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All Journal Journal of Consumer Science JURNAL MANAJEMEN INDUSTRI DAN LOGISTIK Dinasti International Journal of Management Science Dinasti International Journal of Education Management and Social Science Jurnal Ilmu Manajemen Terapan (JIMT) Jurnal Manajemen Pendidikan dan Ilmu Sosial (JMPIS) Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Land Journal Competitive Jurnal Elementaria Edukasia Siber Journal of Advanced Multidisciplinary
Agus Purnomo
Magister Manajemen Logistik, Universitas Logistik Dan Bisnis Internasional
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Social Sciences Transportation Other

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Strategy to Improve Courier & Logistics Performance in the Enterprise Business Directorate through the Influence of Price and Service Quality on Competitive Advantage: Empirical Evidence from PT Pos Indonesia (Persero) Regional 3 Bandung Yogi Sudrajat; Saptono Kusdanu Waskito; Agus Purnomo
Dinasti International Journal of Education Management And Social Science Vol. 6 No. 4 (2025): Dinasti International Journal of Education Management and Social Science (April
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v6i4.4291

Abstract

The logistics and courier service sector plays an important role in supporting economic growth, especially in the era of digitalization and e-commerce expansion. PT Pos Indonesia, as one of the main players in this industry, faces challenges in improving the performance of couriers and logistics in Regional 3 Bandung. This study is important to understand the factors that influence company competitiveness in orders to improve efficiency and customer satisfaction. This study aims to analyze the effect of price and service quality on competitive advantage, and its impact on company performance at PT Pos Indonesia Regional 3 Bandung. The research method used is quantitative with a descriptive and verification approach. Data were collected through questionnaires from 182 PT Pos Indonesia customers and analyzed using SMART PLS to test the relationship between variables. The results of the study indicate that price and service quality have a significant effect on competitive advantage, which in turn has a positive impact on company performance. In addition, price and service quality also directly affect company performance. This study contributes to understanding strategies for increasing competitiveness in the logistics sector. The implication is that PT Pos Indonesia needs to adjust prices to the promised service standards and increase responsiveness to customer needs in order to improve competitiveness and business performance.   Keyword: Price, Service Quality, Competitive Advantage, Company Performance, PT Pos Indonesia
Logistics Management Optimization through Machine Learning: A Predictive Model for Item Transfer Time in Warehouse Activity-Space Hendri Lasmana; Agus Purnomo; Erna Mulyati
Dinasti International Journal of Education Management And Social Science Vol. 6 No. 5 (2025): Dinasti International Journal of Education Management and Social Science (June
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v6i5.5083

Abstract

Operational efficiency in warehouse logistics relies heavily on accurately predicting item transfer time. This study presents a machine learning-based framework using Gradient Boosting Classifier to classify transfer durations in the dynamic Jakarta Centrum warehouse, managed by the Corruption Eradication Commission (KPK) and PosIND. Field observations revealed inefficiencies due to unstructured layouts and fluctuating volumes. To improve prediction accuracy, the model incorporates Z-score normalization, SMOTE for class balancing, and hyperparameter tuning using GridSearchCV and PSO. The optimized model successfully classified 258 High, 285 Low, and 277 Medium transfer-time instances. SHAP analysis identified distance, distribution volume, and throughput as key influencing factors. Results demonstrate the potential of predictive modeling to enhance warehouse operations through better space usage, workforce planning, and SLA compliance. This study supports machine learning as a strategic tool for data-driven logistics optimization, with future work recommended to include contextual variables like workforce capacity and shift schedules for improved precision and real-world applicability.
The Effect of Green Logistics Practices, Digital Order Tracking Transparency, and Transportation on Last Mile Delivery Performance and Its Implications for Logistics Customer Satisfaction Kurniawan, Angga Tri Hanggara; Maniah, Maniah; Purnomo, Agus
Dinasti International Journal of Economics, Finance & Accounting Vol. 7 No. 1 (2026): Dinasti International Journal of Economics, Finance & Accounting (March-April 2
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijefa.v7i1.6303

Abstract

This study examines the effects of Green Logistics Practices, Digital Order Tracking Transparency, and Transportation on Last Mile Delivery Performance and their implications for Logistics Customer Satisfaction among courier and logistics service customers at PT Pos Indonesia Situbondo Branch. A quantitative explanatory research design was employed. Data were collected through questionnaires distributed to 131 respondents selected using stratified random sampling from a population of 188 customers. The data were analyzed using Structural Equation Modeling Partial Least Square with Smart PLS3. The results demonstrate that Green Logistics Practices, Digital Order Tracking Transparency, and Transportation have positive and significant effects on Last Mile Delivery Performance. These variables also have positive and significant direct effects on Logistics Customer Satisfaction. Furthermore, Last Mile Delivery Performance has a positive and significant effect on Logistics Customer Satisfaction and acts as a mediating variable that strengthens the influence of Green Logistics Practices, Digital Order Tracking Transparency, and Transportation on customer satisfaction. These findings highlight the importance of sustainable logistics practices, transparent digital information systems, and reliable transportation in enhancing last mile delivery performance and customer satisfaction. The study provides practical insights for logistics service providers in improving service quality through integrated and sustainable logistics strategies.
Model Integratif Pengaruh Armada Logistik Ramah Energi, Strategi Hub Berbasis Energi Lokal, dan Kualitas Infrastruktur Logistik terhadap Loyalitas Pelanggan dengan Peran Ketahanan Sistem Distribusi Logistik pada Perusahaan Kurir di Indonesia Agil Prasetyo; Agus Purnomo; Erna Mulyati
Jurnal Manajemen Pendidikan dan Ilmu Sosial Vol. 7 No. 3 (2026): Jurnal Manajemen Pendidikan dan Ilmu Sosial (April - Mei 2026)
Publisher : Dinasti Review

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jmpis.v7i3.7978

Abstract

Dengan ketahanan sistem distribusi logistik sebagai variabel mediasi, penelitian ini mengkaji hubungan antara loyalitas pelanggan dan armada logistik hemat energi, strategi pusat berbasis energi lokal, dan kualitas infrastruktur logistik. Temuan menunjukkan bahwa ketiga faktor operasional tersebut memiliki dampak signifikan terhadap loyalitas pelanggan dan ketahanan distribusi, dengan nilai β = 0,396 (p < 0,001), β = 0,460 (p < 0,001), dan β = 0,380 (p < 0,001), masing-masing. Daya penjelas yang kuat ditunjukkan oleh nilai R2 sebesar 0,815, yang berarti bahwa variabel yang diteliti dapat menjelaskan 81,5% varians dalam loyalitas pelanggan. Hubungan antara faktor operasional dan loyalitas pelanggan sangat dimediasi oleh Ketahanan Sistem Distribusi Logistik, menurut uji mediasi. Hasil ini menunjukkan bahwa peningkatan kualitas infrastruktur logistik, pembentukan strategi pusat berbasis energi lokal, dan penggunaan armada hemat energi semuanya berkontribusi pada sistem distribusi yang lebih tangguh, yang pada gilirannya meningkatkan loyalitas pelanggan terhadap jasa kurir di Indonesia.
Dari Transparency Menuju Trust: Menelusuri Dampak Teknologi Blockchain terhadap Kepercayaan Konsumen dalam Supply Chain Pangan Syifa Salsabila; Agus Purnomo; Erna Mulyati
Jurnal Manajemen Pendidikan dan Ilmu Sosial Vol. 7 No. 2 (2026): Jurnal Manajemen Pendidikan dan Ilmu Sosial (Februari - Maret 2026)
Publisher : Dinasti Review

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/jmpis.v7i2.7579

Abstract

Penelitian ini mengkaji pengaruh penggunaan teknologi blockchain terhadap kepercayaan konsumen dalam rantai pasok pangan di Indonesia, dengan mempertimbangkan peran keamanan produk pangan, risiko sosial, dan kepercayaan kepada pemangku kepentingan sebagai variabel mediasi. Menggunakan pendekatan kuantitatif dan analisis pemodelan persamaan struktural berbasis varians, hasil menunjukkan bahwa blockchain secara signifikan meningkatkan persepsi keamanan produk serta kepercayaan terhadap aktor dalam rantai pasok, namun tidak berpengaruh langsung terhadap persepsi risiko sosial. Temuan ini memperkaya pemahaman teoritis mengenai mekanisme mediasi dalam adopsi teknologi digital di sektor pangan dan menegaskan bahwa keberhasilan implementasi teknologi sangat bergantung pada integrasi aspek teknis dan sosial. Secara praktis, hasil penelitian memberikan arahan strategis bagi pemerintah dan pelaku industri dalam mengembangkan sistem pangan yang lebih transparan, aman, dan dapat dipercaya, khususnya di negara berkembang seperti Indonesia.
Integration of Machine Learning Models and Centralized Warehousing Strategy in Multichannel Book Distribution Optimization Ato Kusnandar; Agus Purnomo; Melia Eka Lestiani
Dinasti International Journal of Education Management and Social Science Vol. 7 No. 2 (2025): Dinasti International Journal of Education Management And Social Science (Decem
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v7i2.5294

Abstract

This study aims to optimize multichannel book distribution efficiency through the integration of machine learning–based demand forecasting and centralized warehouse strategy at PT Mizan Media Utama. Using three years of multichannel sales data from offline stores, marketplaces, resellers, and events, the research employs the XGBoost algorithm to predict monthly demand for selected book SKUs. The results demonstrate that XGBoost consistently outperforms conventional forecasting methods, achieving lower Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and higher R² values, indicating improved accuracy and reliability. Comparative analysis between actual sales in 2025 and forecasted results shows that XGBoost reduces average forecast error by 20–30% compared to traditional projection methods. These accurate predictions support more effective stock allocation within the centralized warehouse, minimizing overstock and stockout risks across sales channels. The findings confirm that integrating predictive analytics into distribution planning enhances operational efficiency, improves inventory control, and strengthens data-driven decision-making. This study contributes both theoretically and practically by demonstrating how machine learning can transform conventional supply chain management into a digitally integrated, responsive, and efficient system suited for the publishing and book distribution industry.
Sustainable Supply Chain Odyssey: Exploring The Interplay Of Green Technology, Green Transportation, and Green Logistics Digitalization On Green Supply Chain Performance Agus Purnomo; Muhammad Ardhya Bisma; 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.
Predictive Modeling of Delivery Delays in Transportation Using Machine Learning: A Comparative Study of Service Types Agus Purnomo; Nava Gia Ginasta; Syafrianita Syafrianita; Syafrial Fachri Pane
Dinasti International Journal of Education Management and Social Science Vol. 7 No. 2 (2025): Dinasti International Journal of Education Management And Social Science (Decem
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v7i2.5736

Abstract

Traditional predictive models such as linear regression often struggle to capture the nonlinear interactions among operational factors that cause delivery delays in multi-category courier services. This study addresses that gap by developing and comparing machine learning (ML) algorithms to predict delivery delays across different service types at PT Pos Indonesia. The primary objective is to identify the most accurate predictive model and the dominant variables influencing delays across high-speed (Same Day, Next Day) and economical delivery services. A quantitative experimental design was employed using operational data from PT Pos Indonesia, consisting of 10,999 records and 12 variables. Three ML algorithms Logistic Regression, Random Forest, and XGBoost were trained and evaluated using standardized preprocessing, feature encoding, and stratified data splitting. Results show that Random Forest and XGBoost outperform Logistic Regression, each achieving approximately 65% accuracy with an AUC of 0.73, indicating moderate yet consistent predictive capabilities. Feature importance analysis reveals that Discount_offered, Weight_in_gms, and Prior_purchases are the most influential predictors of delivery timeliness.This study provides theoretical and practical contributions by introducing the first comparative ML framework for delay prediction in a national logistics context. The findings offer actionable insights for optimizing scheduling, load balancing, and promotional strategies, while advancing the integration of AI-based predictive analytics within postal logistics operations.
Development and Validation of a Centralised Procurement Model: The Key Role and Intermediary Role in Strengthening Procurement Governance (Case Study of PT Wika Gedung) Yayuk Dwi Indriani; Agus Purnomo; Melia Eka Lestiani
Dinasti International Journal of Education Management and Social Science Vol. 7 No. 3 (2025): Dinasti International Journal of Education Management and Social Science (Febru
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v7i3.5997

Abstract

This study aims to develop and validate a centralised procurement model in the construction industry using Exploratory Factor Analysis (EFA) and Partial Least Squares Structural Equation Modelling (PLS-SEM). The EFA results identified six new factors representing the multidimensional nature of centralised procurement: ORCHESTRA, STRATEGUS, DIGISONIC, FINCERTO, SYMPHONY-LINK, and GRAND-GOVERNANCE. All constructs showed strong statistical validity and reliability. The PLS-SEM findings showed high explanatory power, with R² values of 0.732 for SYMPHONY-LINK and 0.731 for GRAND-GOVERNANCE. These results highlight that STRATEGUS significantly influences SYMPHONY-LINK, while SYMPHONY-LINK is the dominant predictor in procurement governance. Furthermore, SYMPHONY-LINK fully mediates the effect of STRATEGUS on GRAND-GOVERNANCE, highlighting cross-functional integration as a critical driver of centralised procurement success. This study contributes theoretically by introducing new constructs into the domain of centralised procurement and provides practical implications for construction companies seeking standardised, transparent, and sustainability-oriented procurement strategies.
Beyond Bias and Culture: Exploring the Role of Sustainable Procurement Orientation in Vendor Selection and Procurement Performance in the Construction Industry Gemmi Puspa Wijayanti Irianto; Agus Purnomo; Melia Eka Setiani
Dinasti International Journal of Education Management and Social Science Vol. 7 No. 3 (2025): Dinasti International Journal of Education Management and Social Science (Febru
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v7i3.6019

Abstract

This study aims to examine the influence of Organisational Culture, Perceived Risk, Status Quo Bias, and Sustainable Procurement Orientation on Vendor Selection and Procurement Performance in the construction industry, and to assess the mediating role of Vendor Selection. A quantitative approach was applied using survey data from 112 employees involved in procurement activities at a construction company in Indonesia, and the data were analysed using Partial Least Squares–Structural Equation Modelling. All constructs met the criteria for reliability and both convergent and discriminant validity. Organizational Culture emerged as the strongest predictor of Vendor Selection and Procurement Performance, followed by Sustainable Procurement Orientation. Contrary to theoretical expectations, Perceived Risk and Status Quo Bias showed positive effects on Vendor Selection, indicating the strategic importance of caution and stability in high-risk construction environments. Vendor Selection significantly mediated all examined relationships. These findings enhance the understanding of behavioral dynamics in supply chains and sustainable procurement by demonstrating how psychological, cultural, and sustainability-oriented factors collectively shape vendor decision-making and influence procurement outcomes.
Co-Authors Agil Prasetyo Arif Yudha Wahyudi Ato Kusnandar Dani Ramdani, Dani Dhinda Rezta Adha Erna Mulyati Erna Mulyati Erna Mulyati Fachmi Rachmat Chaidar, Diar Gemmi Puspa Wijayanti Irianto Gunawan, Andri Handoko, Kokoh Hariadi Ismail Hendri Lasmana Imam Budiharto Kurniawan, Angga Tri Hanggara Lasmana, Hendri M. Yogi Riyantama Isjoni Maniah Maniah Maniah, Maniah Melia Eka Lestiani Melia Eka Lestiani Melia Eka Setiani Mohamed Ibrahim Abdul Mutalib Muhamad Faisal Nasrudin Muhammad Ardhya Bisma Mustafia Mustafia* Nava Gia Ginasta Putri Mety Zalynda Ramadhan Surya Dinata Saptono Kusdanu Waskito Sudrajat, Yogi Sutarman Sutarman Syafrial Fachri Pane Syafrianita Syafrianita Syifa Salsabila Yayuk Dwi Indriani Yogi Sudrajat