Article Per Year (5 Year)
p-Index From 2020 - 2025
0.817
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah FIFO JOURNAL OF APPLIED INFORMATICS AND COMPUTING IMTechno: Journal of Industrial Management and Technology Paradigma
Nugroho, Wawan
Unknown Affiliation
Computer Science & IT Industrial & Manufacturing Engineering

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Rancang Bangun Aplikasi Poin Of Sales Dengan Rapid Application Development (RAD) Untuk Efektivitas Penjualan Nugroho, Wawan; Nugroho, Andika Satrio; Hadi, Ahmad Aliyul; Aulia, Feryoda Ashafiro; Hadi, Eva Kristiana
IMTechno: Journal of Industrial Management and Technology Vol. 4 No. 2 (2023): Juli 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/imtechno.v4i2.2033

Abstract

Kebutuhan informasi sangat diandalkan dalam segala bidang termasuk dalam organisasi, bisnis, perusahaan, akademisi, lembaga pendidikan. Kondisi ini sangat relevan dengan penerapan komputerisasi dan telah menjadi suatu hal yang sudah tidak asing lagi dalam dunia usaha karena sangat membantu terhadap peningkatan produktivitas kinerja yang lebih efektif demi mencapai suatu tujuan yang diharapkan. Sistem Point of Sales (POS) merupakan sebuah sistem aplikasi yang digunakan untuk bisnis dalam bidang perdagangan dimana sistem ini dikhususkan untuk pengolahan data transaksi pembelian, transaksi penjualan. Dalam penelitian ini menggunakan metode Rapid Application Development (RAD). Metode RAD merupakan tahapan pengembangan sistem informasi hanya membutuhkan waktu yang relatif singkat. Ada beberapa tahapan diataranya perencanaan, desain sistem dan implementasi. Pada tahapan pengujian dilakukan dengan pengujian fungsionalitas - test case menggunakan Black Box, dimana jika test case sesuai dengan hasil yang diharapkan maka bisa dikatakan valid. Sehingga sistem dapat dijalankan dan dapat membantu lebih efektif dan efisien seperti pencatatan data produk, penjulan, pembelian dan laporan.
Implementation MFEP Method in Developing Recommendation System for Program Keluarga Harapan (PKH) Recipients Nugroho, Wawan; Nurohim, Galih Setiawan; Setyadi, Heribertus Ary Setyadi; Perbawa, Doddy Satrya
Paradigma - Jurnal Komputer dan Informatika Vol. 26 No. 2 (2024): September 2024 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v26i2.4978

Abstract

Poverty occurs because of the imbalance between unlimited human needs and limited resources. This results in a lack of income to meet basic living needs. The Indoonesian government's efforts to alleviate poverty include providing assistance to the poor or underprivileged with assistance called Social Assistance, one of which is the Program Keluarga Harapan (PKH). Problems often occur in determining who is entitled to receive PKH assistance. The conventional selection process is considered inefficient because it requires a long process and the influence of the committee's subjectivity in the assessment, the criteria used in the survey are not in accordance with government regulations and the limited quota of total PKH recipients, so there are still people who do not receive PKH even though they meet the criteria. This research uses the Multi Factor Evaluation Process (MFEP) method. System testing uses the black box method and Boundary Value Analysis techniques which focus on finding system errors. To test the system's accuracy by comparing the MFEP process from the system results and facts based on PKH recipients in 2022 and producing an accuracy value of 91%.
Penentuan Kelayakan dan Jenis Lembaga Keuangan dalam Pemberian Modal UMKM Menggunakan Metode AHP dan Decision Tree Setyadi, Heribertus Ary; Nurohim, Galih Setiawan; Nugroho, Wawan
Jurnal Ilmiah FIFO Vol 16, No 1 (2024)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2024.v16i1.007

Abstract

Terdapat beberapa kendala dibalik kehadiran UKM dalam pengelolaan usaha tersebut, antara lain kesulitan memperoleh pinjaman dari perbankan karena kurangnya pengetahuan pegawai yang ada, kurangnya perkembangan teknologi informasi, dan beberapa syarat yang tidak dapat terpenuhi. Tujuan penelitian ini untuk mengembangkan sistem pendukung keputusan yang dapat membantu dalam menentukan kelayakan UMKM dan lembaga keuangan yang sesuai untuk melakukan pinjaman. Terdapat 25 sampel UMKM yang berada di Kota Surakarta untuk dijadikan bahan penelitian. Algoritma decision tree dan metode Analytic Hierarchy Process (AHP) digunakan dalam penelitian ini. Tahap pertama untuk penentuan kelayakan suatu UMKM yang akan diberi pinjaman menggunakan algoritma decision tree. Penentuan rekomendasi jenis lembaga keuangan yang sesuai menerapkan metode AHP. Dari hasil pengujian diperoleh tingkat akurasi penerapan algoritma decision tree sebesar 80%. Pengujian tingkat akurasi penerapan metode AHP menghasilkan nilai 76,9%. Dari kedua pengujian tersebut, dapat dikatakan bahwa sistem yang dibuat sudah baik atau akurat.
Extreme Learning Machine Method Application to Forecasting Coffee Beverage Sales Sutanto, Yusuf; Setyadi, Heribertus Ary; Nugroho, Wawan; Al Amin, Budi
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10465

Abstract

Sales estimates can be used to set product prices and increase expected profits. Flyover coffee shop Karanganyar does not have a methodical forecasting method to estimate and predict their need/demand for coffee beverage products. Two previous research that used Extreme Learning Machine (ELM) method in other predictions stated that ELM method has high accuracy and fast compilation time. Another research predicted jeans sales using the ARIMA model and produced an accuracy of 17.05% based on the MAPE (Mean Absolute Percentage Error) method. Menstrual cycle prediction using the Long Short-Term Memory (LSTM) method produces a MAPE value of 7.5%. Two advantages of ELM method from two previous research were used as the basis for selecting ELM method used in our study. To help predict sales of coffee beverage menus, this research utilized an artificial neural network method using ELM algorithm. ELM method consists of an input layer and an output layer connected through a hidden layer. Data used for the test was daily sales data for a month. Data used for this study consisted of 215 data samples. Daily sales data at the Flyover coffee shop were collected from June to December 2024. Based on the results and analysis of error values using MAPE method, an average error value was 8.274%. From comparison of original data results and prediction data, an average MAPE error value the best number of features and hidden neurons is 5.65%.
Co-Authors Al Amin, Budi Aulia, Feryoda Ashafiro Doddy Satrya Perbawa Galih Setiawan Nurohim Hadi, Ahmad Aliyul Hadi, Eva Kristiana Heribertus Ary Setyadi Nugroho, Andika Satrio Setyadi, Heribertus Ary Setyadi Yusuf Sutanto