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Sustainable Supply Chain Odyssey: Exploring The Interplay Of Green Technology, Green Transportation, and Green Logistics Digitalization On Green Supply Chain Performance Purnomo, Agus; Bisma, Muhammad Ardhya; Syafrianita, Syafrianita
Dinasti International Journal of Education Management And Social Science Vol. 7 No. 1 (2025): Dinasti International Journal of Education Management and Social Science (Octob
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v7i1.5394

Abstract

The rapid expansion of the courier service industry in Indonesia has resulted in heightened delivery activities, contributing to elevated carbon emissions and diminished logistics efficiency, particularly in last-mile delivery. This situation emphasizes the urgent need for the development of green supply chain strategies that are predicated not only on environmentally sustainable technologies and transportation but also on the support of logistics digitalization. This study seeks to analyze the impacts of Green Technology (GTH) and Green Transportation (GTP) on Green Supply Chain Performance (GSP), while also assessing the mediating role of Green Logistics Digitalization (GLD). A quantitative approach was employed through an explanatory survey utilizing a cross-sectional design. Data were gathered from 341 supervisors of courier companies across eight major provinces in Indonesia and were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 3.0. The findings indicate that both GTH and GTP significantly affect GSP, both directly and indirectly through GLD. GTP exhibited the strongest path coefficient (β = 0.462), followed by GTH (β = 0.350) and GLD (β = 0.295). These results extend the Natural Resource-Based View (NRBV) by incorporating digitalization as a strategic environmental capability. Practically, the study advocates for integrated investment in green technologies, sustainable transportation, and digital infrastructure as a key strategy to improve green supply chain performance within the courier industry.
Perbandingan Savings Algorithm dengan Nearest Neighbour dalam Menyelesaikan Russian TSP Instances Sanggala, Ekra; Bisma, Muhammad Ardhya
Jurnal Media Teknik dan Sistem Industri Vol 7, No 1 (2023)
Publisher : Universitas Suryakancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/jmtsi.v7i1.3039

Abstract

Travelling Salesman Problem (TSP) is the problem for finding the shortest route starting from start node then visiting number of nodes exactly once and finally go back to start node. Several heuristics are popular for solving TSP, for example Savings Algorithm and Nearest Neighbour. Performance heuristics on solving TSP are diverse, so there is need of reference for choosing a heuristic. Comparing heuristics on solving instance can be a reference for choosing a heuristic. This paper will discuss about comparison Savings Algorithm and Nearest Neighbour on Solving Russian TSP Instances. For generating length of route, Savings Algorithm is better than Nearest Neighbour, while for generating CPU time, Nearest Neighbour is better than Savings Algorithm. Travelling Salesman Problem (TSP) merupakan permasalahan penentuan rute terpendek yang diawali dari titik start untuk mengunjungi sekumpulan titik tepat sekali dan diakhiri dengan kembali ke titik start. Beberapa Heuristik yang cukup populer untuk menyelesaikan TSP antara lain Savings Algorithm dan  Nearest Neighbour. Kemampuan Heuristik dalam menyelesaikan TSP berbeda-beda, sehingga diperlukan sebuah acuan untuk menentukan Heuristik yang akan digunakan. Membandingkan Heuristik dalam menyelesaikan instance dapat menjadi acuan untuk pemilihan Heuristik. Pada paper ini akan dibahas mengenai perbandingan Savings Algorithm dan Nearest Neighbour dalam menyelesaikan Russian TSP Instances. Untuk panjang rute yang dihasilkan, maka Savings Algorithm lebih baik dibandingkan Nearest Neighbour, sedangkan untuk CPU Time  yang dihasilkan, maka Nearest Neighbour lebih baik dibandingkan Savings Algorithm.
Random Savings Algorithm for Solving Russian TSP Instances Sanggala, Ekra; Bisma, Muhammad Ardhya
Sainteks: Jurnal Sain dan Teknik Vol 6 No 1 (2024): Maret
Publisher : Universitas Insan Cendekia Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37577/sainteks.v6i1.654

Abstract

Travelling Salesman Problem (TSP) is the problem for finding the shortest route starting from start node then visiting number of node exactly once and finally go back to start node. Savings Algorithm (SA) is a heuristic for solving TSP. In the Savings Algorithm, the first step that must be taken is to calculate the Savings for each pair of nodes. Then the Savings values that have been obtained are sorted from the largest Savings to the smallest Savings. Route is made by first inserting into the route the pair of nodes who has the highest Savings value. Sometimes there are many pairs of node who have the same Savings value, so it will become problem for SA to choose one of them. Random Algorithm can be a solution for solving this problem. Using Random on SA, makes SA become Random Savings Algorithm (RSA). Performance RSA on solving TSP must be tested on TSP Instance. Two important criterias on the test are solution route and CPU Time. Russian TSP Instances contain ten TSP Instances, on which RSA can be tested. The test result shows that RSA can improve the length of existing route rapidly.
Simulasi Proses Picking Order dengan Metode Dedicated Storage Menggunakan Software Fleksim (Studi Kasus PT XYZ) Amalia, Diana Nur; Fayaqun, Reza; Bisma, M Ardhya
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 7 No. 1 (2024): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v7i1.24351

Abstract

PT XYZ is a manufacturing company that produces food and drinks by providing quality products that are halal, high quality and safe for consumption by the public. In producing products, companies must provide several adequate facilities to support production activities, one of which is warehouse facilities. Currently, warehouses where finished food products are stored are stored randomly or placed in empty areas without paying attention to product entry and exit activities. This condition causes picking activities to take a long time and makes stock monitoring difficult. The aim of this research is to produce an appropriate goods storage design so that it can increase warehouse effectiveness. This research uses a special storage method. Where a special storage policy or method is permanently placed on each item. The number of product storage locations must meet the maximum storage space requirements and a simulation is carried out using FlexSim software. The research results show that designing goods storage using the dedicated storage method results in a reduction in the distance traveled for the collection process reaching 52%.
Penyelesaian Split Delivery VRP dengan Ant Colony Optimization (Studi Kasus: Pengiriman Produk di PT Sinarmas Distribusi Nusantara) Ginting, Anita Br; Fayaqun, Reza; Bisma, Muhammad Ardhya
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 7 No. 1 (2024): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v7i1.24844

Abstract

PT Sinarmar Distribusi distributes its products to all Distribution Center (DC) every day. Currently PT Sinarmas Distribution Nusantara uses a predetermined route every day using Colt Diesel Double vehicles with maximum transport capacity of 500 cartons.   Currently the number of products carried by each vehicle never reaches its maximum carrying capacity. PT Sinarmas Distribusi Nusantara wants vehicle transport capacity to be used optimally. This route problem at PT Sinarmas Distribusi Nusantara can be defined as Split Delivery Vehicle Routing Problem (SDVRP). Ant Colony Optimization (ACO) is a metaheuristic that can be used to solve SDVRP. By using ACO the resulting route is always shorter than the current route and the number of vehicles used is smaller.
Analisis Kelayakan Investasi Sensor Counter dan RFID Dengan Penetapan Discount Rate Berbasis CAPM Bisma, Muhammad Ardhya
Journal of Economics and Business UBS Vol. 12 No. 3 (2023): Special Issue
Publisher : Cv. Syntax Corporation Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52644/joeb.v12i3.277

Abstract

PT XYZ Indonesia merupakan perusahaan manufaktur yang berfokus pada produk-produk part otomotif. PT XYZ memiliki permasalahan terkait ketidaksesuaian jumlah hasil produksi yang berpotensi menyebabkan kerugian. Penelitian ini menelaah aspek keuangan untuk mengidentifikasi dan mengevaluasi sistem dan prosedur eksisting guna memberikan gambaran atas kebutuhan dari sistem yang baru. Selanjutnya, hasil dari identifikasi tersebut akan dinilai melalui analisis kelayakan keuangan dengan menggunakan kriteria NPV, IRR, dan payback period. Adapun discount rate ditetapkan berdasarkan pendekatan capital asset pricing model dan investasi diasumsikan sepenuhnya menggunakan ekuitas. Analisis sensitivitas juga dilakukan guna menilai elastisitas variabel dalam perhitungan model kelayakan ini, dan didapatkan bahwa investasi ini memiliki risiko yang tinggi
Determinants Factor of Accommodation Online Buying through Online Travel Agent (OTA) Pramudita, Aditia Sovia; Bisma, M. Ardhya; Guslan, Darfial
APMBA (Asia Pacific Management and Business Application) Vol. 9 No. 2 (2020)
Publisher : Department of Management, Faculty of Economics and Business, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.apmba.2020.009.02.1

Abstract

The objective of this research is to identifying the determinants factor of online shopping behavior in accommodation buying to increase purchase intention and the actual buying in the hospitality sector. The hospitality  industry in Indonesia is growing along with the growth of the tourism industry. Since ICT is developed in Indonesia, the behavior of the traveller changed. Online Travel Agent (OTA) and Accommodation Network Orchestrator (ANO) are emerging to fill consumer wants and needs in the way of accommodation buying. Technology Acceptance Model (TAM) is used as an approach to defining the determinants factor of online shopping behavior in accommodation buying. This research used the questionnaire to get primary data which is distributed to 358 respondents. The statistical tools used were Structural Equation Model-Partial Least Square (SEM-PLS). The result showed that all of the variables (perceived ease of use, perceived usefulness, perceived risk, perceived cost) were a significant and positive impact to purchase intention and actual use in online accommodation buying behavior.