Analisis Komparatif Efisiensi Distribusi Logistik E-Commerce 328 307
DOI:
https://doi.org/10.26623/teknika.v21i1.13645Kata Kunci:
SPX Standard, Logistics Efficiency, Statistical Test, Capacity Management, Last-Mile DeliveryAbstrak
In the contemporary e-commerce ecosystem, delivery lead-time efficiency serves as a critical determinant of customer satisfaction. This study investigates the distributional characteristics of delivery durations for the "SPX Standard" service across four operational configurations: Early-Week Double-Day (peak), Weekend Double-Day (not available), Early-Week Non-Double-Day, and Weekend Non-Double-Day. Utilizing a quantitative comparative Exploratory Data Analysis (EDA) framework, historical logistics data were synthesized from 509 Shopee users in the Gunung Pati District, Semarang, spanning the 2024–2025 period. Statistical computation conducted via RStudio revealed significant departures from normality, as confirmed by Kolmogorov-Smirnov and Shapiro-Wilk tests (p<0.05). Consequently, hypothesis testing was performed using the non-parametric Kruskal-Wallis H-test. The analysis identified significant variance in median delivery velocities across groups (χ2=6.4256; p=0.04024). Findings indicate that while the Early-Week Non-Double-Day configuration recorded the highest median velocity (6 km/h), it exhibited extreme data dispersion, signaling process instability. Conversely, the Early-Week Double-Day period demonstrated superior reliability characterized by low variability, reflecting the efficacy of capacity scaling strategies during peak demand. The lowest performance metrics were observed during weekends, suggesting localized operational constraints. This research concludes that while peak-load operational stability effectively mitigates service degradation risks, standardized processes during regular workdays require further optimization. Limitations include the exclusion of holiday-related freight restrictions (e.g., Eid al-Fitr and Year-End periods).
Referensi
Populix. (2024). Double date campaign: What brands need to know. https://info.populix.co/articles/double-date-campaign-what-brands-need-to-know/
Locad. (2024). 12.12 sales guide for e-commerce sellers. https://golocad.com/blog/12-12-sales-guide-for-ecommerce-sellers/
Shopee Indonesia. (n.d.). SPX Express. Pusat Edukasi Penjual Shopee Indonesia. https://seller.shopee.co.id/edu/article/18015
The Economic Times. (2020, 2 Maret). 'Monday effect' may be impacting your package delivery: Study. https://m.economictimes.com/news/international/world-news/monday-effect-may-be-impacting-your-package-delivery-study/how-the-supply-chain-performance-is-affected/slideshow/74438114.cms
EZ SPSS. (n.d.). Report a Kruskal-Wallis test from SPSS in APA style. https://ezspss.com/report-a-kruskal-wallis-test-from-spss-in-apa-style/
Laerd Statistics. (n.d.). Kruskal-Wallis H test using SPSS statistics. https://statistics.laerd.com/spss-tutorials/kruskal-wallis-h-test-using-spss-statistics.php
Ahadi, G. D., & Zain, N. N. L. E. (2023a). Pemeriksaan Uji Kenormalan dengan Kolmogorov-Smirnov, Anderson-Darling dan Shapiro-Wilk. EIGEN MATHEMATICS JOURNAL, 11–19. https://doi.org/10.29303/emj.v6i1.131
Andy Agustian, Kania Lisdiana, Adang Suryana, & Muhammad Nursalman. (2025). Analisis Statistik Uji Normalitas dan Homogenitas Data Nilai Mata Pelajaran dengan Menggunakan Python. AL-IBANAH, 10(1), 51–56. https://doi.org/10.54801/b2726673
Boysen, N., Fedtke, S., & Schwerdfeger, S. (2021). Last-mile delivery concepts: A survey from an operational research perspective. OR Spectrum, 43(1), 1–58. https://doi.org/10.1007/s00291-020-00607-8
Heryana, A. (n.d.). Uji Statistik Non Parametrik.
Ibrahim, N. A. N., Husseini, F., Aisyah, N., Camelia, N., Khazlyn, N., Faiz, W., & Kahar, N. (2023). Online Shopping Behaviour in Youth: A Systematic Review of The Factors Influencing Online Shopping in Young Adults. International Journal of Academic Research in Business and Social Sciences, 13(2), Pages 168-178. https://doi.org/10.6007/IJARBSS/v13-i2/16257
Josefsson, J. H. O. (n.d.). The impact of delivery lead time on customer conversion.
Lim, S. F. W. T., Jin, X., & Srai, J. S. (2018). Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models. International Journal of Physical Distribution & Logistics Management, 48(3), 308–332. https://doi.org/10.1108/IJPDLM-02-2017-0081
Mauludin, M. R., Nurdiawan, O., & Basysyar, F. M. (2025). Penerapan Algoritma K-Means Clustering Untuk Analisis Kinerja Pengiriman Paket Shopee Express Di Hub Transit Kedawung. Jurnal Informatika dan Teknik Elektro Terapan, 13(1). https://doi.org/10.23960/jitet.v13i1.5870
Mishra, P., Pandey, C., Singh, U., Gupta, A., Sahu, C., & Keshri, A. (2019). Descriptive statistics and normality tests for statistical data. Annals of Cardiac Anaesthesia, 22(1), 67. https://doi.org/10.4103/aca.ACA_157_18
Pakpahan, R., Febriyanti, S., Berliana, D., & Esmeralda, R. N. (2024). Pengaruh Promo Event 6.6 Flash Sale Terhadap Perilaku Konsumtif Mahasiswa. 8.
Tawasuli, L., & Kholifah, K. (2023). Korelasi Special Event Day Tanggal Kembar Terhadap Minat Beli Masyarakat Di Shopee. Journal of Digital Business and Management, 2(2), 91–96. https://doi.org/10.32639/jdbm.v2i2.401
Usmadi, U. (2020). Pengujian Persyaratan Analisis (Uji Homogenitas dan Uji Normalitas). Inovasi Pendidikan, 7(1). https://doi.org/10.31869/ip.v7i1.2281
Wahid, A. J., Millantika, S. C., & Supriatna, A. K. (n.d.). The Effect of Double Date Discounts on Sales Levels In E-Commerce Shopee (Case Study on Students of Padjadjaran University in Jatinangor).
Yang, L., Shen, Q., & Li, Z. (2016). Comparing travel mode and trip chain choices between holidays and weekdays. Transportation Research Part A: Policy and Practice, 91, 273–285. https://doi.org/10.1016/j.tra.2016.07.001
Unduhan
Diterbitkan
Terbitan
Bagian
Lisensi
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

This work is licensed under a Creative Commons Attribution 4.0 International License.



