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All Journal Jurnal Teknoin OPSI Seminar Nasional Teknik Kimia Kejuangan Heuristic Jurnal Sistem dan Manajemen Industri Jurnal Teknik Industri : Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri INTECOMS: Journal of Information Technology and Computer Science Angkasa: Jurnal Ilmiah Bidang Teknologi Journal of Appropriate Technology for Community Services Enrichment : Journal of Management International Journal of Industrial Optimization (IJIO) Dinamika Kerajinan dan Batik : MAJALAH ILMIAH International Journal of Computer and Information System (IJCIS) International Journal of Multidisciplinary Research and Literature (IJOMRAL) Jurnal Kalibrasi Jurnal Teknologi dan Manajemen Industri Terapan Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika International Journal of Industrial Innovation and Mechanical Engineering
Muhammad Ridwan Andi Purnomo
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Aerospace Engineering Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Optimisation-in-the-loop simulation of multi products single vendor-multi buyers supply chain systems with reactive lateral transhipment Purnomo, Muhammad Ridwan Andi
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.6495

Abstract

Considering that batik is one of the most popular products in Indonesia, it is important to analyse the supply chain system for batik products. In reality, the supply chain system for batik products enables orders between buyers to receive products more rapidly, allowing them to anticipate stock outs and obtain lower ordering costs than when ordering from vendors. It is referred to as reactive lateral transshipment. This paper discusses the development of a simulation-based stochastic optimisation model for a batik product supply chain system with multiproducts and single vendor-multi buyers. The utilised solution searching algorithm is a modified Genetic Algorithms (GA) executed in-loop with the developed simulation-based stochastic model. The results demonstrate that the proposed modified GA is able to provide a global optimum solution, allowing the proposed simulation-based stochastic model to reduce the joint total cost (JTC) of the investigated supply chain system by up to 19% when compared to the local optimisation model in each supply chain party.
Intelligent optimisation for multi-objectives flexible manufacturing cells formation Purnomo, Muhammad Ridwan Andi; Widodo, Imam Djati; Zukhri, Zainudin
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 1 (2024): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i1.7974

Abstract

The primary objective of conventional manufacturing cell formation typically uses grouping efficiency and efficacy measurement to reduce voids and exceptional parts. This objective frequently leads to extreme solutions, such as the persistently significant workload disparity among the manu­facturing cells. It will have a detrimental psychological impact on operators who work in each formed manufacturing cell. The complexity of the problem increases when there is a requirement to finish all parts before the midday break, at which point the formed manufacturing cells can proceed with the following production batch after the break. This research examines the formation of manufacturing cells using two widely recognized intelligent optimization techniques: genetic algorithm (G.A.) and particle swarm optimisation (PSO). The discussed manufacturing system has flexible machines, allowing each part to have multiple production routing options. The optimisation process involved addressing four simultaneous objectives: enhancing the efficiency and efficacy of the manufacturing cells, minimizing the deviation of manufacturing cells working time with the allocated working hours, which is prior to the midday break, and ensuring a balanced workload for the formed manufacturing cells. The optimisation results demonstrate that the G.A. outperforms the PSO method and is capable of providing manufacturing cell formation solutions with an efficiency level of 0.86, efficacy level as high as 0.64, achieving a minimum lateness of only 24 minutes from the completion target before midday break and a maximum difference in workload as low as 49 minutes.
Implementasi Sistem Business Intelligence Berbasis RFM Extended Untuk Segmentasi Toko Ritel Batik Muhamad Kaswa; Muhammad Ridwan Andi Purnomo; Demas Emirbuwono Basuki
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 5 No. 2 (2026): Jurnal Teknologi dan Manajemen Industri Terapan
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v5i2.1582

Abstract

Persaingan bisnis ritel batik yang semakin ketat menuntut pelaku usaha untuk memahami karakteristik pelanggan secara lebih mendalam agar strategi pemasaran dapat dilakukan secara tepat sasaran. Penelitian ini bertujuan untuk menganalisis perilaku pelanggan dan segmentasi pasar menggunakan RFMLC (Recency,Frequency,Monetary,Lifetime,Channel) pada data transaksi pelanggan toko ritel batik yang mencakup waktu transaksi terakhir, frekuensi pembelian, nilai transaksi, lama hubungan pelanggan dengan toko, serta saluran pembelian yang digunakan. Variabel R,F,M dan L dihitung berdasarkan historis pembelian, sedangkan variabel C meprensentasikan saluran pembelian utama pelanggan. Analisis K-Means Clustering diterapkan secara visual untuk menampilkan scatter plot pelanggan berdasarkan skor RFMLC, sehingga memudahkan identifikasi pola distribusi dan konsentrasi pelanggan dengan karakteristik serupa. Hasilnya menunjukkan pola pembelian yang jelas, dan variabel channel tetap dapat memberikan informasi tambahan mengenai saluran pembelian dominan tiap pelanggan. Analisis ini membantu toko ritel batik dalam memahami perilaku pelanggan dan merancang strategi pemasaran yang lebih tepat sasaran, sehingga pemilik usaha dapat merancang strategi pemasaran, promosi, dan pelayanan yang lebih efektif sesuai dengan karakteristik masing masing segmen pelanggan agar mampu meningkatkan loyalitas pelanggan dan kinerja penjualan secara berkelanjutan.
A Systematic Literature Review of Predictive Maintenance Strategies Using RUL and GRU for Industrial Packaging Machines Dendi Permana; Muhammad Ridwan Andi Purnomo
Jurnal Kalibrasi Vol 24 No 1 (2026): Jurnal Kalibrasi
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/kalibrasi/v.24-1.3252

Abstract

Predictive Maintenance is a key strategy in improving asset reliability and efficiency in the era of Industry 4.0. However, most existing approaches rely on sensor data, making them difficult to implement in companies that do not yet have sensor infrastructure. This study presents a systematic literature review (SLR) of predictive maintenance approaches based on Remaining Useful Life (RUL) and Gated Recurrent Unit (GRU), focusing on their potential application in vertical liquid packaging machines in the food industry. The review was conducted on 25 articles from 2017 to 2024 using the PRISMA 2020 guidelines. The results show that the majority of studies are still sensor-based and focus on heavy industry, while studies utilizing non-sensor historical data are still very limited. In addition, the RUL-GRU hybrid approach is only found in a small number of studies and has never been applied in the context of the food processing industry. This study contributes by mapping these research gaps and formulating a conceptual framework for the application of RUL-GRU-based predictive maintenance using non-sensor historical data. These findings provide a scientific basis for the development of data-based maintenance strategies in companies with limited sensor infrastructure.
Implementation of Lean Technique to Improve Efficiency in Quail Egg Farming Rafly Galih Saputra; Muhammad Ridwan Andi Purnomo
JTI: Jurnal Teknik Industri Vol 11 No 1 (2025): JUNI 2025
Publisher : Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/jti.v11i1.37297

Abstract

The quail farming industry in Indonesia has recently experienced significant growth, which has led to an increase in demand for quail eggs. This shows substantial challenges in quail egg farming, namely low operational efficiency and high levels of waste in the production process. This study aims to improve operational efficiency by reducing waste in a quail egg farming production at CV. Vigaza uses lean manufacturing and the theory of constraints. Lean tools such as value stream mapping, waste assessment model, and value stream analysis tools are applied to identify the dominant wastes. The theory of constraints is used to determine the root cause using the current reality tree. The process activity value-added ratio has improved from 60.73% to 68.91%, lead time has decreased from 12.1 to 10.99 days, and the defect rate has reduced from 0.68% to below 0.5%. Overproduction is recommended to align production with the market demand rather than the production cycle. Integrating the lean method and the constraint theory effectively reduced waste in a small-scale agricultural production, a quail egg farm. These findings suggest a potential for adopting lean techniques in the agricultural sector in Indonesia. Keywords: Lean Manufacturing, Value Stream Mapping, Waste Assessment Model, Value Stream Analysis Tools, Theory of Constraints
A genetic algorithm-based predictive–reactive scheduling for no-wait flow shop with sequence-dependent setup times under dynamic job arrivals Muhammad Ridwan Andi Purnomo; Azmi Hassan
Jurnal Sistem dan Manajemen Industri Vol. 10 No. 1 (2026): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v10i1.11538

Abstract

Modern electronics controller manufacturing operates in highly dynamic environments where production schedules must rapidly adapt to newly arriving customer orders while maintaining production efficiency and delivery performance. However, conventional predictive scheduling alone is often insufficient because schedule revisions are required for unexpected order arrivals, which may increase production completion time and customer lateness. Therefore, this study aims to develop a two-stage predictive–reactive scheduling framework for a no-wait flow shop with sequence-dependent setup times (SDST), involving 20 initial jobs with varying release times and 7 dynamically arriving jobs with distinct due dates. In Stage 1, a Genetic Algorithm (GA) is employed to maximize the number of initial jobs completed before a 300-minute production cut-off, establishing a predictive baseline schedule. In Stage 2, the proposed GA performs reactive rescheduling by integrating the unprocessed initial jobs with the newly arriving jobs to minimize the makespan deviation from the predictive schedule and reduce the new jobs’ lateness. Based on a case study, the results demonstrate that the proposed model and GA optimization effectively balance schedule stability and responsiveness. The results show that while reactive rescheduling introduces a makespan deviation of 183-time units, incoming job lateness is substantially reduced, providing a trade-off between operational continuity and service-level performance.
Lime Saturation Factor as a Determinant of Free Lime Content in Portland Cement Clinker: A Machine Learning-Based Preventive Quality Control Study Andi Muhammad Fadhlurrahman; Muhammad Ridwan Andi Purnomo
International Journal of Industrial Innovation and Mechanical Engineering Vol. 3 No. 3 (2026): August: International Journal of Industrial Innovation and Mechanical Engineeri
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijiime.v3i3.441

Abstract

Free lime (FCaO) is the most critical and rapidly available quality indicator of Portland cement clinker, and its control depends on the composition of the raw meal entering the kiln. This study investigates the relationship between the Lime Saturation Factor (LSF) of raw meal as the upstream compositional parameter and clinker FCaO as the downstream quality outcome. A total of 960 valid daily production records collected from Kiln Line V of PT Semen Tonasa, Indonesia (January 2023–December 2025), integrating Distributed Control System (DCS) and laboratory quality-control data, were analyzed using descriptive statistics, Pearson correlation, independent-samples t-tests, quartile-based risk stratification, and supervised machine learning. XGBoost was compared with Linear Regression, Random Forest, and Artificial Neural Network models using 25 process parameters. The mean FCaO was 1.2552% (SD = 0.224), with 12.4% of observations classified as defective (FCaO > 1.5%). LSF showed a significant positive correlation with FCaO (r = +0.295, p < 0.001), and defective batches exhibited significantly higher LSF values than normal batches. Defect frequency increased from 7.5% in the lowest LSF quartile to 22.9% in the highest. XGBoost achieved the best predictive performance (R² = 0.517, MAE = 0.105%, RMSE = 0.144%, MAPE = 8.96%), confirming LSF as an important upstream predictor. The findings demonstrate that raw meal LSF is an interpretable and actionable parameter for preventive clinker quality control and early-warning monitoring before kiln entry.
Optimasi Pengendalian Persediaan obat menggunakan Pendekatan Deep Learning Hybrid LSTM-GRU dan Optimasi Solver: Studi Kasus Apotek Harist Abdillah; Muhammad Ridwan Andi Purnomo
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika Vol. 4 No. 5 (2026): September : Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Inf
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/jupiter.v4i5.1551

Abstract

Pharmacy inventory management faces major challenges in balancing stockout and overstock risks caused by high demand uncertainty and the perishable nature of medicines. Conventional methods such as Reorder Point (ROP) and Economic Order Quantity (EOQ) assume stable demand, making them less responsive to real fluctuations. This study proposes a predict-then-optimize framework that integrates demand forecasting using a Hybrid Long Short-Term Memory–Gated Recurrent Unit (LSTM-GRU) model with a mathematical optimization (Solver) model for inventory control of 146 category-A medicines at Alkafi Pharmacy. Four years of historical sales data were used to train the forecasting model, and the results served as input for a perishable-inventory optimization model that minimizes total ordering, holding, shortage, and expiration costs. Testing on 52 weeks of data showed the Hybrid LSTM-GRU model achieving MAE 1.18, RMSE 5.10, MAPE 17.64%, and R² 0.52, outperforming rolling-mean, seasonal-naive, and naive baselines. Integrating the forecast with the Solver produced an order recommendation of 14,696.64 units against a forecast demand of 28,678.42 units, with zero lost sales, a simulated service level of 100%, and 6,162.80 expired units, markedly better than the manual system, which recorded 6,527.50 lost-sales units and 43,314.25 expired units per year.
Mapping Sustainable Logistics through the DPSIR Framework: A PRISMA-Guided Systematic Literature Review and Evidence Synthesis Case Study: Logistic Service Provider Muhammad Rizqy Abdurrahman Assyifa; Agus Mansur; Elisa Kusrini; Muhammad Ridwan Andi Purnomo
Angkasa: Jurnal Ilmiah Bidang Teknologi Vol 18, No 3 (2026): Agustus
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/angkasa.v18i3.4012

Abstract

This study charts the current state of sustainable logistics by using the Drivers–Pressures–State–Impacts–Responses (DPSIR) framework to a five-year collection of peer-reviewed research, focusing on logistics service providers (LSPs) as the operational facilitators of transportation, storage, and delivery. Eligible records are first categorized into DPSIR schema codes, then integrated into a unified indicator system, and ultimately consolidated to reveal prominent trends and identifiable areas for improvement. The 80-20 retention principle guides a priority rule, where the minimal set of components whose collective impact totals 80 percent is designated as the core signal, and the remaining 20 percent is recorded for transparency without compromising inference. The synthesis shows that digitalization and carbon efficiency act as main drivers, although emissions constraints, transport burdens, and disruption risk remain significant pressures; ongoing effects include energy inefficiency and public health externalities. Effective responses center on sustainable practices that conserve energy, full digital transparency, process refinement, decision-making guided by data, and the ability to recover from disruptions. In this portfolio, Logistic Service Providers have a key function in translating policy goals into actual governance by facilitating data pipelines that can communicate with one another, near-real-time monitoring, and standardized operating procedures among partners. The review provides a plan for implementation that connects results to quantifiable state metrics and feasible responses, enabling the prioritization of high-impact interventions, synchronization of monitoring with policy goals, and phased investment choices under changing constraints, particularly through LSP-led coordination
Co-Authors Agham Satria Pristiwaji Agus Haerudin Agus Haerudin Agus Agus Mansur, Agus Alhabsyi, Feni Silvani P Ali Parkhan Andi Muhammad Fadhlurrahman Apriani, Ratna Agil Azmi Hassan Basuki, Demas Emirbuwono Demas Emirbuwono Basuki Dendi Permana Dhuha Khanif Rizky Dian Janari Digdoyo Oktapriandi Febriani, Atik Harist Abdillah Imam Djati Widodo Kirana, Nabila Lintang Kusrini, Elisa Mei Andrianto Meilinda Fitriani Nur Maghfiroh Muhamad Kaswa Muhammad Rizqy Abdurrahman Assyifa Nashrullah Setiawan Novrianty Rizky Rafly Galih Saputra Rifa'i Rifa'i Rosyid, Yaqub Kasuma Saputro, Iswoyo Seno Sholeh Ma’mun Sri Indrawati Taufiq Immawan, Taufiq Wahyu Sidiq Saputra Zainudin Zukhri