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All Journal Jurnal Teknik Industri Terintegrasi (JUTIN) Indonesian Journal of Informatic Research and Software Engineering
A’yuniyah, Qurotul
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Analisa Algoritma Naïve Bayes Classifier (NBC) Untuk Prediksi Penjualan Alat Kesehatan : Naïve Bayes Classifier (NBC) Algorithm Analysis for Prediction Medical Device Sales Ramadhani, Dian; A’yuniyah, Qurotul; Elvira, Winda; Nazira, Nanda; Ambarani, Isnani; Intan, Sofia Fulvi
Indonesian Journal of Informatic Research and Software Engineering (IJIRSE) Vol. 3 No. 2 (2023): Indonesian Journal of Informatic Research and Software Engineering
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijirse.v3i2.941

Abstract

The application of Data Mining in the business scope can be found in the use of Customer Relationship Management (CRM). CRM is a company's effort to manage its sales and customers more optimally. Company Sales Data can be processed into knowledge that can be used to optimize marketing strategies. Purna Karya Scientific is a company engaged in the field of medical/medical devices, laboratory equipment, chemical and dental materials as well as educational aids. In this study has used sales data at PT. After Scientific Work with attributes item code, relation, number of items, and label as class. Then classify medical device sales data by implementing the Naïve Bayes Classifier (NBC) algorithm which can predict sales results by displaying an accuracy value. Implementation was carried out using Google Colab to obtain an accuracy value of 95%, a recall value of 95%, and a precision value of 81%. The results of data on sales of medical devices with 2 classes namely "Selling" and "Not Selling". The resulting value is very good and can be used as a basis for classifying sales of medical devices by analyzing the stock of goods at PT. Full Scientific Work.
Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi Di MAN 3 Pekanbaru Menggunakan Metode Analytic Hierarchy Process: Decision Support System For Selection Of Achieving Students At Man 3 Pekanbaru Using Analytic Hierarchy Process Method Rizaldi, Dede; A’yuniyah, Qurotul
Indonesian Journal of Informatic Research and Software Engineering (IJIRSE) Vol. 4 No. 1 (2024): Indonesian Journal of Informatic Research and Software Engineering
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijirse.v4i1.1349

Abstract

Dalam suatu sekolah penilaian siswa berprestasi biasanya hanya dipilih berdasarkan Nilai Ke- disiplinan dan Nilai Raport saja, begitu pula di MAN 3 Pekanbaru saat ini. Pemilihan siswa berprestasi di MAN 3 Pekanbaru hanya berdasarkan penilaian kedisiplinan siswa dan nilai raport yang menduduki peringkat tertinggi. Proses pemilihan tersebut banyak terdapat peluang untuk membuat keputusan yang salah karena proses pemilihan siswa hanya berdasarkan satu aspek saja yaitu nilai akhir siswa, sedangkan nilai prestasi lain yang didapat di luar sekolah tidak dijadikan bahan pertimbangan sebagai bahan tambahan kriteria untuk menentukan siswa yang berprestasi. Ini berarti kemungkinan besar siswa berprestasi yang dipilih tidak memenuhi standar sebagai siswa yang berprestasi. Tujuan dari penelitian ini adalah membangun sistem pendukung keputusan agar proses seleksi siswa berprestasi dapat berjalan dengan baik dan dapat meminimalisir kesalahan dalam proses penyeleksian siswa berprestasi. Metode yang digunakan dalam penelitian ini yaitu metode Analytic Hierarchy Process (AHP). Hasil dari penelitian ini yaitu berupa sistem pendukung keputusan pemilihan siswa berprestasi berdasarkan metode AHP. Adapun sistem mampu menghasilkan keputusan yang tepat dengan penilaian dari 5 kriteria.
Sistem Pendukung Keputusan Pemilihan Jurusan Dengan Metode Simple Additive Weighting (SAW) Pada SMAN 1 Kampar: Decision Support System for Choosing Majors Using the Simple Additive Weighting (SAW) Method at SMAN 1 Kampar Andika, Perdi; A’yuniyah, Qurotul; maulana, Muhammad rizki
Indonesian Journal of Informatic Research and Software Engineering (IJIRSE) Vol. 4 No. 1 (2024): Indonesian Journal of Informatic Research and Software Engineering
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/ijirse.v4i1.1350

Abstract

SMAN 1 Kampar terdapat 2 Jurusan IPA dan IPS. Pemilihan jurusan di SMAN 1 Kampar yang dilakukan pihak sekolah memprioritaskan jurusan IPA bagi siswa baru. Didalam kegiatan pemilihan jurusan, SMAN 1 Kampar masih menggunakan sistem manual dalam penginputan data dan nilai siswa. Hal ini menyebabkan pihak sekolah kesulitan dalam pengambilan keputusan untuk pemilihan jurusan. Tujuan dari penelitian ini adalah membantu pihak sekolah dalam pemilihan jurusan pada siswa didik baru dan membantu dalam perekapan data siswa. Metode yang digunakan dalam penelitian ini adalah metode Simple Additive Weighting (SAW). Berdasarkan hasil pengujian mengunakan User Acceptance Test didapat rata-ata persentasi pertanyaan Sangat Baik yaitu 88%. Berdasarkan pengujian Black Box, fitur-fitur sistem berfungsi dengan sangat baik.
Analisis Model Manajemen Permintaan SCM dan Peramalan Penjualan Busana Menggunakan Metode Holt-Winter Exponential Smoothing Tasia, Ena; Nazira, Nanda; A’yuniyah, Qurotul; Fikri , M. Hayatul; Am, Andri Nofiar
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 6 No. 4 (2023): Oktober
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v6i4.20313

Abstract

Sales forecasting is a highly crucial strategy in the business world, as it significantly contributes to enhancing a company's profits. In this context, sales transaction forecasting plays a vital role in assisting business decision-makers in planning effective sales strategies. The utilization of the Holt-Winters Exponential Smoothing method in sales forecasting demonstrates an effective approach. In this study, this method was applied to retail sales data of Muslim clothing from 2021 to 2023. By setting the parameters ? = 0.9, ? = 0.1, and ? = 0.1, the forecasting results indicate a high level of accuracy with low values for Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE), amounting to 29.93, 295.93, and 0.62%, respectively. Consequently, the forecast reveals that the inventory of clothing for periods 13 to 16 is 83, 228, 129, and 115, respectively
Co-Authors Am, Andri Nofiar Ambarani, Isnani Andika, Perdi Elvira, Winda Fikri , M. Hayatul Intan, Sofia Fulvi Maulana, Muhammad Rizki Nazira, Nanda Ramadhani, Dian Rizaldi, Dede Tasia, Ena