Sanurya Putri Purbaningrum; Ridho Hans Gurning; Fredy Sumasto; Desy Agung
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

This study aims to determine the most suitable initial injection-molding condition for a polypropylene (PP) ID card holder using Autodesk Fusion. Five paired melt-temperature and mold-surface-temperature conditions were evaluated at injection times of 0.5 and 1.0 s, resulting in ten simulation cases. The contribution of this study is a multi-response screening approach before mold fabrication that simultaneously considers fill confidence, injection pressure, quality prediction, cooling time, air traps, weld lines, sink marks, and warpage. All conditions achieved fill-confidence values of 99.67–100%. P4 at 1.0 s produced the highest quality prediction of 85.81% but required 11.87 s of cooling. P2 at 1.0 s was selected as the most balanced condition, with 85.27% quality prediction, 44.98 MPa injection pressure, 4.95 s cooling time, approximately four air-trap areas, 18 weld-line faces, a 0.027 mm sink mark, and 1.736 mm warpage. These simulation results require experimental validation.
Perbandingan Kinerja Algoritma Random Forest, Support Vector Machine, dan Naive Bayes Pada Klasifikasi Judul Skripsi Menggunakan Variasi N-Gram Nur Wachid Adi Prasetya; Ike Yunia Pasa
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Choosing a thesis topic remains challenging because many students struggle to select an appropriate research title. Thesis title classification can support this process by helping identify suitable research areas. Although classification algorithms have been widely applied in sentiment analysis, comparative studies of Random Forest, Support Vector Machine (SVM), and Naive Bayes, for thesis title classification using N-Gram features remain limited. This study compares these algorithms through text preprocessing, TF-IDF-based N-Gram feature extraction, and evaluation using confusion matrices and processing time. The dataset consists of 96 thesis titles classified into four categories: Information Systems, Multimedia, Networks, and IoT & Artificial Intelligence. The results show that SVM achieved the best performance, with 80% accuracy, 89% precision, 80% recall, an F1-score of 81.46%, and a processing time of 0.003 seconds, indicating that SVM is the most effective algorithm for thesis title classification compared with Naive Bayes and Random Forest.
Otomatisasi Pelabelan Korpus Sarkasme pada Komentar YouTube Berbahasa Indonesia Menggunakan Model Bahasa RoBERTa Rizky Agil Singgih Susanto; Taqwa Hariguna; Azhari Shouni Barkah
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Sarcasm detection in Indonesian YouTube comments remains challenging due to contextual ambiguity, limited labeled data, and class imbalance. This study proposes a fine-tuned RoBERTa-based auto-labeling pipeline to generate high-confidence pseudo-labels for unlabeled comments. The scientific contribution lies in integrating Back-Translation augmentation, confidence-threshold filtering at P ≥ 0.85, and comparative evaluation against baseline models on a YouTube sarcasm corpus. The data were collected from 10 public Indonesian YouTube videos covering public service, political, social, and entertainment topics during January-March 2025. From 1,000 raw comments, 493 clean comments, 200 manually labeled instances, and 536 final instances were obtained after augmentation and pseudo-label filtering. The 5-fold cross-validation results show that RoBERTa achieved an accuracy of 0.89 and a macro F1-Score of 0.87, with class-wise precision/recall of 0.81/0.81 for sarcasm and 0.92/0.92 for non-sarcasm. Compared with TF-IDF + SVM, BiLSTM, and IndoBERT, RoBERTa improved the F1-Score by 24.29%, 12.99%, and 3.57%, respectively. These findings indicate that RoBERTa-based auto-labeling can support a more controlled expansion of sarcasm corpora while reducing reliance on fully manual annotation.
Sistem Global Positioning System (GPS) Tracking Pendaki Gunung Menggunakan Komunikasi LoRa Zaenurrohman; Arif Sumardiono; Erna Alimudin; Adrian Ramdhan; Hera Susanti
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Mountain climbing activities involve a high risk of hikers becoming lost due to limited location information and the lack of reliable cellular network coverage in mountainous areas. This study aims to develop an Internet of Things (IoT)-based GPS tracking system utilizing Long Range (LoRa) communication to support real-time hiker location monitoring and emergency notification in cellular network blind-spot areas. The proposed system consists of an ESP32-based transmitter equipped with a GPS module, an SX1262 LoRa module, and an emergency push button, a LoRa gateway as the receiver, and a web-based monitoring platform for real-time location visualization. System performance was evaluated through GPS accuracy testing, emergency response time measurement, and LoRa communication performance in both urban environments and the Mount Slamet hiking trail. The experimental results indicate that the GPS positioning error ranges from 7.25 to 9.16 m, with an average error of 8.25 m. The emergency notification system achieved a 100% transmission success rate with a response time of 20–22 s. Communication testing demonstrated that LoRa provided reliable data transmission over distances of up to approximately 300 m in urban environments, while communication quality degraded at longer distances due to reduced Received Signal Strength Indicator (RSSI), increased packet loss, and the effects of terrain, vegetation, and Line-of-Sight (LoS) conditions along the hiking trail. These results demonstrate that the proposed system is capable of providing reliable location monitoring and emergency communication in areas with limited cellular coverage, making it a promising solution for supporting Search and Rescue (SAR) operations in mountainous environments.
Mekanisme Kehilangan Tekanan dan Struktur Aliran Gas LPG pada Swivel Joint Style 40 dengan Sudut Gerak 45°: Studi Computational Fluid Dynamics I Putu Redy Irawan; Atus Buku; Yusuf Siahaya
Infotekmesin Vol 17 No 2 (2026): Infotekmesin: Juli 2026
Publisher : P3M Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/

Abstract

Swivel joints are an important component in the loading arm system that affects the efficiency of LPG transfer; however, the characteristics of pressure distribution and flow patterns in a 40° style swivel joint with a rotation angle of 45° have not been widely studied. This study aims to analyze the pressure distribution and flow structure using the Computational Fluid Dynamics (CFD) method with the k–ω SST turbulence model. The simulation results show that the flow is in a turbulent regime with a Reynolds number of around 71000 and a Darcy friction factor of 0.035. The pressure distribution is in the range of −0.0293 to 0.0445 Pa, with the maximum pressure concentrated on the outer side of the bend due to the centrifugal effect, while the minimum pressure appears on the inner side of the elbow, which triggers the formation of secondary flow. Streamline visualization shows the formation of a low-intensity Dean vortex without a significant recirculation zone, with a maximum velocity of around 0.244 m/s. The novelty of this research lies in the integrated analysis of pressure distribution and flow structure in a 40° 45° swivel joint style configuration that represents the actual operating conditions of the loading arm. The research results provide a scientific basis for optimizing the swivel joint design to minimize pressure loss and improve the efficiency of the LPG transfer system.

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