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Journal : Building of Informatics, Technology and Science

Penerapan Supply Chain Management (SCM) Dalam Pemantauan Stok Barang Berbasis Web Sri Wahyuni Nasution; Nuriadi Manurung; Elly Rahayu
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.1781

Abstract

Umi Nala Shop store is engaged in selling toys, such as floats, laptop screens, construction sets, ambulance cars, small cars, jeep cars, and many more. The problem is that this store does not know the amount of inventory of goods in the warehouse. This store purchases goods from suppliers for the inventory of goods to be sold without knowing the available stock. This makes the inventory of goods to be sold by the store uncontrollable. The store records incoming and outgoing goods and transactions manually using paper so that data can be lost. The Umi Nala Shop has more than 200 resellers but is inactive and has ten suppliers to supply the goods sold. The sale of goods at the Umi Nala Shop is still offline, where customers come directly to the Umi Nala Shop. Marketing is carried out through social media networks such as Facebook, WhatsApp, and Instagram. In carrying out its business, it is necessary to pay attention to inventory management to provide for consumer needs and control inventory when there is a high demand for goods. For the store to compete, it is necessary to implement Supply Chain Management (SCM) to integrate suppliers, warehouse manufacturing, and storage so that goods are distributed in the correct quantity at the right time, to minimize costs and provide satisfaction to consumers. The purpose of this study is to build an SCM application that can make it easier for stores to find out the amount of inventory to ensure the availability of goods. The results of this study with the implementation of Supply Chain Management at the Umi Nala Shop store can help and make it easier for store owners to manage the supply chain of goods.
Penerapan Metode Dempster Shaper Pada Sistem Pakar Diagnosa Penyakit Diabetes Mellitus Aandanu Aandanu; Jeperson Hutahaean; Elly Rahayu
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.2159

Abstract

Penyakit Diabetes Mellitus (DM) dapat didiagnosa berdasarkan data fakta ataupun gejala yang dialami pengguna sistem dan kadang gejala awal yang dialami pasien penyakit DM masih biasa saja sehingga dianggap dalam kondisi masih sehat. Dengan memperhatikan data fakta ataupun gejala-gejala yang dialami, diharapkan sistem ini dapat mendiagnosa tipe pada penyakit DM, sehingga gangguan atau penyakit dapat terdeteksi lebih awal dan penangannya. Terutama pasien yang ada di Rumah Sakit Umum Abdul Manan Simatupang Kisaran perlu ditangani dengan cepat karena berdasarkan jumlahnya cukup banyak pada setiap tahunnya. Kemajuan sistem pakar dapat mengatasi permasalahan ini yaitu dengan merancang sebuah sistem komputer berbasis web yang terintegrasi dengan database dan bahasa pemrograman seperti PHP-MySQL sehingga dapat membantu penderita untuk mendiagnosa gejala-gejala dan tipe penyakit tersebut. Tujuan dari penelitian ini adalah untuk membangun sebuah sistem pakar untuk mendiagnosa penyakit Diabetes Mellitus berbasis web. Aplikasi sistem pakar dalam pengambilan keputusan ini menggunakan metode Bayes dalam menghadapi suatu permasalahan, sering ditemukan jawaban yang tidak memiliki kepastian penuh. Peluang atau probalitas ini dapat berupa hasil suatu kejadian. Pada analisa permasalahannya sehingga didapatkan persentasi dari tipe penyakit tersebut. Hasil dari implementasi sistem yaitu sistem memberikan pilihan berupa gejala-gejala yang harus dipilih oleh pasien berdasarkan gejala yang dialami oleh pasien dan hasil dari proses tersebut adalah penyakit diabetes gestasional dengan bobot lebih tinggi dari penyakit diabetes lainnya yaitu bobot =1.66. Sistem juga akan memberikan informasi dalam penanganan penyakit diabetes tersebut
Penerapan Data Mining Untuk Prediksi Penjualan Produk Terlaris Menggunakan Metode K-Nearest Neighbor Dewi, Sri Puspita; Nurwati, Nurwati; Rahayu, Elly
Building of Informatics, Technology and Science (BITS) Vol 3 No 4 (2022): March 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (712.693 KB) | DOI: 10.47065/bits.v3i4.1408

Abstract

The implementation of Data Mining is very much needed by UD Andar because this trading business sells various types of products. This trading business sells powdered herbal medicine, plastic bags, food & beverage ingredients, and frozen foods that are in demand by consumers. Judging from the large number of consumer requests, it turns out that there are several best-selling and not-selling products, so based on the last 1 year data, a prediction of the best-selling product sales is needed, in order to make it easier for trading businesses in planning stock providers. Because the current system is still manual, the data obtained is less accurate and efficient. So to overcome this, we need a sales prediction system for best-selling products with data mining techniques using the k nearest neighbor method. This research produces a system of k nearest neighbor algorithms in data mining techniques that help to predict the sales of the best-selling products at UD Andar
Co-Authors . Zulfan Aandanu Aandanu Adi Prijuna Adi Prijuna Lubis Agus, Raja Tama Andri Aidil Adi Suhendra Aidil Syah Putra Alfa, Zikri Apriaji Kurniawan Ayu Lestari Baehaqi Cindy Ross Dewi Maharani Dewi, Sri Puspita Dinda Nuri Fazira Donni Nasution Edi Kurniawan Fauzy Maulana Sinaga Febbrian, Aldi Gundari, Putri Handayani, Masitah Havid Syafwan Helmiah, Fauriatun Herman Saputra Herman Saputra Herman Saputra Herman Saputra Iqbal Kamil Siregar Irawati, Novica Jeperson Hutahaean Kifti, Wan Mariatul Kiki Andriani Lestari, Oni Dewi Lubis, Adi Prijuna Lubis, Syafaat Sufi Maharani, Dewi Manurung, Nuriadi Mariatul Kifti, Wan Marpaung, Miftah Rizki Marpaung, Nasrun Masitah Handayani Melati, Putri Milandari, Novi Monalisa, Nency Widya Muhammad Ardiansyah Sembiring Nadya Viranika Nasution, Putri Alfiani Natasya, Tri Adetia Nency Widya Monalisa Neni Mulyani Niki Fazira Nirda Julianda Nofriadi Nofriadi Nofriadi Nofriadi Novi Silvana Kawila Nurhani, Irma Nuriadi Manurung Nuriadi Manurung Nurul Rahmadani Nurwati Nurwati Nurwati Nurwati Nurwati Nurwati Nurwati Oni Dewi Lestari panjaitan, widia fahwana br Permana, Yogi Abimanyu Putri Melati Putri Sundari Putri, Indri Anggraini Rahmadani, Sherly Ramadani, Dilla Ramdhan, William Renanda Eka Putri Risnawati Risnawati Rita Ratna sari Rizaldi, Rizaldi Roesella Anjani Rohminatin Rohminatin Rohminatin Rohminatin Roni Dalimunthe sahren, sahren Salsadilah, Nadya SANTOSO SANTOSO Santoso Santoso Saragih, Zuriah Br Siddik, Mohd. Siregar, Iqbal Kamil Sri Wahyuni Nasution Sundari, Putri Suriana Suriana Susanti, Riski Syafaat Sufi Lubis Syahira Syahira Syahputri, Rian Tantri Maya Leni Tri Anjar Ningsih USWATUN HASANAH Utama, Gita Nurul Waode Aminah Andella William Ramdhan Yusda, Riki Andri Zulfi Azhar