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All Journal Jurnal Teknik Industri MANAJEMEN DEWANTARA Jurnal Transportasi Multimoda
Liane Okdinawati
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Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Transportation

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Adaptation Of The Variable Neighborhood Search Heuristic To Solve The Vehicle Routing Problem Arif Imran; Liane Okdinawati
Jurnal Teknik Industri Vol. 12 No. 1 (2011): Februari
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/JTIUMM.Vol12.No1.10-15

Abstract

The vehicle routing problem is investigated by using some adaptations of the variable neighborhood search (VNS). The initial solution was obtained by Dijkstra’s algorithm based on cost network constructed by the sweep algorithm and the 2-opt. Our VNS algorithm use several neighborhoods which were adapted for this problem. In addition, a number of local search methods together with a diversification procedure were used. The algorithm was then tested on the data sets from the literature and it produced competitive results if compared to the solutions published.
Covid-19 dan Pengaruhnya Terhadap Bisnis Angkutan Logistik di Indonesia Subiakto Soekarno; Liane Okdinawati; Prawira Fajarindra Belgiawan; Dedy Sushandoyo; Oktofa yudha Sudrajad; Harimukti Wandebori; Muhamad Rizki; Umiyatun hayati Triastuti; Dedy Cahyadi; Listantari Listantari; Yessi Gusleni; Win Akustia; Herma Juniati; Elviana R. Simbolon; Herawati Herawati; Rita Pasaribu; Reslyana Dwitasari; Irawati Andriani; Maria Magdalena; Hasriwan putra; Yuveline Aurora; Sugiyanto sugiyanto; Akhmad Rizal Arifudin; Suci Susanti; Marlia Herwening; Anzy Indrashanty; Agung wicaksono
Jurnal Transportasi Multimoda Vol 18, No 2 (2020): Desember
Publisher : Puslitbang Transportasi Antarmoda-Kementerian Perhubungan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3721.059 KB) | DOI: 10.25104/mtm.v18i2.1719

Abstract

Pandemi COVID-19 membuat masyarakat mengurangi aktivitas ekonomi, seperti berbelanja kebutuhan tersier atau berlibur. Penerapan Pembatasan Sosial Berskala Besar (PSBB) di DKI Jakarta yang sudah berjalan dan disambut positif oleh masyarakat, dimana bidang logistik merupakan salah satu sektor yang dikecualikan dalam aturan PSBB sehingga dapat dengan leluasa melakukan distribusi dengan tetap mengikuti protokol COVID-19. Walaupun sektor logistik mendapat pengecualian pada masa PSBB ini, dari sisi arus pengiriman barang dalam negeri maupun skala ekspor sayangnya mengalami tren penurunan. Oleh karena itu penelitian ini mencoba melihat bagaimana dampak COVID-19 dan pengaruhnya terhadap angkutan logistik. Penelitian ini juga ingin melihat apakah angkutan logistik yang dikecualikan dalam PSBB memiliki pengaruh pada meluasnya penyebaran COVID-19. Data-data dari Badan Pusat Statistika dan wawancara beberapa pelaku logistik dipergunakan untuk melihat pengaruhnya terhadap keberlangsungan bisnis selama pandemik. Sedangkan, metode regresi linear dipergunakan untuk fokus pada tujuan kedua dari penelitian ini. Berdasarkan analisa yang dilakukan maka diketahui bahwa sektor lapangan usaha transportasi dan pergudangan menunjukkan tanda-tanda pemulihan di kuartal III 2020. Sedangkan berdasarkan regresi linier menunjukan bahwa pergerakan logistik tidak berpengaruh terhadap lonjakan kasus COVID-19.
REDUCING COMPONENTS QUALITY VARIATION USING SIX SIGMA DMAIC METHODOLOGY IN AUTOMOTIVE MANUFACTURING INDUSTRY Taufiq Byomantoro Hanurogo; Liane Okdinawati
MANAJEMEN DEWANTARA Vol 9 No 2 (2025): MANAJEMEN DEWANTARA
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/md.v9i2.20386

Abstract

This research aims to reduce quality defects in cylinder block components supplied to PT. Automotive Manufacturing Indonesia (PT. AMI). In 2024, the company experienced a 4.42% defect rate and a first pass yield (FPY) of 95.01% in its cylinder block machining line, leading to over IDR 17 billion in losses. Defects such as leakage and porosity were only detected after further machining, indicating weaknesses in the supplier’s casting and inspection processes. The study applies the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) methodology to identify root causes, reduce variation, and improve product quality. The objective is to lower the defect rate to below 2%, increase FPY, and establish a sustainable quality control approach. The research stages include identifying critical-to-quality (CTQ) factors, analyzing defect trends using statistical tools, evaluating root causes through visual inspection and cross-sectional cuts, and testing improvement actions in trial runs. Results show that improvements such as cooling pin addition and die temperature control led to a significant defect reduction, including a 0% defect rate in ventilation hole leakage after implementation. A monitoring and control plan was established to maintain long-term quality performance. This study demonstrates that Six Sigma can be effectively extended beyond internal processes to supplier-side quality improvement. The findings provide a practical model for other manufacturing firms facing similar challenges, highlighting the importance of structured collaboration, data analysis, and preventive quality control in managing outsourced components.
OPTIMIZING INVENTORY MANAGEMENT THROUGH ADVANCED FORECASTING METHODS AND STRATEGIC STOCKING Wisnhu Purbo Waseso; Liane Okdinawati
MANAJEMEN DEWANTARA ARTICLES IN PRESS (2025)
Publisher : Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/md.v9i3.20520

Abstract

Parts distribution companies face challenges in balancing stock availability and operational cost efficiency. The low Inventory Turnover Ratio (ITR) of 2.46–2.67 in 2024 reflects inefficiencies in inventory planning and control, which leads to high storage costs and slow-moving accumulation of goods. This research aims to identify the root cause and optimal solutions through a mixed method approach. Qualitative data was obtained from semi-structured interviews with demand planners and branch heads, while quantitative data was analyzed using historical data for 2024. Accuracy evaluation was carried out on the Moving Average, Weighted Moving Average, and Exponential Smoothing forecasting methods using MAPE, MAD, RMSE, and Tracking Signal. Current Reality Tree (CRT) is used to map the root of the problem, and ABC classification to focus on high-value parts. The Fixed-Order Quantity (Q) and Fixed-Time Period (P) inventory models were also compared. The results showed that the Weighted Moving Average (6–7 months) and Exponential Smoothing improved the forecasting accuracy by 43.93%. The integration of this method with the Q and P models is able to reduce the risk of overstock and stockout, and results in an annual inventory cost efficiency of 0.33%. The increase in the ITR ratio close to the company's target underscores the importance of using predictive analytics and integrated inventory management systems in supporting operational efficiency and financial performance. This study recommends forecasting optimization and system integration as a strategic step for parts distribution companies.
Co-Authors Akhmad Rizal Arifudin Anzy Indrashanty Arif Imran Belgiawan, Prawira Fajarindra Dedy Cahyadi Dedy Sushandoyo Elviana R. Simbolon Harimukti Wandebori Hasriwan Putra Herawati Herawati Herma Juniati Irawati Andriani Listantari Listantari Maria Magdalena Marlia Herwening MUHAMAD RIZKI Oktofa yudha Sudrajad Reslyana Dwitasari Rita Pasaribu Salsabila, Unik Hanifah Subiakto Soekarno Suci Susanti Sugiyanto Sugiyanto Taufiq Byomantoro Hanurogo Umiyatun hayati Triastuti Win Akustia Wisnhu Purbo Waseso Yessi Gusleni yuveline aurora