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Teknologika
Published by Sekolah Tinggi Teknologi Wastukancana Purwakarta
ISSN : 16932978     EISSN : 27154645     DOI : https://doi.org/10.51132/teknologika.v12iNo%202
Core Subject : Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering Mechanical Engineering Other
Jurnal Teknologika adalah wadah informasi berupa hasil penelitian, studi kepustakaan maupun tulisan ilmiah yang terkait bidang ilmu Teknik Informatika, Teknik dan Manajemen Industri, Teknik Mesin dan Teknik Tekstil. Terbit dua kali setahun pada bulan Mei dan November. Artikel Jurnal Teknologika dalam versi cetak telah di-online-kan menggunakan Open Journal System (OJS)
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 282 Documents
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Sistem IoT Dan Kecerdasan Buatan Terintegrasi Untuk Optimalisasi Kondisi Lingkungan Kandang Ayam Closed House Deden Komaludin; Hadi Sofyan
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.446

Abstract

Gas paparan amonia (NH?) dalam kandang ayam close house dapat menurunkan produktivitas dan meningkatkan mortalitas ayam boiler. Penelitian sebelumnya telah mengembangkan sistem IoT untuk menjaga kadar amonia, suhu, dan kelembaban. Namun, sistem tersebut belum dilengkapi dengan mekanisme pengendalian otomatis berbasis kecerdasan buatan (AI)..Lingkungan kandang ayam close house yang tidak terkontrol dapat meningkatkan kadar amonia (NH?) dan memicu stres termal pada ayam boiler, menurunkan produktivitas hingga 15%. Penelitian ini sistem IoT berbasis kecerdasan buatan (AI) untuk mengembangkan dan mengendalikan kadar amonia, suhu, serta kelembaban secara otomatis. Penelitian ini bertujuan untuk mengembangkan sistem IoT yang terintegrasi dengan pembelajaran mesin algoritma untuk memprediksi kadar amonia dan mengoptimalkan ventilasi serta pemberian pakan secara otomatis. Metode yang digunakan meliputi pengumpulan data secara real-time menggunakan sensor MQ135, DHT22, dan sensor oksigen, serta penerapan algoritma Random Forest untuk analisis prediktif. Sistem terdiri dari jaringan sensor MQ135 (amonia), DHT22 (suhu/kelembaban), dan ESP32 sebagai pengontrol utama, dengan algoritma Random Forest untuk prediksi kenaikan amonia. Hasil uji coba selama 60 hari di kandang komersial menunjukkan akurasi pengukuran 98.7% (RMSE = 0.4 ppm), respon sistem <3 detik, dan penurunan mortalitas ayam sebesar 22%. Sistem ini juga mengoptimalkan konsumsi energi ventilasi hingga 30% melalui mekanisme kontrol berbasis penguatan pembelajaran. Temuan ini membuktikan bahwa integrasi IoT-AI mampu menciptakan lingkungan kandang yang stabil (suhu: 20±1.5°C, NH? <15 ppm) sekaligus meningkatkan efisiensi operasional peternakan
A Dynamic System Model for Multi-Echelon Inventory Policy Optimization Considering Bullwhip Effect and Supply chain Disruptions in the Sport Footwear Industry Dedy Setyo oetomo; Rizky Fajar Ramdhani; Asep Hermawan
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.447

Abstract

This research develops a dynamic system model to optimize inventory policies in multi-echelon supply chains within the sport footwear industry, addressing challenges from the bullwhip effect and supply chain disruptions. The sports footwear sector faces unique inventory management challenges due to complex demand patterns influenced by seasonality, fashion trends, and competitive dynamics. Our comprehensive system dynamics model captures the intricate relationships between four supply chain echelons: retailers, distributors, manufacturers, and raw material suppliers. The model integrates machine learning algorithms—specifically Long Short-Term Memory (LSTM) neural networks—for adaptive demand prediction and employs genetic algorithm optimization to determine optimal inventory parameters under various disruption scenarios. Using real-world data from a leading sports footwear manufacturer, we validated the model under normal operations and three distinct disruption scenarios: raw material shortages (45% reduction for 6 weeks), manufacturing capacity constraints (30% reduction for 8 weeks), and transportation disruptions (doubled lead times for 4 weeks). Results demonstrate that our proposed hybrid model reduces overall inventory costs by 18.7% compared to traditional policies while maintaining a 97.2% service level. The integration of machine learning for demand forecasting reduced prediction errors by 43.6% compared to conventional methods, directly mitigating the bullwhip effect by decreasing the order variability coefficient from 0.89 to 0.61 at the supplier level. Furthermore, the model enhanced supply chain resilience by reducing recovery time by 42% following major disruptions. This research contributes to the theoretical understanding of complex supply chain dynamics and practical applications for inventory management in volatile industries, offering a robust framework for decision-making under uncertainty.
Heat Transfer Fluid Deposit in Retainer of Mechanical Seal Yadi Heryadi; Amri abdulah; Apang Djafar Shieddieque; Dede Ardi Rajab; Heri Suripto; Dibyo Setiawan; Agus Solehudin
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.450

Abstract

Mechanical seals in industrial pumps play a critical role in preventing heat transfer fluid leakage, especially under high-temperature operating conditions. A key component of this system is the seal head, which functions as a compression mechanism through a spring to maintain contact between sealing surfaces. However, the spring's performance can deteriorate due to the accumulation of deposits resulting from prolonged exposure to elevated temperatures, operating pressure, and fluid degradation—ultimately leading to seal failure and fluid leakage. This study aims to investigate the thermal stability of the reservoir fluid Therminol 66 (TM-66) and its impact on seal performance under long-term thermal exposure. The methodology includes direct observation of failed seals, thermogravimetric analysis (TGA) at temperatures of 75, 150, 250, and 350?°C for durations of 3, 6, and 12 hours, and chemical characterization using Fourier Transform Infrared Spectroscopy (FTIR). Additionally, thermal degradation behavior was assessed through activation energy estimation based on weight loss data obtained from TGA. FTIR results revealed that phenylcyclohexane is the dominant compound in TM-66, with a relative intensity of 0.803119. The thermogravimetric data demonstrated that higher temperatures and longer exposure times significantly accelerated fluid evaporation and mass loss. The activation energy analysis confirmed that thermal degradation is more likely to occur under extended high-temperature conditions. These findings highlight the importance of maintaining reservoir fluid temperature below 75°C to minimize deposit buildup in the seal chamber and ensure the long-term reliability and efficiency of the mechanical seal system.
Analisis Pengendalian Kualitas Produk Compound Dengan Model Seven Tools Di PT Velasto Indonesia Farliana Sutartiah; Raqib Zamal; Pandena Kicky Basuki Putri
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.451

Abstract

This study focuses on quality control using the QC Seven Tools method to reduce product defects in compound production at PT Velasto Indonesia, located in Purwakarta Regency. Defective products can lead to increased production costs, decreased customer satisfaction, and reduced competitiveness. Therefore, identifying the root causes of defects and implementing effective control measures are essential. The QC Seven Tools—comprising Check Sheets, Histograms, Pareto Diagrams, Cause-and-Effect Diagrams, Control Charts, Scatter Diagrams, and Flowcharts—are applied to analyze and monitor the production process. This study uses primary data collected from direct observations, interviews with production staff, and company production records. Analysis using the Pareto Diagram revealed that the most frequent defects in compound products were surface roughness, inconsistent texture, and contamination. The Cause-and-Effect Diagram identified potential root causes such as machine malfunctions, operator error, and inconsistent raw material quality. Control Charts were utilized to observe process stability, while Scatter Diagrams helped identify correlations between variables affecting quality.The results showed that implementing corrective actions based on QC tool analysis—such as machine maintenance scheduling, operator training, and supplier quality control—led to a significant reduction in defect rates. This demonstrates that the QC Seven Tools are effective in identifying, analyzing, and resolving quality issues in manufacturing processes. Overall, this study highlights the importance of structured quality control approaches in achieving continuous improvement and operational efficiency. The findings provide practical insights for other manufacturing companies aiming to minimize defects and improve product quality through systematic problem-solving techniques.
Analisis Sifat Konduktivitas Listrik Berbagai Jenis Variasi Elektroda Pensil Grafit Tipe B Eko Sulistio Hanam; Muhammad Rizqan Akbar; Ely Rismawati
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.452

Abstract

Elektroda pensil grafit tipe B memiliki karakteristik dapat menghantarkan listrik lebih mudah dibandingkan tipe F dan H. Pada penelitian ini akan dikaji dan dianalisis sifat dasar dari konduktivitas listrik beberapa variasi pensil grafit tipe B, dianmtaranya B, 2B, 4B, 6B dan 8B. Penelitian ini menggunakan pendekatan kurva karakteristik arus-tegangan yang dimodelkan melalui pencocokan persamaan garis lurus untuk mendapatkan komponen 1/R yang digunakan dalam penentuan konduktivitas listrik sampel uji melalui hukum ohm. Pengukuran konduktivitas listrik dilakukan dengan memasukkan dimensi dari bahan berupa diameter dan panjang sampel uji menggunakan jangka sorong. Hasil penelitian menunjukkan bahwa konduktivitas listrik pada elektroda pensil grafit tipe 8B memiliki konduktivitas listrik yang terbaik diantara seluruh sampel uji yaitu 341.94 S/m. Penelitan ini menunjukkan bahwa semakin tinggi ukuran nomor pada elektroda pensil tipe B, semakin baik konduktivitas listriknya sehingga bahan elektroda tersebut mudah menghantarkan listrik. Ukuran nomor dan tipe yang terdapat pada elektroda pensil grafit menunjukkan konsentrasi grafit yang terdapat pada bahan tersebut sehingga semakin besar nomor pada tipe pensil grafit tipe B maka kandungan grafit akan semakin banyak yang menyebabkan sifat konduktivitas listrik dari bahan pensil semakin meningkat
Line Balancing with Simulation Approach (ProModel) on SMC Big Volume Lane in HA Export Department at PT. XYZ Dewanto Djoko Purwito; Ramlan Yuniar Velani; Diki Muchtar; Suci Tresna Dewi Handayani
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.456

Abstract

This research aims to identify and overcome bottlenecks in production process at PT. XYZ Indonesia, especially in HA Export Department on SMC Big Volume Lane. Bottlenecks were detected in Visual Acc and Housing processes, which resulted in decreased efficiency and productivity. The method used in this study is line balancing with the Pro Model simulation approach, which allows analysis of improvement scenarios without disrupting ongoing operations. Data collected includes process time and machine capacity. Initial simulation results showed significant idle time 15,4%, with accumulation at Raw Material workstation (12.30%), Housing workstation (1.20%), and Visual Acc (1.90%). After the improvements were made, including increasing the Raw Material capacity to 20 pcs, the Housing process to 3 pcs, and Visual Acc to 3 pcs, the bottleneck was successfully eliminated from 15.4% became 0% and the production flow became more stable. This research provides practical solutions to improve efficiency and reduce cycle time, and can be a reference for companies in implementing line balancing and simulation methods to improve productivity in the manufacturing industry.
Bottleneck Analysis in Garment Production Process Using Simulation Approach (ProModel) Diki Muchtar
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.457

Abstract

Garment industry is a labor-intensive manufacturing sector with a complex production flow, highly susceptible to bottlenecks. Unresolved bottlenecks can lead to decreased efficiency, increased waiting times, and reduced productivity. This research aims to analyze bottlenecks in the garment production process using a simulation approach with ProModel software. The research method was carried out using a quantitative-descriptive approach, starting with production system selection, process flow mapping, and simulation model development and testing. The results of the original model simulation show a production output of 1.719 units, with a bottleneck of 3,86% and a cost of USD 38,01. This situation requires improvement, which was achieved through scenario 1, where production capacity at each location was increased, considering a relatively similar cost of USD 41,40. This change reduced the bottleneck to 0,60%, and total production increased to 1.811 units. In scenario 2, with a similar cost, the author recommended further adjustments to the production capacities at the required processes. After conducting the simulation, total production increased to 1.908 units, with a cost of USD 41,42. The simulation using ProModel proved effective in systematically identifying and evaluating bottleneck solutions. This research provides practical recommendations for garment industry management in making data-driven decisions to improve production efficiency. keyword: Bottleneck; Garment Industry; Simulation; ProModel; Production Efficien
Peramalan Permintaan Produk Sosis Menggunakan Metode Peramalan Dekomposisi Akhsani Nur Amalia
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.458

Abstract

PT. PTX merupakan suatu perusahaan manufaktur yang bergerak dalam bidang pangan. Salah satu produk yang diproduksi adalah produk sosis. Dalam proses produksinya, PT. PTX mengalami kendala dalam menentukan prediksi permintaan sosis diwaktu yang akan datang. Akibatnya, Perusahaan harus mengeluarkan biaya yang lebih tinggi akibat permintaan yang tidak terpenuhi ataupun kelebihan produksi. Penelitian ini dilakukan untuk menentukan perkiraan permintaan sosis untuk satu tahhun yang akan datang. Metode yang digunakan adalah metode peramalan dekomposisi. Hal ini dilakukan karena pola data permintaan mengandung musiman dan trend. Hasil peramalan menunjukkan bahwa perkiraan permintaan sosis selama satu tahun yang akan adalah sebeagai berikut (dalam satuan pcs) 136189, 173757, 129528, 140572, 175672, 116092, 143663, 114160, 125031, 154009, 149915, dan 96874.
Analisis Perawatan Mesin dengan Metode Reliability Centered Maintenance (RCM) terhadap Mesin Air Jet Loom (AJL) Yayan Heru Haerudin; Wanwan Jamaludin; Sri Suhartini; Jaenudin
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.459

Abstract

Persaingan dunia industri yang semakin ketat mengharuskan perusahaan untuk mengoptimalkan penggunaan mesin agar dapat meningkatkan produktivitasnya. Terjadinya kerusakan pada mesin dapat memberikan banyak kerugian seperti menurunnya jumlah produksi, pembengkakan biaya, kecelakaan kerja, dan hal-hal yang dapat menimbulkan kerugian besar lainnya. Untuk menjamin pengoptimalan mesin diperlukan adanya suatu skema perawatan mesin. Penelitian ini menggunakan metode Reliability Centered Maintenance (RCM) untuk menganalisis perawatan terhadap mesin Air Jet Loom (AJL). Metode RCM ini dapat menentukan tindakan pemeliharaan yang harus dilakukan agar menjamin peralatan tetap optimal sesuai dengan fungsinya. Hasil menunjukkan adanya 16 mode kegagalan yang terjadi pada mesin AJL, terdapat 12 komponen yang dapat diatasi secara condition direct (CD), Serta 4 komponen mesin AJL lainnya yang dapat ditangani dengan cara Finding Failue (FF). Selain itu, Komponen Kamran merupakan komponen kritis dengan nilai RPN tertinggi sebesar 256, yang berarti bahwa Kamran mengalami kegagalan yang harus ditangani akibat terjadinya downtime yang paling besar.
Sistem Monitoring Parameter Listrik Tiga Fasa Berbasis IoT Dengan Data Logger Untuk Meningkatkan Efisiensi Energi Dayan Singasatia; Minarto; M.Agus Sunandar
Jurnal Teknologika Vol. 15 No. 1 (2025): Jurnal Teknologika
Publisher : Sekolah Tinggi Teknologi Wastukancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51132/teknologika.v15i1.461

Abstract

Penggunaan energi listrik yang efisien dan efektif menjadi sangat penting dalam beberapa tahun terakhir. Listrik sistem tiga fasa memerlukan monitoring yang komprehensif. Dengan meningkatnya kebutuhan energi listrik, pengelolaan energi yang baik menjadi kunci untuk mengurangi biaya dan meningkatkan efisiensi. Sistem monitoring energi listrik tradisional seringkali memiliki keterbatasan dalam hal akurasi dan kecepatan data karena tidak dapat memantau parameter listrik secara real-time sehingga tidak dapat memberikan analisis data untuk mengidentifikasi peluang penghematan energi. Teknologi Internet of Things (IoT) telah memungkinkan pengembangan sistem monitoring energi listrik yang lebih akurat dan dapat diandalkan. Sistem IoT dapat memantau parameter listrik seperti arus, tegangan, daya, dan energi listrik secara real-time.

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