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All Journal OPERATION EXCELLENCE: Journal of Applied Industrial Engineering Angkasa: Jurnal Ilmiah Bidang Teknologi MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Brahmana : Jurnal Penerapan Kecerdasan Buatan Journal of Industrial Engineering and Operation Management (JIEOM)
Fakhri Ikhwanul Alifin
Department Of Industrial Engineering, Universitas Singaperbangsa Karawang
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Industrial & Manufacturing Engineering

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Quality improvement of food products using taguchi method: a study in a bread product SME Alifin, Fakhri Ikhwanul; Rahma, Rana Ardila; Sadidan, Ikhwanussafa; Fitriani, Risma
Operations Excellence: Journal of Applied Industrial Engineering Vol. 15, No. 2, (2023): OE July 2023
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2023.v15.i2.078

Abstract

Quality is one of the most crucial factors for manufactured products. Good product quality will increase customer loyalty and hence, higher profit for the company. SR company is a local Small Medium Enterprise (SME) in Bandung that produces bread products. Among various kinds of bread, Kadet is the main product with an average production of approximately 1000 pcs per day. In addition, Kadet bread has numerous defective products with an average of 3%-5% per 1000 pcs. Moreover, Kadet is a product baked at high temperatures, and hence, the timing of the production staff is crucial to prevent defectiveness. In this work, we use the Taguchi method to obtain factors that produce defectiveness and the combination of the optimal production factors. Furthermore, using the Analysis of Variance, the results show the optimal process design for minimum defective Kadet bread products as the process evaluation for better product quality. 
PENERAPAN METODE SILVER MEAL UNTUK OPTIMALISASI PERSEDIAAN BAHAN BAKU ARM REAR BRAKE KYEA PADA PT XYZ Rahayu, Octavia; Winarno, Winarno; Alifin, Fakhri Ikhwanul
Journal of Industrial Engineering and Operation Management (JIEOM) Vol 8, No 1 (2025)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jieom.v8i1.16772

Abstract

Perkembangan pesat industri otomotif di Indonesia mendorong peningkatan produksi dan kebutuhan suku cadang, termasuk di PT XYZ, perusahaan manufaktur stamping logam. Salah satu tantangan spesifik yang dihadapi adalah kurangnya metode perencanaan kebutuhan material yang tepat dalam mengelola persediaan bahan baku plat SPCC, sehingga sering terjadi overstock atau out of stock yang menghambat produksi dan memperlambat turnover inventory. Selain itu, fluktuasi permintaan dan kurang optimalnya penentuan ukuran lot menyebabkan biaya penyimpanan yang tinggi dan potensi terjadinya kelebihan stok. Penelitian ini bertujuan mengoptimalkan pengendalian persediaan bahan baku dengan metode Silver Meal, sebuah teknik lot sizing untuk menekan biaya persediaan rata-rata per periode. Analisis menunjukkan bahwa meskipun perusahaan belum menerapkan metode ini, potensi efisiensi yang ditawarkan sangat signifikan. Dengan penerapan metode Silver Meal, ditemukan ukuran lot optimal untuk 11 periode yang mampu menghemat biaya sebesar 0,031% atau Rp430.450. Selain itu, metode ini secara efektif mengurangi biaya penyimpanan hampir hingga nol setiap bulannya. Oleh karena itu, metode Silver Meal diharapkan dapat membantu PT XYZ dalam meminimalkan biaya persediaan dan meningkatkan efisiensi operasional.Kata Kunci: Silver Meal, Pengendalian Persediaan, Ukuran Lot, Fluktuasi Permintaan, PT XYZ, Efisiensi Biaya.
Occupational Safety And Health Risk Analysis (K3) Using The HIRADC Method On Cleaning service Workers In The Health Segment Damayanti, Silvianah; Alifin, Fakhri Ikhwanul
MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Vol 6 No 1 (2024): Motivection : Journal of Mechanical, Electrical and Industrial Engineering
Publisher : Indonesian Mechanical Electrical and Industrial Research Society (IMEIRS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46574/motivection.v6i1.306

Abstract

The healthcare industry is one of the industries that has a high risk of accidents and disease infection. Thus, the workers in this segment are vulnerable and require strict work rules to avoid the risks. The purpose of this study is to provide recommendations for preventive measures to reduce the risks faced by cleaning service workers in the health sector. Furthermore, the object of this study is an outsourcing company that provides cleaning service workers for several hospitals or healthcare institutions. The focus of this study includes i) identifying potential hazards, ii) risk assessments, and iii) risk control recommendations by using the HIRADC (Hazard Identification Risk Assessment and Determining Control) method. This study utilized primary information obtained through observation and interviews with the company's HSE (Health, Safety, and Environment) and samples from cleaning service workers in Indonesia. According to the results, the study found 15 medium risks and 19 low risks. Since several work accidents occurred to the cleaning services workers, it is still important to carry out appropriate risk control in the form of preventive measures to reduce the risks faced by workers, despite the medium and low-risk levels found in the company.
A User-oriented UI/UX Application Design Using The Integration of Quality Function Deployment (QFD) and Design Thinking Methods Koswara, Robby; Alifin, Fakhri Ikhwanul
MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering Vol 6 No 1 (2024): Motivection : Journal of Mechanical, Electrical and Industrial Engineering
Publisher : Indonesian Mechanical Electrical and Industrial Research Society (IMEIRS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46574/motivection.v6i1.308

Abstract

UI / UX is essential in designing an application or website due to its impact on the user. With a decent and user-oriented UI/UX, users will experience high conformance and interact easily with the application or website, hence increasing the intensity of product usage and providing a better experience for users. However, the users' requirements are often neglected, making it difficult for the applications or websites to obtain a constant user number. Furthermore, this research aims to create a novel method to design UI/UX for CRM, which aligns with the needs and specifications of users. The data are collected using primary data through direct observation and questionnaires at an IT company called Numazu and its users. These data aim to measure and determine user needs and expectations by the integration of the Design Thinking and Quality Function Deployment (QFD) method. This research contributes to creating innovative and user-relevant UI/UX design methods, especially for CRM systems. The findings of this research also show an improvement in user experience through a user-oriented UI/UX design.
Performa Model YOLOv8 untuk Deteksi Kondisi Mengantuk pada pengendara mobil Armin, Edmund Ucok; Edra, Anggun Purnama; Alifin, Fakhri Ikhwanul; Sadidan, Ikhwanussafa; Sary, Indri Purwita; Latifa, Ulinnuha
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 5, No 1 (2023): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v5i1.279

Abstract

Driving while drowsy is identified as a significant risk factor in traffic accidents, yet awareness of this risk is often lower compared to other hazards. Phenomena such as microsleep have been shown to increase the risk of inattention and accidents on the road. This study proposes a novel approach utilizing Deep Learning, specifically YOLOv8, to detect and address the risk of driver drowsiness. To train the model, the researchers employed a secondary dataset consisting of 3708 images, partitioned into 80% for model training and 20% for validation. Multiple models were compared during the training process, and the results indicated that the YOLOv8 model outperformed previous models, achieving a recall value of 0.95261, precision of 0.94655, F1-SCORE of 0.9496, and mAP of 0.98055. This research contributes to the development of more effective drowsiness detection systems using Deep Learning approaches, with promising evaluation results.
Pemanfaatan Machine Learning untuk Memprediksi Kandungan Dissolved Oxygen (DO) pada Air Sungai Menggunakan Metode Decision Tree Regressor (DTR) dan Support Vector Regressor (SVR) Sadidan, Ikhwanussafa; Sari, Gina Lova; Armin, Edmund Uncok; Alifin, Fakhri Ikhwanul; Bunga, Venny Ulya
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 5, No 1 (2023): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v5i1.280

Abstract

Water quality is a key factor in maintaining a healthy river ecosystem and supporting the life of aquatic organisms. The measurement of Dissolved Oxygen (DO) content in water is one of the crucial parameters that assess the level of dissolved oxygen, directly influencing the life of aquatic organisms. This study aims to predict the Dissolved Oxygen (DO) content in the Citarum River Irrigation Area by employing Support Vector Regression (SVR) analysis and Decision Tree Regressor. The predictive model was developed by analyzing the relationship between other water quality parameters such as Chemical Oxygen Demand (COD), Biological Oxygen Demand (BOD), and temperature. The analysis results indicate that the accuracy score of the Decision Tree Regressor analysis is superior to that of the Support Vector Regression (SVR) analysis.
Preventive Maintenance Analysis Based on Mean Time Between Failure (MTBF) and Mean Time to Repair (MTTR) Alfionita, Silvana; Alifin, Fakhri Ikhwanul
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 15, No 2 (2023): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/angkasa.v15i2.1833

Abstract

A company's ability to meet its goals depends heavily on the smooth operation of its production process. To ensure that the production machinery operates smoothly and without any breakdowns, it is essential to implement effective maintenance that addresses any issues related to the equipment. This research aims to identify the root causes of equipment failure in the soda and dolomite bucket elevator by analyzing the Mean Time Between Failure (MTBF), Mean Time to Repair (MTTR), and conducting a qualitative evaluation using Failure Mode Effects Analysis (FMEA). The analysis reveals that the company performs preventive maintenance every 3 days, which is more frequent than the optimal schedule of once every 33 days. This suggests that the company may be addressing unforeseen failures. The FMEA analysis indicates that the highest Risk Priority Number is associated with suboptimal maintenance of the Staff. To address this issue, the company can use Radio-Frequency Identification (RFID) technology.
Co-Authors Alfionita, Silvana Armin, Edmund Ucok Armin, Edmund Uncok Damayanti, Silvianah Edra, Anggun Purnama Fitriani, Risma Gina Lova Sari Ikhwanussafa Sadidan, Ikhwanussafa Koswara, Robby Latifa, Ulinnuha Rahayu, Octavia Rahma, Rana Ardila Sary, Indri Purwita Venny Ulya Bunga Winarno Winarno