Article Per Year (5 Year)
p-Index From 2021 - 2026
2.195
P-Index
This Author published in this journals
All Journal Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) JURNAL ILMIAH INFORMATIKA Journal Information System Development Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Brahmana : Jurnal Penerapan Kecerdasan Buatan Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat JURNAL LIGA ILMU SERANTAU Computer & Science Industrial Engineering Journal
Yenni, Yusli
Universitas Nahdlatul Ulama Sumbar
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 25 Documents
Search

 1   2   3 
IMPLEMENTASI SISTEM PAKAR DALAM MENDIAGNOSIS PENYAKIT PNEUMONIA PADA ANAK Yenni, Yusli; Khaerini, Nini
Jurnal Liga Ilmu Serantau Vol. 2 No. 2 (2025): Edisi Agustus - Jurnal Liga Ilmu Serantau
Publisher : LPPM Universitas Ibnu Sina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jlis.v2i2.1238

Abstract

Pneumonia is a disease with a high mortality rate in children. Pneumonia is an acute respiratory infection and is a disease that is often suffered by children and remains a high cause of child mortality in Indonesia. This occurs due to the still limited knowledge of parents and the lack of medical personnel and treatment facilities, especially in certain areas. This becomes a major point causing delays in disease treatment, resulting in death in children. This research aims to develop and implement a rule-based expert system. Knowledge can assist in the process of diagnosing pneumonia in children. This expert system knowledge is a system that can solve a problem by using the mindset of an expert implemented into the system. This system is built using the forward chaining method in diagnosing pneumonia. The forward chaining method is known as data-driven reasoning because this method searches starting from data or facts that are already known as input. It also searches for appropriate rules, then decisions can be made based on the rules that have been created. The interface implementation uses a web-based system using the PHP programming language and a MySQL database, which can be accessed by the public for consultation. It is hoped that this system will assist relevant parties, especially those with limited knowledge of pneumonia. It will also help medical professionals and the government reduce the child mortality rate due to this disease.
Jaringan Saraf Tiruan Menjaga Keamanan Data dengan Metode Bidirectional Associative Memory Yenni, Yusli
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 5, No 1 (2023): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v5i1.282

Abstract

System security is currently very much needed from irresponsible parties who damage and steal data. For this reason, a system is needed that is able to protect and secure data from criminal acts. The aim of this research is to provide data codes and keys using binary conversion using the Continuous BAM method. The Continuous BAM method, namely Bidirectional Associative Memory (BAM), has the ability to act as associative memory or content addressable memory, namely memory that can be called up using part of the information stored in it. Apart from that, the Bidirectional Associative Memory (BAM) Artificial Neural Network (ANN) has 2 layers and is fully connected from one layer to the other, so it is possible to have a reciprocal relationship between the input layer and the output layer. The final results of this research are 6 patterns that are entered into the search process, including number patterns 1, 3, 4, 5, 7, and 9 with input vector values of numbers 1 [16,-22], numbers 3 [20, 22], numbers 4 [16,-22], number 5 [20,6], number 7 [24,2] and number 9 [20,18], which do not match the pattern number 7. Requested target [1,-1], result obtained [1,1]. The Continuous Bam method can be used to detect patterns correctly and accurately.
ANALISIS BACKWARD CHAINING MENGIDENTIFIKASI VIRUS TANAMAN CABAI Yenni, Yusli; Mahendra, Ikhsa
Jurnal Liga Ilmu Serantau Vol. 1 No. 2 (2024): Edisi Agustus - Jurnal Liga Ilmu Serantau (JLIS)
Publisher : LPPM Universitas Ibnu Sina

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36352/jlis.v1i2.867

Abstract

Tanaman cabai salah satu komoditas sayuran yang banyak permintaan di kalangan Masyarakat. Tingkat produksi tanaman cabai di Sumatera barat dari tahun mengalami kenaikkan. Sehingga banyak Masyarakat Sumatera barat mulai membudidayakan tanaman cabai ini. Hal ini juga dimanfaatkan oleh Masyarakat pasaman bara khususnya daerah tandikek yang mulai memudidayakan tanaman cabai yang menjadi bagian penting dalam perekonomian local. Namun hal tersebut menimbulkan permasalah yang Dimana masih minim pengetahuan masyarak tentang penyakit tanaman cabai yang di akibatkan oleh virus. Sistem pakar merupakan suatu system yang dalam penyelesaian masalah menggunakan pola pikir seorang pakar. Pola pikir ini yang nanti di implementasikan kedalam suatu system yang nanti digunakan untuk memecahkan suatu masalah. Proses inferensi yang digunakan untuk memecahkan masalah dalam system pakar menggunakan pelacakan mudur (backward chaining) yang di ambil dari penalaran pengamatan dari hasil dengan mencari beberapa fakta-fakta yang mendukung sehingga mendapatkan Kesimpulan. Pengimplementasi ke system web dengan menggunakan Bahasa pemograman PHP dan database Mysql yang nantinya dapat di akses oleh Masyarakat sebagai media konsultasi.
PEMBERDAYAAN STRATEGI PEMASARAN DAN KEUANGAN KOMPETITIF UNTUK PENINGKATAN KEUNTUNGAN USAHA MIKRO, KECIL, DAN MENENGAH (UMKM) PADA PASAR DIGITAL KUBE HISHAN STRAWBERY Yuliana, Liza; Yenni, Yusli
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 5, No 2 (2025): Desember 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v5i2.5392

Abstract

Abstract: The purpose of this community service is to improve the managerial capacity and competitiveness of the Hishan Strawberry Joint Business Group (KUBE) in facing market dynamics, especially in the digital realm. The main problems faced by MSMEs often include inaccuracy in mapping consumer needs, difficulty in setting competitive prices, limited promotional reach, and less than optimal financial performance evaluation. This program is designed with four main intervention focuses, namely: (1) In-depth socialization regarding consumer needs analysis and strategic target market selection; (2) Value-based pricing training to ensure consumer purchasing power while maintaining profitability; (3) Workshop on developing effective digital marketing and advertising strategies to expand reach; and (4) Technical guidance in simple financial performance evaluation to measure the effectiveness of marketing activities and ensure profitability. The implementation method uses a participatory action research approach through interactive workshops, case studies, and ongoing mentoring. The expected output is the creation of MSMEs that are able to apply measurable marketing strategies, have competitive price advantages, and can independently analyze their business profitability. A significant contribution of this service is to provide a holistic framework that integrates marketing and financial aspects as the key to the sustainability and growth of MSME profits in the digital market era. Keyword: MSME Empowerment, Digital Marketing Strategy, Competitive Pricing, Financial Analysis, KUBE Hishan Strawberry. Abstrak: Tujuan dari pengabdian kepada masyarakat ini adalah untuk meningkatkan kapasitas manajerial dan daya saing Kelompok Usaha Bersama (KUBE) Hishan Strawberry dalam menghadapi dinamika pasar, terutama di ranah digital. Permasalahan utama yang dihadapi UMKM seringkali meliputi ketidaktepatan dalam pemenuhan kebutuhan konsumen, kesulitan menetapkan harga yang kompetitif, keterbatasan jangkauan promosi, dan evaluasi kinerja keuangan yang belum optimal. Program ini dirancang dengan empat fokus intervensi utama, yaitu: (1) Sosialisasi mendalam mengenai kebutuhan konsumen dan pemilihan target pasar yang strategis; (2) Pelatihan penetapan harga berbasis nilai untuk menjamin daya beli konsumen sambil mempertahankan profitabilitas; (3) Workshop penyusunan strategi pemasaran dan periklanan digital yang efektif untuk memperluas jangkauan; serta (4) Bimbingan teknis dalam evaluasi kinerja keuangan sederhana untuk mengukur efektivitas aktivitas pemasaran dan memastikan tercapainya keuntungan. Metode pelaksanaannya menggunakan pendekatan penelitian aksi partisipatif melalui lokakarya interaktif, studi kasus, dan pendampingan berkelanjutan. Luaran yang diharapkan adalah terciptanya UMKM yang mampu menerapkan strategi pemasaran terukur, memiliki keunggulan harga kompetitif, dan secara mandiri dapat melakukan analisis profitabilitas usahanya. Kontribusi signifikan pengabdian ini adalah menyediakan kerangka kerja holistik yang mengintegrasikan aspek pemasaran dan keuangan sebagai kunci keinginan dan pertumbuhan keuntungan UMKM di era pasar digital. Kata kunci: Pemberdayaan UMKM, Strategi Pemasaran Digital, Penetapan Harga Kompetitif, Analisis Keuangan, KUBE Hishan Strawberry.
data mining Implementasi Data Mining Menggunakan Algoritma Apriori dalam Memprediksi Persediaan Pupuk Tanaman di Toko Marni: Data Mining Dea Puspita Unu; Yusli Yenni
JURNAL ILMIAH INFORMATIKA Vol 14 No 01 (2026): Jurnal Ilmiah Informatika (JIF)
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v14i01.10674

Abstract

This research aims to apply the Apriori algorithm to predict the inventory of plant fertilizers at Toko Pupuk Marni. The primary focus of this study is to analyze sales transaction data as a means to enhance the efficiency of inventory management. The background of this research is rooted in the difficulties faced in managing inventory due to inefficient manual recording, which can lead to excess or shortage of stock. The method employed in this study is data mining, with the Apriori algorithm as the main technique for identifying purchasing patterns and relationships among items in the data. The analyzed data includes fertilizer sales transactions during the year 2024. The analysis results indicate that the Apriori algorithm can generate significant association rules, such as the relationship between Apsa and Rovral fertilizers, with a confidence level reaching 53.2%. Testing conducted using RapidMiner shows results consistent with manual analysis, thereby demonstrating the effectiveness of the Apriori algorithm in uncovering customer purchasing patterns. These findings provide valuable insights for store managers in determining better inventory strategies based on historical data. Thus, this research is expected to contribute significantly to the development of inventory information systems in the agricultural sector and serve as a reference for future studies related to data mining and inventory management.
Co-Authors Andreas, Yose Dea Puspita Unu Dedy Saputra Dedy Saputra Diana, Nia Ebitwan Famati Saro Ndruru Ellbert Hutabri, Ellbert Fajrin, Rifaldi Fariska, Muhammad Yogi Febrianto, Wahyu Gultom, Heman Hottua Intan Utnasari james simatupang Khaerini, Nini Lenny Husna M. Ichsan Alfajri Mahendra, Ikhsa Mega Rahmawati Ndruru, Ebitwan Famati Saro Rangga Pradana Putra Utnasari, Intan Wahyu Febrianto Wicaksono, Dicky Eko Yuliana, Liza