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All Journal ILKOMNIKA: Journal of Computer Science and Applied Informatics Journal of Welding Technology Jurnal Mesin Nusantara Sewagati
Dewi, Yulia Puspa
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Aerospace Engineering Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Transportation Other

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Inovasi Mesin Pencacah Kayu untuk Meningkatkan Efisiensi Produksi Gula Merah Tebu pada UMK Gendis Jaya Arif, Saiful; Sektiono, M Wisnu Arif; Bahtiar, Ahmad Dony Mutiara; Cahyono, Hiding; Dewi, Yulia Puspa; Hamidah, Fitria Nur
Sewagati Vol 9 No 2 (2025)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j26139960.v9i2.2591

Abstract

Gula merah tebu (reddish brown sugar) merupakan komoditas bahan baku pangan untuk kebutuhan konsumsi lokal maupun industri, yang diproduksi skala usaha mikro dan kecil (UMK) Gendis Jaya. Peneningkatkan efisiensi produksi di UMK Gendis Jaya dilakukan dengan penerapan mesin pencacah kayu. Mesin ini dirancang untuk menghasilkan bahan bakar alternatif yang berukuran seragam, sehingga mendukung kestabilan api selama pemasakan air nira tebu. Hasil implementasi mesin memberikan pengaruh terhadap durasi pemasakan berkurang dari 3 jam menjadi 2,5 jam, dengan peningkatan frekuensi produksi harian dari 4 menjadi 5 kali. Kapasitas produksi meningkat dari 11 kwintal menjadi 12 kwintal per hari. Selain itu, kualitas gula merah menjadi lebih konsisten, dan limbah bahan bakar berkurang hingga 30%. Sosialisasi dan pelatihan pengoperasian mesin diberikan kepada mitra memastikan karyawan UMK Gendis Jaya dapat mengoperasikan alat dengan baik, meminimalisir kesalahan operasional. Implementasi teknologi ini tidak hanya meningkatkan efisiensi dan kualitas produk gula merah tebu, tetapi juga mendukung pengembangan industri UMK Gendis Jaya.
ANALISA THERMOELECTRIC TEC UNTUK MENINGKATKAN MASSA OKSIGEN O2 PADA PROSES PEMBAKARAN MOTOR BAKAR Khalida, Zulfa; Rahmad, Hadi; Dewi, Yulia Puspa; Dewi, Kartika Chandra; Putranti, Eti
Jurnal Mesin Nusantara Vol 8 No 2 (2025): Jurnal Mesin Nusantara
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/jmn.v8i2.23548

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh penggunaan Thermoelectric Cooler (TEC) sebagai sistem pendingin udara masuk terhadap performa mesin sepeda motor 110 cc. Sistem TEC dipasang pada saluran intake manifold dan diuji menggunakan dynamometer test untuk membandingkan karakteristik mesin pada kondisi dengan dan tanpa pendinginan udara masuk. Parameter yang dianalisis meliputi daya, torsi, dan Air Fuel Ratio (AFR). Hasil pengujian menunjukkan bahwa pendinginan udara masuk menyebabkan penurunan nilai AFR sebesar sekitar 4,8%, yang mengindikasikan peningkatan densitas udara dan massa oksigen yang masuk ke ruang bakar. Perubahan tersebut berkontribusi pada peningkatan performa mesin, dengan daya maksimum mencapai 6,58 HP pada putaran 5600 rpm, atau meningkat sekitar 1,8 HP dibandingkan kondisi tanpa penggunaan TEC. Namun demikian, efektivitas pendinginan masih dibatasi oleh tingginya kecepatan aliran udara masuk, sehingga diperlukan pengembangan desain sistem pendingin yang lebih optimal pada penelitian selanjutnya.
Current progress on wire-arc and welding-based additive manufacturing with its potential application: a review Dioktyanto, Mudzakkir; Abdullah, Hidayat; Dewi, Yulia Puspa; Rokhim, Imam Nur; Kuswanto, Teguh Junian
Journal of Welding Technology Vol 7, No 2 (2025): December
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jowt.v7i2.8418

Abstract

Wire-Arc Additive Manufacturing (WAAM) is one of the leading metal additive manufacturing procedures for producing medium to large-scale components due to its high deposition rate, low material cost, and compatibility with common structural alloys. This paper review provides a focused and critical assessment of welding-based Additive Manufacturing (AM) technologies, particularly WAAM processes utilizing Gas Metal Arc Welding (GMAW), Gas Tungsten Arc Welding (GTAW), and Plasma Arc Welding (PAW). The scope covers the fundamental process principles, thermal–metallurgical behaviour, mechanical performance, and deposition control methods. The specific contribution of this review is: (i) explaining key process–structure–property relationships documented in recent studies, (ii) identifying core technological barriers—such as thermal distortion, porosity, residual stresses, and anisotropic microstructures—that limit industrial deployment, and (iii) outlining strategic future research directions that important for improving process stability and weld results. Key findings indicate that heat input management governs bead morphology, cooling rate, phase formation, and residual stress accumulation across multi-layer builds. Advances such as adaptive arc modes, interpass temperature control, closed-loop sensing, and hybrid subtractive–additive workflows have shown significant reductions in geometric deviation and defect formation. Nevertheless, reproducibility, dimensional accuracy, and mechanical property predictability remain persistent challenges. Overall, the review shows that integrating real-time monitoring, predictive simulation, alloy design tailored for WAAM, and intelligent control systems represents the most impactful pathway toward achieving certified and industrial-grade components.
Naive Bayes Predictive Model for Failure Detection in CODLAG Propulsion Systems Rokhim, Imam Nur; Kuswanto, Teguh Junian; Dioktyanto, Mudzakkir; Abdullah, Hidayat; Dewi, Yulia Puspa
ILKOMNIKA Vol 8 No 1 (2026): Volume 8, Number 1, April 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28926/ilkomnika.v8i1.831

Abstract

This study implements a Naive Bayes Classifier algorithm to detect failures in gas turbines operating within a CODLAG (Combined Diesel-Electric and Gas) propulsion system. The complexity of hybrid propulsion systems necessitates reliable data-driven monitoring methods to support early anomaly detection and predictive maintenance. An open-access dataset from Kaggle was utilized as the source of gas turbine operational data, with five key parameters (GTn, T48, ṁf, P1, and P2) selected due to their strong correlation with turbine thermodynamic performance. Following data preprocessing and an 80:20 train–test split, the model was trained to classify operating conditions into Normal and Faulty states. The evaluation results demonstrate an accuracy of 86.89%, accompanied by high precision and recall values, indicating the model’s capability to identify anomalies with minimal misclassification. Furthermore, the Receiver Operating Characteristic (ROC) curve yields an Area Under the Curve (AUC) of 0.96, reflecting strong discriminative performance. These findings confirm that the Naive Bayes approach is computationally efficient and suitable for real-time implementation within shipboard Condition-Based Monitoring (CBM) systems, thereby enhancing the reliability and operational efficiency of CODLAG propulsion systems.
Co-Authors Abdullah, Hidayat Ahmad Dony Mutiara Bahtiar, Ahmad Dony Mutiara Cahyono, Hiding Dewi, Kartika Chandra Dioktyanto, Mudzakkir Fitria Nur Hamidah, Fitria Nur Kuswanto, Teguh Junian Putranti, Eti Rahmad, Hadi Rokhim, Imam Nur Saiful Arif Sektiono, M Wisnu Arif Zulfa Khalida