Article Per Year (5 Year)
p-Index From 2021 - 2026
4.462
P-Index
This Author published in this journals
All Journal Jurnal Media Infotama JURNAL MEDIA INFORMATIKA BUDIDARMA JurTI (JURNAL TEKNOLOGI INFORMASI) JOURNAL OF SCIENCE AND SOCIAL RESEARCH JSAI (Journal Scientific and Applied Informatics) E-Link: Jurnal Teknik Elektro dan Informatika GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Jurnal Komputer, Informasi dan Teknologi Jurnal PADAMU NEGERI (Pengabdian pada Masyarakat Bidang Eksakta) Jurnal Dehasen Untuk Negeri Jurnal Media Computer Science Journal of Innovation Research and Knowledge Jurnal Komputer Indonesia Jurnal Komputer
Liza Yulianti
Universitas Dehasen Bengkulu
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

Published : 43 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 43 Documents
Search

 1   2   3   4   5 
Implementation Of Additive Ratio Assessment (Aras) Method For Online Reward Driver Provision M. Iqbal Syahputra; Liza Yulianti; Devi sartika
Jurnal Media Computer Science Vol 1 No 2 (2022): Juli
Publisher : Fakultas Ilmu Komputer Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v1i2.2706

Abstract

Giving rewards to online drivers is one of the annual agendas carried out at Grab Bengkulu Branch to encourage driver motivation and professionalism in improving the quality of work. The obstacles faced in giving these rewards are due to the diversity of educational backgrounds, experiences, competencies and portfolios of the drivers, so we need a system that can assist in the process of giving rewards to drivers so that they do not become sluggish and experience difficulties. In the process of designing the application of this reward decision support system using the ARAS approach. The ARAS method is a method based on the intuitive principle that alternatives must have the largest ratio to produce an optimal solution. The ARAS method performs ranking by comparing the value of each criterion on each alternative by looking at the weights of each to obtain the ideal alternative. The implementation of the system uses the Visual Basic 2010 programming language. From the results of the tests carried out, it can be concluded that the best employee with a value of 0.90, the lowest value of 0.81
Decision Support System Determination Of Achieving Students Using The Promethe Method At Smk Negeri 4 Kepahiang Jepri Haji Utama; Liza Yulianti; Dewi Suranti
Jurnal Media Computer Science Vol 1 No 2 (2022): Juli
Publisher : Fakultas Ilmu Komputer Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v1i2.2708

Abstract

SMK Negeri 4 Kepahiang is one of the State Vocational High Schools located in Kepahiang Regency, Bengkulu Province. So far, the assessment system for outstanding students in schools is carried out by registering students and looking at 4 aspects of the assessment, namely the value of knowledge, the value of absenteeism, the value of non-academic achievement, the value of attitudes and behavior. The determination process is still done manually, where the four aspects will be compared between one student and another so that it can be known with various considerations, so that 3 outstanding students are obtained from the number of students. This is of course an obstacle for the school, because sometimes it is difficult to determine outstanding students and it takes quite a long time. The Decision Support System for determining outstanding students at SMK Negeri 4 Kepahiang was made using the Visual Basic .Net programming language and SQL Server 2008r2 database, where in the application one of the Decision Support System Methods (SPK) was applied, namely the Promethee Method. This application can be used as an alternative in assisting the school in determining outstanding students each academic year. The Decision Support System for determining outstanding students at SMK Negeri 4 Kepahiang begins with student assessment data which is then processed into the Promethee Method according to the stages of the method, so as to produce a final score by sorting the highest score to the lowest value. Based on the assessment data for the 2021/2022 Academic Year as many as 4 students, the outstanding student was Alim Predika with a net flow value of 0.42..
The Basis Of Ratio Analysis For The Selection Of Majors At SMA Negeri 1 In Kepahiang Regency Epan Susandi; Liza Yulianti; Eko Suryana
Jurnal Media Computer Science Vol 1 No 2 (2022): Juli
Publisher : Fakultas Ilmu Komputer Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v1i2.2744

Abstract

SMA Negeri 1 is one of the schools in Kepahiang regency which annually routinely conducts major selection for the students. This major is intended so that later students can complete school according to their interests and abilities before continuing to a higher level. The current major selection process has weaknesses, including taking a long time and also the results obtained are less accurate because there could be many mistakes because there is no special application to support these calculations. In addition, the element of subjectivity is quite high because the criteria used are still few and less relevant. To overcome this problem, a decision support system is made to determine the selection of majors. This study used the method of multi-objective optimization on the basis of ratio analysis (MOORA) with the criteria of the value of report cards for science subjects, social studies scores, mathematics scores, Indonesian language scores, and the average value of report cards. The implementation of the system uses the Visual Basic 2010 programming language and the method used in this research is the Waterfall method. The final result was that the decision support system with the MOORA method was able to overcome problems in the process of selecting majors at SMA Negeri 1 Kepahiang Regency.
TINGKAT PEMAHAMAN SISWA TERHADAP MATA PELAJARAN SELAMA PANDEMI COVID-19 DENGAN ALGORITMA C4-5 Kemas Muhammad Fadli; Liza Yulianti; Feri Hari Utami
Journal of Innovation Research and Knowledge Vol. 2 No. 8: Januari 2023
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53625/jirk.v2i8.4622

Abstract

Algoritma C4.5 dapat digunakan untuk meneliti berbagai macam hal diantara nya adalah prediksi penerimaan calon siswa baru, loyalitas pelanggan dan lain lain, algoritma C4.5 adalah salah satu dari algoritma yang memiliki decision tree, Algoritma C4.5 merupakan algoritma klasifikasi dengan teknik pohon keputusan yang terkenal dan disukai karena memiliki kelebihan-kelebihan. Kelebihan ini misalnya dapat mengolah data numeric (kontinyu) dan diskret, dapat menangani nilai atribut yang hilang, menghasilkan aturan-aturan yang mudah diintrepetasikan dan tercepat diantara algoritma-algoritma yang lain. Dalam pengembangan web pada HTML yang memungkinkan dibuatnya aplikasi dinamis yang memungkinkan adanya pengolahan data dan pemrosesan data. Semua sintax yang diberikan akan sepenuhnya dijalankan pada server sedangkan yang dikirimkan ke browser hanya hasilnya saja. Kemudian merupakan bahasa berbentuk script yang ditempatkan dalam server dan diproses di server pada sistem Pemahaman Siswa Terhadap Mata Pelajaran Selama Pandemi COVID-19 Dengan Algoritma C.45.
PENERAPAN METODE PREFERENCE SELECTION INDEX (PSI) DALAM SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KINERJA PERAWAT depa supitri suharjun; Liza Yulianti; Lena Elfianty
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 2 (2023): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i2.5220

Abstract

Sistem Pendukung keputusan merupakan disiplin ilmu sistem informasi yang fokus dalam mendukung dan meningkatkan pengambilan keputusan manajerial, sebuah teknologi komputer yang dapat digunakan untuk mendukung pengambilan keputusan dan penyelesaian masalah yang kompleks. Metode Preference Selection Index (PSI)  merupakan metode untuk memecahkan multi kriteria pengambilan keputusan (MCDM). Dalam metode yang diusulkan itu tidak perlu untuk menetapkan kepentingan relative antara atribut. Penilaian kinerja pada dasarnya merupakan faktor kunci guna mengembangkan suatu organisasi secara efektif dan efisien, karena adanya kebijakan atau program yang lebih baik atas sumber daya manusia yang ada dalam organisasi. Penilaian kinerja individu sangat bermanfaat bagi dinamika pertumbuhan organisasi secara keseluruhan, melalui penilaian tersebut maka dapat diketahui kondisi sebenarnya tentang bagaimana kinerja karyawan. Keperawatan merupakan suatu bentuk layanana kesehatan profesional yang merupakan bagian integral dari layanan kesehatan yang berlandaskan ilmu  dan kiat keperawatan bebentuk layanan bio, psiko, sosial, dan spiritual yang komprehensif yang ditujukan bagi individu, keluarga, dan masyarakat, baik dalam keadaan sehat ataupun sakit.
PENERAPAN METODE PREFERENCE SELECTION INDEX (PSI) DALAM SISTEM PENDUKUNG KEPUTUSAN PENILAIAN KINERJA PERAWAT depa supitri suharjun; Liza Yulianti; Lena Elfianty
JSAI (Journal Scientific and Applied Informatics) Vol 6 No 2 (2023): Juni
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v6i2.5220

Abstract

Sistem Pendukung keputusan merupakan disiplin ilmu sistem informasi yang fokus dalam mendukung dan meningkatkan pengambilan keputusan manajerial, sebuah teknologi komputer yang dapat digunakan untuk mendukung pengambilan keputusan dan penyelesaian masalah yang kompleks. Metode Preference Selection Index (PSI)  merupakan metode untuk memecahkan multi kriteria pengambilan keputusan (MCDM). Dalam metode yang diusulkan itu tidak perlu untuk menetapkan kepentingan relative antara atribut. Penilaian kinerja pada dasarnya merupakan faktor kunci guna mengembangkan suatu organisasi secara efektif dan efisien, karena adanya kebijakan atau program yang lebih baik atas sumber daya manusia yang ada dalam organisasi. Penilaian kinerja individu sangat bermanfaat bagi dinamika pertumbuhan organisasi secara keseluruhan, melalui penilaian tersebut maka dapat diketahui kondisi sebenarnya tentang bagaimana kinerja karyawan. Keperawatan merupakan suatu bentuk layanana kesehatan profesional yang merupakan bagian integral dari layanan kesehatan yang berlandaskan ilmu  dan kiat keperawatan bebentuk layanan bio, psiko, sosial, dan spiritual yang komprehensif yang ditujukan bagi individu, keluarga, dan masyarakat, baik dalam keadaan sehat ataupun sakit.
PENERAPAN METODE ASOSSIATION RULE MINING (ARM) UNTUK MEMPREDIKSI JUMLAH STOK PRODUK PADA SWALAYAN FADHILLAH BENGKULU Irfan Wendiyansa; Liza Yulianti; Ila Yati Beti
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 1 (2024): February 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i1.1683

Abstract

Abstract: Management of product sales data at Supermarket Fadhillah Bengkulu is still done manually. There is no system that helps predict the amount of product stock and the problem that is often faced is the scarcity of supply of products that are in demand at Supermarket Fadhilla. For decision making in determining the amount of product inventory that can be adjusted to market demand, Fadhilla Supermarkets does not yet use a system and is still calculating manually. Therefore, this research was carried out with the aim of implementing the Association Rule Mining (ARM) method in grouping sales data at the Fadhilla Supermarket. So you can easily determine and classify high product sales. The system implementation uses the PHP programming language and MySQL database and the method used in this research is the waterfall method. After carrying out the Association Rule Mining (ARM) process at the Fadhilla Supermarket with data testing, the results obtained were the highest level of product sales at the Fadhilla Supermarket, Bengkulu. This can be used as a reference by Supermarket Fadhilla for product supplies for the following month. Based on the results of calculations on sales transaction data using the Association Rule Mining (ARM) method with a minimum support of 50% and a minimum Confidance of 75%, the association value of the Association Rule Mining (ARM) method is 93.75%. Keywords: data mining, asossiation rule mining (ARM), swalayan fadhilla Abstrak: Pengelolaan data penjualan produk di Swalayan Fadhillah Bengkulu masih dilakukan secara manual. Belum terdapatnya sistem yang membantu dalam memprediksi jumlah stok produk dan permasalahan yang sering dihadapi adalah kelangkaan pasokan produk yang laris di Swalayan Fadhilla. Untuk pengambilan keputusan dalam menentukan jumlah persediaan produk yang dapat disesuaikan dengan permintaan pasar Swalayan Fadhilla belum menggunakan sistem dan masih dihitung secara manual. Oleh karena dilakukan penelitian ini dengan tujuan untuk mengimplementasikan metode Asossiation Rule Mining (ARM) dalam pengelompokan data penjualan pada Swalayan Fadhilla. Sehingga dengan mudah dapat menentukan dan mengklasifikasikan penjualan produk yang tinggi. Implementasi sistem menggunakan bahasa pemrograman PHP dan Database MySQL dan metode yang digunakan dalam penelitian ini adalah metode waterfall. Setelah dilakukan proses Asossiation Rule Mining (ARM) pada Swalayan Fadhilla dengan uji data maka didapatkan hasil tingkat penjualan produk tertinggi di Swalayan Fadhilla Bengkulu. Hal ini dapat dijadikan acuan oleh Swalayan Fadhilla untuk persediaan  produk bulan berikutnya. Berdasarkan hasil perhitungan terhadap data transaksi penjualan menggunakan metode Asosiation Rule Mining (ARM) dengan minimal support 50% dan minimum Confidance 75% maka nilai asosiasi metode Asosiation Rule Mining (ARM) sebesar 93,75%. Kata kunci: data mining, asossiation rule mining (ARM), swalayan fadhilla
Drug Data Clustering Based on Total Inventory and Total Demand for Drugs Using the K-means Clustering Method at Pajar Bulan Health Center Saputra, Robi; Yulianti , Liza; Elfianty , Lena
Jurnal Komputer, Informasi dan Teknologi Vol. 2 No. 1 (2022): Juni
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v2i1.784

Abstract

At Pajar Bulan Health Center, drug supply data processing is already using office application packages, namely Microsoft Word and Excel. The application package is used for making monthly usage reports, requests and drug supplies. Constraints that often occur are that it takes a long time to manage drug inventory data because they have to record one by one the amount of drug use and the number of drug requests to be made. The number of requests is carried out every month by looking at the latest drug supply, if the stock starts to run low then a request is made. However, it is possible that the stock has run out before making a request, this results in a lack of drug supply management. Drug data clustering is carried out based on the amount of supply and the number of requests for drugs at the Pajar Bulan Health Center through the K-Means Clustering Method approach. To help cluster the drug data, an application was built using the Visual Basic .Net programming language and SQL Server 2008r2 database. Clustering of drug data is carried out in units of pcs in 2021 where the amount of inventory is reduced by the number of requests for drugs, so that the results obtained are 2 drugs enter cluster I and 27 drugs enter cluster II. good and the application can help the Pajar Bulan Health Center in knowing the grouping of drug data based on 2 groups, namely the few clusters and the large clusters
Clasterization Of Data Using Contraceptive Equipment At Puskesmas Kampung Bali, Bengkulu City Using K-Means Method Tessa, Prara Sindia Citra; Yulianti , Liza; Sari , Herlina Latipa
Jurnal Komputer, Informasi dan Teknologi Vol. 2 No. 1 (2022): Juni
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v2i1.786

Abstract

Kampung Bali Health Center is one of the health centers in Bengkulu City. The health center serves the family planning program by providing contraceptives, such as pills, injections, condoms, IUDs, and implants. The data processing on supplies and expenditures of contraceptives is done manually by filling in the form provided. It will be recapitulated by the officer to know the use of contraceptives for 1 year. Unfortunately, this procedure is not efficient because it takes time and sometimes there are miscalculations that cause errors in determining the supply of contraceptives. Moreover, the health center needs data on most in demand and least desirable contraceptives. The application of data clusterization on contraceptive use at the Kampung Bali Health Center in Bengkulu City is used to assist the Health Center in managing monthly contraceptive data, and to assist the Health Center in finding out which contraceptive information is most in demand and the least desirable. The K-Means Clustering methodology applied in this research is used in order to divide the contraceptive data into 2 groups; Cluster C1 (the most popular) and Cluster C2 (the least desirable) based on an analysis of the amount of supply and use of contraceptives. There are 60 participants in this study, where Cluster C1 consisted of 24 data and Cluster C2 consisted of 36 data, with the percentage value of C1 clustering 40% and C2 60%. Based on the test, it shows that the functional application of clustering data on contraceptive use at the Kampung Bali Health Center in Bengkulu is running well. It also give beneficial information about data clasterization of contraceptives.
Application of the Simple Additive Weighting (SAW) Method in Recommended Skripsi Topics Sari, Tengsi Mayang Nopita; Yulianti , Liza; Sartika , Devi
Jurnal Komputer, Informasi dan Teknologi Vol. 2 No. 2 (2022): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v2i2.953

Abstract

Students were confused by the selection of thesis topics from the 3 thesis topics to be discussed in research, thus slowing down the thesis submission process and some students did not submit titles during semester 7. thesis topic, one way is by utilizing information technology systems. The recommendation application for thesis topics at the Management Study Program, Faculty of Economics, University of Dehasen Bengkulu, was made using the Visual Basic .Net programming language and SQL Server 2008r2 database. In the application, one of the Decision Support System (DSS) methods has been applied, namely the Simple Additive Weighting (SAW) method which is used to help determine recommendations for final semester student thesis topics based on the value of the courses obtained by students. There are 3 thesis topics in the Management Study Program, Faculty of Economics, University of Dehasen Bengkulu, namely finance, human resources, and marketing with a course value of 17 courses. Recommendations for this thesis topic are given per student by generating course grades for each student. Based on the results of the black box test, the functional application of the thesis topic recommendation at the Management Study Program, Faculty of Economics, Dehasen Bengkulu University has been running properly and is able to display the results of the thesis topic recommendation for each student through the stages of the SAW method.
Co-Authors Abdussalam Al Akbar Aji Sudar sono Aji Sukmo Annisa Dwi Putri Asnawati Asnawati Asnawati Asnawati Ayu Mayang Sari Belyna Novellya Cahyani, Cendi Nur Cahyani, Lindry Dwi Cahyono, Trisna Dani, Ragil Fadilla Rahma Dari, Erika Dwi Ulan Devi Sartika Devi Sartika Dewi Suranti Eko Putra Membara Eko Suryana Eko Suryana Elfianty , Lena Ema Sastri Puspita Epan Susandi Ernawati Ernawati Feri Hari Utami Feri Hari Utami Fezi Fadwa Rendika Fredricka, Jhoanne Fredricka, Jhoanne Gragrista M, Avelyn Hari Aspriyono Hastuti, Silvia Wahyu Herlina Latipa Sari Ila Yati Beti Indra Kanedi Irfan Wendiyansa Irvan Ciantury Jaswan, Mali Jepri Haji Utama Juju Jumadi Juju Jumadi Kanedi , Indra Kanedi, Indra Kanedi Kemas Muhammad Fadli Lena Elfianty Lianda, Deri Liza Yulianti M. Iqbal Syahputra Ninti Putriani Prahasti Prahasti , Prahasti Prara Sindia Citra Tessa Pratiwi, Annisa Putri Reno Supardi Rita Nilawati Rizka Tri Alinse Robi Saputra Rodi Rodi Sapri Sapri Saputra, Robi Sari, Tengsi Mayang Nopita Sartika , Devi Setiaji, Ganang Supardi, Reno Tengsi Mayang Nopita Sari Tessa, Prara Sindia Citra Toibah Umi Kalsum Vobey Alex Sander Yanolanda Suzantri H Yuisar Yuisar Yupianti Yupianti Yupianti Yupianti, Yupianti Zuhri, M. Khoiruddin