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All Journal JITK (Jurnal Ilmu Pengetahuan dan Komputer) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Jutsi: Jurnal Teknologi dan Sistem Informasi J-Com (Journal of Computer) Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat
Rahayu, Elly
Sekolah Tinggi Manajemen Informatika Dan Komputer Royal
Humanities Computer Science & IT Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Public Health Social Sciences

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Journal : Building of Informatics, Technology and Science

 1 
Penerapan Data Mining Untuk Prediksi Penjualan Produk Terlaris Menggunakan Metode K-Nearest Neighbor Sri Puspita Dewi; Nurwati Nurwati; Elly Rahayu
Building of Informatics, Technology and Science (BITS) Vol 3 No 4 (2022): Maret 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
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
Co-Authors Aandanu Aandanu Adi Prijuna Lubis Aidil Adi Suhendra Apriaji Kurniawan Ayu Lestari Cindy Ross Dewi Maharani Donni Nasution Fauzy Maulana Sinaga Helmiah, Fauriatun Herman Saputra Herman Saputra Iqbal Kamil Siregar Jeperson Hutahaean Kifti, Wan Mariatul Kiki Andriani Masitah Handayani Nadya Viranika Nency Widya Monalisa Nofriadi Nofriadi Novi Silvana Kawila Nuriadi Manurung Nurul Rahmadani Nurwati Nurwati Nurwati Nurwati Oni Dewi Lestari Putri Sundari Renanda Eka Putri Risnawati Risnawati Rita Ratna sari Rohminatin Rohminatin Rohminatin Rohminatin Roni Dalimunthe Santoso Santoso SANTOSO SANTOSO Sri Puspita Dewi Sri Wahyuni Nasution Suriana Suriana Syafaat Sufi Lubis Syahira Syahira Tri Anjar Ningsih USWATUN HASANAH Wan Mariatul Kifti William Ramdhan