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All Journal Jurnal Teknik Industri USU Jurnal Sistem Teknik Industri
Nazaruddin Matondang
Universitas Sumatera Utara
Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering

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USULAN MODEL DALAM MENENTUKAN RUTE DISTRIBUSI UNTUK MEMINIMALKAN BIAYA TRANSPORTASI DENGAN METODE SAVING MATRIX DI PT. XYZ Ririn Rahmawati; Nazaruddin Matondang; Rahmi M Sari
Jurnal Teknik Industri USU Vol 5, No 2 (2014): JURNAL TEKNIK INDUSTRI USU
Publisher : Departemen Teknik Industri Universitas Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (670.64 KB)

Abstract

Route distribution of a product constituting the order dismissal successive against branches and planning process from point of origin (a company) to the point of consumption (consumers) to fulfill its best customers turn. Pt. Xyz. Is the company in the sectors production snacks. Area their distribution over all the agent scattered in town medan. In medistribusikan of PT. XYZ sued for could design performance shipping reliable, while in fulfillment of a target there are still problems of companies are in distribution products. The process of product distribution in once product delivery only done to one retailing. Distribution products improper in determining route distribution to customers and without seeing former capacity of conveyance resulting in path traveled inefficient. This research berujuan to get route distribution by using centrifugal savings matrix that integrates any muaraangke supply facilities (csf) to distribution canter (d.c.) considering capacity conveyance and means of transportation owned company and to get route distribution efficient with optimize the mileage distribution minimize the use of conveyance; minimizing a charge required by the company and get time distribution feasiable. In distribution system beginning, PT. XYZ send to 14th outlet/day with the mileage 521,600 km and fund of rp. 847.600 and 5 fruit conveyance. By using the method saving matrix produce sub-division route less than route distribution company, applied where sub-division route proposal ' s 7 sub-division routes, produce a greater minimum with thrift distance of 193,7 km can save cost distribution rp. 309.725,- and matrix raise a total time distribution car conveyance of 1193,554 minutes with total car conveyance allocated about three units. Distribution system proposal can save distance of 37,1% and can save the transportation of 36,5 %.
Production Process Quality Inspection with Machine Learning Approach Ari Pradana; Nazaruddin Matondang; Anizar Anizar
Jurnal Sistem Teknik Industri Vol. 27 No. 4 (2025): JSTI Volume 27 Number 4 September 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i4.21005

Abstract

Technological developments in the industrial world encourage innovation in the inspection process, one of which is the application of artificial intelligence with machine learning. CV. XYZ is a palm oil machine component fabrication workshop that still applies manual quality inspection. Manual inspections are prone to errors, depend on human skills, and take a long time. This research aims to develop an automated inspection system using the YOLO (You Only Look Once) model which is a convolutional neural network (CNN) based algorithm for product defect detection. The manual inspection used is considered inconsistent, error-prone, and time-consuming. The use of machine learning is able to identify product defects such as geometry defect, porous defect, and surface defect. Evaluation of model performance using confusion matrix, loss graph, and precision recall curve. The results obtained show that the model has detection accuracy with a mAP50-95 value of 74.5%, mAP50 of 88.5%, and detection time of 0.0084 seconds per image.
The Use of Machine Learning Algorithms for Supply Chain Optimization at PT. XYZ Diomen Syahputra Manik; Nazaruddin Matondang; Nismah Panjaitan
Jurnal Sistem Teknik Industri Vol. 28 No. 1 (2026): JSTI Volume 28 Number 1 January 2026
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v28i1.22207

Abstract

Increased demand fluctuations pose a major challenge in supply chain management, particularly in the fast-food beverage industry like PT. XYZ. This research aims to build and evaluate a demand forecasting model based on machine learning, considering multivariate variables such as product price, seasonal trends, weather, per capita income, population, and historical sales data. The three algorithms used are Random Forest Regressor, Gradient Boosting Regressor, and Prophet Time Series Model. This research method employs a quantitative approach with descriptive-predictive analysis based on time-series data. Model evaluation was conducted using MAE, MSE, RMSE, and MAPE metrics. The research results indicate that Prophet has the highest accuracy (MAPE: 2.33%) and excels in capturing seasonal trends, while Random Forest ranks second (MAPE: 2.47%) with an advantage in comprehensively handling multivariate variables. Gradient Boosting yields the lowest accuracy (MAPE: 2.70%). The conclusion of this study recommends the use of Prophet for short-term seasonal-based predictions, while Random Forest is more suitable for medium to long-term strategic planning. The combination of the two has the potential to become an accurate and adaptive hybrid approach for optimizing the demand forecasting system at PT. XYZ.
Bobabox SME Development Strategy Based on the Influence of Supply Chain Resilience Variables on Company Performance Dhede Pristi Afrinda; Nazaruddin Matondang; Juliza Hidayati
Jurnal Sistem Teknik Industri Vol. 27 No. 4 (2025): JSTI Volume 27 Number 4 September 2025
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v27i4.22904

Abstract

Supply chain resilience refers to the capacity of a supply chain to develop adequate responsiveness, readiness, and recovery strength so it can handle risks and disruptions and restore its operations to their previous condition or achieve an even better state. Bobabox faced challenges such as fluctuating sales, the closure of six outlets, shifting customer demand, and increasing competition. This study involved 81 boba drink outlets in Medan using purposive sampling. Data were collected through questionnaires and an interview with the Bobabox CEO, then analyzed using Smart-PLS 4 to test relationships between variables. SWOT and QSPM methods were applied to formulate strategies. The findings show that supply chain resilience significantly influences company performance. The IE matrix placed Bobabox in quadrant V (hold and maintain), suggesting that the company should preserve its current market position and focus on efficiency rather than aggressive expansion. The study identified 11 internal factors (IFE score: 2.73636) and 8 external factors (EFE score: 2.67857). The SWOT matrix produced nine alternative marketing strategies. Based on the QSPM results, the most recommended strategy is reducing supplier dependency through multi-sourcing to mitigate geopolitical risks (W2, T3).
Optimization of Fiber to the Home Network Using a Genetic Algorithm in Medan Simon Rioland Simanjuntak; Nazaruddin Matondang; Nurhayati Sembiring
Jurnal Sistem Teknik Industri Vol. 28 No. 3 (2026): JSTI Volume 28 Number 3 July 2026
Publisher : TALENTA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32734/jsti.v28i3.24133

Abstract

Urban GPON FTTH planning must jointly manage feeder length and limited optical cores. This study develops a two-stage planning framework for a real GPON FTTH network in Medan, Indonesia. A road-constrained graph and Genetic Algorithm (GA) with a set-cover decoder are used to select and order closures; a closure-level pre-splitter power-margin rule then screens locations for splitter 1:2 deployment. This coordinated route-splitter evaluation is the study's main contribution because it links spatial routing with core-use decisions rather than treating them separately. The GA used 80 individuals, 100 generations, tournament selection, ordered crossover (0.90), and swap/segment-shuffle mutation (0.15). The resulting 7.02-km feeder covered all 29 service areas through nine closures and was 6.4% and 15.4% shorter than the two existing routes (7.50 and 8.30 km). Seven closures met the 2.45-dB pre-splitter margin rule; applying splitter 1:2 only at those locations reduced core requirements from 216 to 121 (43.98%), which fits the available 144-core feeder capacity and leaves 23 cores for expansion. The framework provides a repeatable decision-support method for urban FTTH planning; field power measurements and cost constraints should be included before construction.
Co-Authors Anizar Anizar Ari Pradana Dhede Pristi Afrinda Diomen Syahputra Manik Juliza Hidayati Nismah Panjaitan Nurhayati Sembiring Rahmi M Sari Ririn Rahmawati Simon Rioland Simanjuntak