{"id":789,"date":"2026-04-20T09:00:37","date_gmt":"2026-04-20T02:00:37","guid":{"rendered":"https:\/\/online.binus.ac.id\/industrial-engineering\/?p=789"},"modified":"2026-02-20T10:35:56","modified_gmt":"2026-02-20T03:35:56","slug":"pemanfaatan-big-data-untuk-pengambilan-keputusan-manajerial","status":"publish","type":"post","link":"https:\/\/online.binus.ac.id\/industrial-engineering\/2026\/04\/20\/pemanfaatan-big-data-untuk-pengambilan-keputusan-manajerial\/","title":{"rendered":"Pemanfaatan Big Data untuk Pengambilan Keputusan Manajerial"},"content":{"rendered":"

\"\"
\nDi masa lalu, manajer sering kali mengandalkan intuisi atau pengalaman masa lalu untuk mengambil keputusan penting. Namun, di era digital saat ini, volume, kecepatan, dan variasi data yang dihasilkan sangatlah besar. <\/span>Big Data<\/span><\/b>\u00a0telah\u00a0mengubah\u00a0paradigma\u00a0kepemimpinan\u00a0dari\u00a0<\/span>gut feeling<\/span><\/i>\u00a0(perasaan)\u00a0menjadi\u00a0<\/span>Data-Driven Decision Making (DDDM)<\/span><\/b>.<\/span>\u00a0<\/span><\/p>\n

Mengapa\u00a0Big Data\u00a0Penting\u00a0bagi\u00a0Manajer?<\/span><\/b>\u00a0<\/span><\/p>\n

Big Data bukan sekadar tentang jumlah data yang besar, melainkan tentang apa yang bisa dilakukan organisasi dengan data tersebut. Bagi seorang manajer, pemanfaatan Big Data memberikan keunggulan dalam tiga aspek utama:<\/span>\u00a0<\/span><\/p>\n

    \n
  1. Analisis\u00a0Prediktif\u00a0(Forecasting):<\/span><\/b> Manajer dapat memprediksi tren pasar, perilaku konsumen, dan kebutuhan stok di masa depan dengan akurasi yang lebih tinggi menggunakan algoritma machine learning.<\/span>\u00a0<\/span><\/li>\n
  2. Segmentasi\u00a0Pelanggan\u00a0yang\u00a0Presisi:<\/span><\/b> Dengan data besar, perusah an dapat memetakan profil pelanggan secara individu, memungkinkan kampanye pemasaran yang lebih personal dan efektif.<\/span>\u00a0<\/span><\/li>\n
  3. Optimalisasi\u00a0Operasional:<\/span><\/b> Data dari berbagai sensor (IoT) dan log kerja dapat dianalisis untuk menemukan kemacetan (bottleneck dalam proses produksi atau layanan<\/span>\u00a0<\/span><\/li>\n<\/ol>\n

    Transformasi\u00a0Keputusan di\u00a0Berbagai\u00a0Departemen<\/span><\/b>\u00a0<\/span><\/p>\n\n\n\n\n\n\n\n
    No<\/span>\u00a0<\/span><\/td>\nDepartemen<\/span>\u00a0<\/span><\/td>\nManfaat Big Data<\/span>\u00a0<\/span><\/td>\n<\/tr>\n
    1<\/span>\u00a0<\/span><\/td>\nPemasaran<\/span>\u00a0<\/span><\/td>\nMenentukan\u00a0harga\u00a0dinamis\u00a0(dynamic pricing)\u00a0berdasarkan\u00a0permintaan\u00a0real-time<\/span>\u00a0<\/span><\/td>\n<\/tr>\n
    2<\/span>\u00a0<\/span><\/td>\nKeuangan<\/span>\u00a0<\/span><\/td>\nDeteksi\u00a0dini\u00a0penipuan\u00a0(fraud detection) dan\u00a0analisis\u00a0risiko\u00a0kredit\u00a0yang\u00a0lebih\u00a0tajam<\/span>\u00a0<\/span><\/td>\n<\/tr>\n
    3<\/span>\u00a0<\/span><\/td>\nSDM<\/span>\u00a0<\/span><\/td>\nAnalisis\u00a0retensi\u00a0karyawan\u00a0untuk\u00a0memprediksi\u00a0siapa\u00a0yang\u00a0berisiko\u00a0resign<\/span>\u00a0<\/span><\/td>\n<\/tr>\n
    4<\/span>\u00a0<\/span><\/td>\nLogistik<\/span>\u00a0<\/span><\/td>\nPenentuan\u00a0rute\u00a0pengiriman\u00a0tercepat\u00a0berdasarkan\u00a0data\u00a0cuaca\u00a0dan\u00a0lalu\u00a0lintas<\/span>\u00a0<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

    \u00a0<\/span><\/p>\n

    Tantangan\u00a0Manajerial\u00a0dalam\u00a0Implementasi<\/span><\/b>\u00a0<\/span><\/p>\n

    Meskipun sangat bermanfaat, mengelola Big Data bukanlah tanpa hambatan. Manajer harus menghadapi tantangan seperti:<\/span>\u00a0<\/span><\/p>\n

      \n
    • Kualitas Data: “Garbage in, garbage out”\u2014data yang kotor akan menghasilkan keputusan yang salah.<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
        \n
      • Keamanan & Privasi: Kepatuhan terhadap regulasi perlindungan data (seperti GDPR atau UU PDP di Indonesia).<\/span>\u00a0<\/span><\/li>\n<\/ul>\n
          \n
        • Kesenjangan Keterampilan: Kebutuhan akan tenaga kerja yang fasih data (<\/span>data literate<\/span><\/i>).<\/span>\u00a0<\/span><\/li>\n<\/ul>\n

          Tren 2025\u20132026: Augmented Analytics<\/span><\/b>\u00a0<\/span><\/p>\n

          Memasuki tahun 2026, tren akan bergeser ke arah Augmented Analytics, di mana kecerdasan buatan (AI) secara otomatis mengolah data besar dan memberikan saran keputusan langsung kepada manajer tanpa perlu melalui ilmuwan data secara manual.<\/span>\u00a0<\/span><\/p>\n

          \u00a0<\/span><\/p>\n

          Daftar Pustaka<\/span>\u00a0<\/span><\/p>\n

          Davenport, T. H., & Miller, J. G. (2022).\u00a0<\/span>Working with AI: Real Stories of People Working with Intelligent Machines<\/span><\/i>. MIT Press.<\/span>\u00a0<\/span><\/p>\n

          George, G., Merrill, R. K., &\u00a0Schillebeeckx, S. J. (2023). Digital Sustainability and Management Strategy.\u00a0<\/span>Journal of Management Studies<\/span><\/i>, 60(8), 2100-2135.<\/span>\u00a0<\/span><\/p>\n

          Gartner. (2024).\u00a0<\/span>Predicts 2025: Data and Analytics Strategies for the AI Era<\/span><\/i>. Gartner Research.<\/span>\u00a0<\/span><\/p>\n

          McAfee, A., & Brynjolfsson, E. (2020).\u00a0<\/span>Machine, Platform, Crowd: Harnessing Our Digital Future<\/span><\/i>\u00a0(Updated Edition). W. W. Norton & Company.<\/span>\u00a0<\/span><\/p>\n

          Provost, F., & Fawcett, T. (2021).\u00a0<\/span>Data Science for Business: What You Need to Know about Data Mining and\u00a0Data-Analytic\u00a0Thinking<\/span><\/i>\u00a0(Revised Edition). O’Reilly Media.<\/span>\u00a0<\/span><\/p>\n

          Sivarajah, U., et al. (2025). The Evolution of Big Data in Managerial Decision Making: A 2026 Perspective.\u00a0<\/span>International Journal of Information Management<\/span><\/i>, 72, 102-118.<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

          Di masa lalu, manajer sering kali mengandalkan intuisi atau pengalaman masa lalu untuk mengambil keputusan penting. Namun, di era digital saat ini, volume, kecepatan, dan variasi data yang dihasilkan sangatlah besar. Big Data\u00a0telah\u00a0mengubah\u00a0paradigma\u00a0kepemimpinan\u00a0dari\u00a0gut feeling\u00a0(perasaan)\u00a0menjadi\u00a0Data-Driven Decision Making (DDDM).\u00a0 Mengapa\u00a0Big Data\u00a0Penting\u00a0bagi\u00a0Manajer?\u00a0 Big Data bukan sekadar tentang jumlah data yang besar, melainkan tentang apa yang bisa dilakukan organisasi […]<\/p>\n","protected":false},"author":705,"featured_media":790,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[2],"tags":[],"class_list":["post-789","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-article"],"_links":{"self":[{"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/posts\/789","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/users\/705"}],"replies":[{"embeddable":true,"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/comments?post=789"}],"version-history":[{"count":1,"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/posts\/789\/revisions"}],"predecessor-version":[{"id":791,"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/posts\/789\/revisions\/791"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/media\/790"}],"wp:attachment":[{"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/media?parent=789"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/categories?post=789"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/online.binus.ac.id\/industrial-engineering\/wp-json\/wp\/v2\/tags?post=789"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}