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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Minfo Polgan (JMP)
Sipayung, Sardo
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Computer Science & IT Library & Information Science Mathematics Social Sciences

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Implementasi Algoritma Dijikstra dalam Menentukan Rute Pengiriman Terpendek pada Layanan Shopee Express Medan Silaban, Daniel; Simbolon, Cantriya Anastasya; Gorat, Paulina Gorat; Pakpahan, Frans Steven; Simatupang, Gracia; Sipayung, Sardo
Jurnal Minfo Polgan Vol. 14 No. 1 (2025): Artikel Penelitian
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/jmp.v14i1.14912

Abstract

Di era digital yang semakin berkembang, efektivitas distribusi logistik menjadi faktor kunci dalam mendukung kualitas layanan e-commerce, termasuk di kota Medan yang merupakan pusat pertumbuhan ekonomi di wilayah Sumatera Utara. Salah satu tantangan utama dalam proses pengiriman adalah pemilihan jalur yang efisien untuk meminimalisir waktu tempuh dan biaya operasional. Penelitian ini berfokus pada penerapan Algoritma Dijkstra dalam menentukan rute pengiriman terpendek pada layanan Shopee Express Medan. Algoritma Dijkstra dipilih karena kemampuannya dalam menghitung lintasan minimum dari satu simpul ke simpul lainnya dalam graf berbobot non-negatif secara efisien dan akurat. Penelitian ini menggunakan representasi graf berbobot, dimana titik-titik lokasi pengiriman dianggap sebagai simpul dan jarak antar lokasi direpresentasikan sebagai bobot sisi. Proses analisis dilakukan dengan memodelkan graf jaringan rute pengiriman Shopee Express di wilayah Medan, yang kemudian diolah menggunakan algoritma Dijkstra untuk mendapatkan rute yang optimal. Hasil penelitian menunjukkan bahwa penerapan algoritma ini mampu mengurangi jarak tempuh dan waktu pengiriman secara signifikan, serta memberikan alternatif lintasan yang lebih efisien dibandingkan dengan pendekatan manual atau berbasis intuisi.Penerapan sistem ini berpotensi untuk diintegrasikan dalam platform navigasi internal layanan logistik untuk mendukung pengambilan keputusan operasional secara real-time. Dengan demikian, penerapan algoritma Dijkstra tidak hanya relevan secara teknis, tetapi juga strategis dalam meningkatkan efisiensi pengiriman dan kepuasan pelanggan.
Integration Of Pca And K-Means Clustering For Staple Food Segmentation In Support Of National Food Policy Sipayung, Sardo; Hasugian, Paska Marto
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15343

Abstract

This study aims to develop cross-provincial staple-food segmentation by integrating Principal Component Analysis (PCA) and K-Means to support policy formation. The dataset comprises 2023 staple-food consumption for 34 Indonesian provinces across six indicators from BPS/SUSENAS. All indicators were standardized using z-score, reduced via PCA, and the resulting component scores were used as inputs to K-Means. Three components (PC1–PC3) explained 73.86% of the variance and captured shifts between sweet/animal-based vs. plant foods, fatty or animal-based grains, and the energy contribution of fat. The optimal number of clusters was determined as k = 3, yielding Silhouette = 0.466 and DBI = 0.733, indicating sufficiently compact and well-separated groups. The results reveal three segments: the first group consists of 11 provinces that are predominantly plant-based with low sugar and low animal-based consumption; the second group includes 13 provinces characterized by high animal-based and high-fat consumption; and the third group comprises 10 provinces with low-fat diets and fresh plant-based consumption. Stability checks on initialization and a leave-one-feature-out procedure confirmed consistent assignments. This fills an empirical gap: to our knowledge, no prior research integrates PCA with K-Means for cross-provincial staple-food segmentation in Indonesia while also reporting internal validation. Practically, the study provides operational segmentation to support food-security interventions moving beyond composite indices toward actionable targeting for production support, supply/price stabilization, and improved nutritional access thereby reframing IKP/FSVA from index-ranking to evidence-based segmentation.
Co-Authors Gorat, Paulina Gorat Hasugian , Paska Marto Pakpahan, Frans Steven Silaban, Daniel Simatupang, Gracia Simbolon, Cantriya Anastasya