Optimalisasi Penjualan Produk Sayuran Organik dengan Pendekatan Analisis Asosiasi
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Perusahaan distribusi sayuran organik sangat menghindari terjadinya produk yang tidak segar dikarenakan penyimpanan produk yang terlalu lama, khususnya pada perusahaan distribusi sayuran di Kecamatan Cipanas, Kabupaten Cianjur ini. Dalam 3 tahun terakhir perusahaan mengalami penurunan transaksi yang dapat mengakibatkan produk-produk tersimpan terlalu lama, sehingga perusahan perlu meningkatkan penjualan dengan merekomendasikan produk kepada pelanggan. Berdasarkan data transaki-transaksi sebelumnya diharapkan dapat diolah untuk dapat membuat rekomendasi produk sesuai produk pertama yang diambil oleh pelanggan. Pada penelitian sebelumnya terdapat algoritma untuk menemukan aturan asosiasi yaitu metode Apriori, FP-Growth dan Eclat. Pada penelitian ini akan membandingkan metode asosiasi terlebih dahulu untuk menemukan aturan asosiasi yang terbaik berdasarkan data histori yang ada, dengan jumlah data sebanyak 120.642 data yang terjadi antara Juni 2020 sampai November 2022. Indeks yang digunakan untuk mengukur kebaikan association rule yang ditemukan meliputi support, confidence, dan lift. Selanjutnya jika sudah ditemukan algoritma terbaik maka akan dilakukan proses analisis asosiasi, diharapkan dapat menemukan aturan asosiasi dalam bentuk mapping yang dapat diimplementasikan untuk merekomendasikan produk yang tepat kepada pelanggan. Dalam proses mengolah data mining akan menggunakan metode CRISP-DM. CRISP-DM digunakan sebagai kerangka kerja standar untuk proses data mining yang digunakan dalam penelitian ini. Penelitian ini diharapkan dapat memberikan solusi yang bermanfaat bagi perusahaan dalam mengatasi tantangan dalam menjaga kesegaran produk sayuran organik serta meningkatkan penjualannya.
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