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All Journal JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Ilmu Komputer dan Bisnis Jurnal Computer Science and Information Technology (CoSciTech) Bulletin of Computer Science Research Jutech: Jurnal Teknologi Informasi
SRI NADRIATI
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Computer Science & IT Economics, Econometrics & Finance

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SISTEM PENGAMBILAN KEPUTUSAN UNTUK MENGUKUR TINGKAT PENGETAHUAN DAN SIKAP SISWA TENTANG BAHAYA NARKOBA BAGI KESEHATAN DENGAN METODE “AHP” PADA SMP PGRI 1 PADANG YANTI YUSMAN; SRI NADRIATI
Jurnal Ilmu Komputer dan Bisnis Vol. 10 No. 1 (2019): Vol. 10 No. 1 (2019)
Publisher : STMIK Dharmapala Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47927/jikb.v10i1.66

Abstract

Penyalahgunaan obat terlarang bukan hanya untuk kebutuhan medis diproduksi, dijual,dan dikosumsi secara terlarang, Remaja merupakan kelompok yang rentan dalam penyalah gunaan narkoba. Penelitihan dilakukan untuk, mengetahui bagai mana hubungan antara pengetahuan dan sikap, hubungana pengetahuan dan prilaku, dan sikap penyalahgunaan narkoba padabagaimana hubungan antara siswa / siswi di SMP PGRI 1 Padang. Metode : penelitihan ini melakukan pengumpulan data, dalam bentuk kuesioner yang diberikan kepada para siswa / siswi dengan dari pertanyaan yang di ajukan sehingga penulis bisa mengetahui.seberapa pengetahuan dan sikap siswa terhadap narkoba bagi kesehatan.
PEMILIHAN PRESIDEN MAHASISWA ATAU BEM STMIK DHARMAPALA RIAU CHANDRA KUSUMA; SRI NADRIATI
Jurnal Ilmu Komputer dan Bisnis Vol. 10 No. 2 (2019): Vol. 10 No. 2 (2019)
Publisher : STMIK Dharmapala Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47927/jikb.v10i2.68

Abstract

Kualitas Presiden Mahasiswa atau BEM dalam mendukung majunya suatu Perguruan Tinggi sangat penting, sehingga banyak Universitas yang berupaya agar memiliki kualitas Presma yang berkualitas. Salah satu cara yang bisa dilakukan yaitu dengan menjaring calon Presma sesuai dengan kriteria yang diinginkan universitas, hanya saja selama ini banyak universitas yang sering bermasalah dalam proses pemberkasan dan penyortiran karena dilakukan secara manual, karena sangat dimungkinkan terjadinya kesalahan dalam model seleksi ini sehingga hasilnya menjadi tidak sesuai dengan kriteria calon pegawai yang diinginkan perusahaan.Sehingga dibutuhkan sebuah sistem pendukung keputusan (SPK) dengan metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) untuk seleksi Presma yang memiliki beberapa kriteria antara lain Wawasan yang luas, Keaktifan organisasi, Prestasi, Orasi, Kepribadian. hasil pengujian dapat disimpulkan bahwa SPK pemilihan presma dengan metode TOPSIS menghasilkan sistem yang dapat memberikan rekomendasi calon presma sesuai dengan kriteria yang ditentukan.
Sistem Informasi Perangkat Desa (SINPERDES) Berbasis Website Dengan Metode Waterfall Dalam Pelaksanaan Pembangunan Desa Yanti Yusman; Nurafina Siregar; Randi Rian Putra; Sri Nadriati
Bulletin of Computer Science Research Vol. 3 No. 6 (2023): October 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v3i6.274

Abstract

Website-Based Village Information System (SINPERDES) Using the Waterfall Method in Implementing Village Development The Village Information System (SINPERDES) is a technological solution designed to optimize the implementation of village development through the use of the Waterfall method in its development. The Waterfall method is a software development approach that focuses on sequential stages, starting from planning, analysis, design, implementation, to maintenance. This research aims to develop SINPERDES which is able to support village officials in managing information and village development processes more efficiently and effectively. Website-based SINPERDES was chosen as a platform to enable easier access for village communities and related stakeholders. This study involves analyzing the needs of village officials, system design, website development, and implementation in several villages as case studies. The results of this research show that Website-Based SINPERDES using the Waterfall method has succeeded in increasing information accessibility, monitoring village development, as well as coordination between village officials and the community. In addition, the use of the Waterfall method in SINPERDES development provides clarity and order in the software development process. The successful implementation of SINPERDES provides an opportunity to improve the overall quality of village development
Overview: Machine Learning for Fine Particle Matter Estimation Based on Remote Sensing: Tinjauan: Algoritma Random Forest untuk Estimasi PM2.5 Berbasis Pengindraan Jauh Sri Nadriati
Computer Science and Information Technology Vol 3 No 3 (2022): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v3i3.4380

Abstract

Studi ini merangkum penelitian tentang estimasi PM2.5 menggunakan algoritme pembelajaran mesin random forest (RF), penginderaan jauh, dan keduanya. Tujuan dari tinjauan ini adalah menyajikan studi yang komprehensif untuk memfasilitasi dan menentukan batasan, luas dan kedalaman pengetahuan yang dieksplorasi untuk memperkirakan konsentrasi PM2.5 di masa depan menggunakan RF dan pengindraan jauh. PM2.5 merupakan parameter lingkungan atmosfer yang penting, terutama karena dampaknya terhadap kesehatan manusia dan lingkungan. Terlepas dari skala spasial-temporal, perkiraan PM2.5 yang akurat penting untuk memahami dan menanggapi berbagai efek buruk dari polusi udara. Oleh karena itu, metode penginderaan jauh dan pembelajaran mesin dikembangkan untuk mendapatkan estimasi PM2.5 resolusi tinggi dan mengurangi kesalahan penilaian yang disebabkan oleh dislokasi spasial. Sejak penggunaan pertama jaringan saraf (NN) untuk mempelajari hubungan kompleks AOD-PM2.5, lebih dari 40 artikel terkait ML telah diterbitkan dalam dekade terakhir, dan lebih dari 90% di antaranya telah diterbitkan dalam lima tahun dan 75% dalam tiga tahun terakhir. Metode validasi yang mempertimbangkan pola spasial dalam validasi model ML mengungkapkan bahwa RF dan BPNN adalah yang paling populer digunakan.
Sistem Penunjang Keputusan Pemilihan Teknologi ERP Menggunakan Pendekatan MFEP pada UMKM Coffee Shop Rizki Ananda, Lidya; Sri Nadriati; Muhammad Ikhlas; Chandra Kusuma; Julianto Simatupang
Jurnal Teknologi Informasi (JUTECH) Vol 6 No 1 (2025): JUTECH: Jurnal Teknologi Informasi
Publisher : ITB Ahmad Dahlan Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32546/jutech.v6i1.3111

Abstract

The rapid development of digital technology requires various business sectors, including coffee shops, to adopt systems that improve operational efficiency and service quality. Enterprise Resource Planning (ERP) is a strategic solution to integrate various business processes centrally. However, the wide variety of ERP options with different features and costs necessitates an appropriate evaluation method to select the system that best fits business needs. This study uses the Multi-Factor Evaluation Process (MFEP) method to assist coffee shops in choosing the best ERP technology based on criteria such as cost, features, user-friendliness, security, and technical support. The results indicate that Odoo ERP is the recommended option due to its modularity, ease of use, cost flexibility, and adequate community and technical support. Proper ERP implementation is expected to enhance efficiency, effectiveness, and competitiveness of coffee shop businesses in an increasingly competitive market.
Analysis Of Employee Discipline Based On Digital Attendance With The K-Means Algorithm Method Yulya Muharmi; Sri Nadriati
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 5 No. 2 (2022): Jurnal Teknologi dan Open Source, December 2022
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v5i2.2628

Abstract

Employee discipline is one of the most important factors for the progress of the company. PT. Sumatra Core Cellular (PT. SIS) Pekanbaru has implemented a digital attendance application, but the company has not evaluated the application to determine the level of employee discipline. Data mining is the process of extracting useful information from a large database population. One of the data mining methods is the K-Means algorithm. The data mining process uses the method of K-Means algorithm with 2 clusters namely discipline and less disciplined categories. The data used is attendance data of 159 employees, namely data on tardiness, non-attendance (TAP), attendance hours and 4 selected questionnaire questions. Tools for grouping with the Rapidminer application. Using the K-Means algorithm method, it is known that cluster 0 consists of 133 employees or 83.64% with a disciplined category and cluster 1 produces 26 employees or 16.35% with a less disciplined category. Judging from the accuracy of attendance hours, employees in cluster 0 are more likely to be present at 07.45 - 08.15 and in cluster 1 they are more likely to be present at 08.15 - 08.30. In terms of lateness and TAP, there is a lack of discipline in cluster 1. From the level of satisfaction with the application based on 4 selected questions, it can be concluded that the digital attendance application increases the discipline of the employees. The results of this analysis can be used as a reference for evaluating employee discipline, determining promotions and improving employee discipline in the future.
Co-Authors CHANDRA KUSUMA Indradewa, Rhian Julianto Simatupang Nurafina Siregar Putra, Randi Rian Yanti Yusman Yulya Muharmi