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All Journal Jurnal Media Infotama CESS (Journal of Computer Engineering, System and Science) JURNAL MEDIA INFORMATIKA BUDIDARMA JurTI (JURNAL TEKNOLOGI INFORMASI) JOURNAL OF SCIENCE AND SOCIAL RESEARCH GATOTKACA Journal (Teknik Sipil, Informatika, Mesin dan Arsitektur) Jurnal Multidisiplin Dehasen (MUDE) Jurnal Dehasen Untuk Negeri Jurnal Media Computer Science Digital Transformation Technology (Digitech) Jurnal Dehasen Mengabdi Jurnal Karya Nyata Pengabdian Jurnal Komputer, Informasi dan Teknologi
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Universitas Dehasen Bengkulu
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Metode Forward Chaining Pada Sistem Pakar Diagonis Penyakit Tanaman Tomat Prahasti Prahasti; Nofi Qurniati; Venny Novita Sari
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5833

Abstract

Agricultural extension workers need solutions to the various difficulties faced by tomato farmers with their tomato plants. The aim of this research is to produce an expert system application in diagnosing diseases in tomato plants as an effort to help the difficulties of agricultural instructors and tomato farmers regarding problems with tomato plants by utilizing information technology through the Visual Basic programming language with a MySQL database through prior definition by experts. The method used in the research is the waterfall model, meanwhile in creating the knowledge base expert system application used is the forward chaining method. The expert system application is created to produce data that is entered into the application consisting of symptom data, disease data, solution data, solution data, rule data, as well as diagnosis (consulation) data by farmers. The output from the application created produces diagnostic results for tomato plant diseases based on the symptoms entered and solutions to the diagnoses that have been made. The results of the research are that the expert system application created can be operated well with a knowledge base using the forward chaining method and rules as a knowledge base that are in accordance with the objectives
Pengembangan Media Pembelajaran Interaktif Jaringan Komputer Berbantuan Action Script 3.0 Adobe Animated CC Di SMKN 3 Kota Bengkulu Prahasti Prahasti; Sriyanto Sriyanto; Indra Kanedi
Jurnal Media Infotama Vol 21 No 1 (2025): April 2025
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v21i1.7954

Abstract

Media pembelajaran interaktif adalah media belajar yang menggunakan teknologi digital untuk menyampaikan informasi dan mendorong interaksi aktif antara siswa dan materi pelajaran. Tujuan dari penelitian ini adalah melakukan pengembangan media pembelajaran interaktif jaringan komputer untuk membantu kegiatan pembelajaran di SMKN 3 Kota Bengkulu. Penelitian ini menggunakan model pengambangan Luther-Sutopo dengan tahapan pembuatan konsep, perancangan, pengumpulan bahan, pembuatan, pengujian dan distribusi dengan menggunakan pemrograman action script 3.0. pada aplikasi Adobe Animated CC. Hasil penelitian yaitu diperoleh media pembelajaran interaktif materi jaringan komputer yang dapat digunakan oleh guru kejuruan TKJ SMKN 3 Kota Bengkulu dalam melaksanakan kegiatan belajar. Menu-menu pada pengembangan media pembelajaran interaktif terdiri dari Menu Utama, Menu, Materi dan Menu Evalusi. Pengembangan media pembelajaran dengan menggunakan pemrograman action script 3.0 pada aplikasi Adobe Animate CC yang telah dibuat mampu memberikan manfaat kepada guru dan peserta didik di SMKN 3 Kota Bengkulu dalam meningkatkan pengetahuan dan keterampilan kejuruan melalui materi jaringan dasar komputer.
Implementasi Metode Topsis Dalam Pemilihan Tenaga Fasilitator Lapangan Pada Pembangunan Infrastruktur Di Provinsi Bengkulu Helvi Ramadhanti Rossa; Jusuf Wahyudi; Prahasti Prahasti
Jurnal Media Infotama Vol 21 No 2 (2025): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v21i2.9194

Abstract

The selection of the right field facilitator is very important in supporting the success of infrastructure development in Bengkulu Province. One method that can be used to help the objective selection process is the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The TOPSIS method focuses on selecting the alternative that is closest to the positive ideal solution and conversely, the furthest from the negative ideal solution. This study aims to implement the TOPSIS method in selecting field facilitators that are in accordance with the predetermined criteria. The criteria used in this study include experience, technical skills, managerial abilities, and competence in the field of infrastructure. Data collected from various field facilitator candidates were then analyzed using the TOPSIS method to provide the best ranking based on their proximity to the ideal solution. The results of this study are expected to provide more effective and efficient recommendations in selecting field facilitators, so that they can support the smoothness and quality of infrastructure development in Bengkulu Province
Pengelompokan Data Penduduk Di Desa Penembang Menggunakan Algoritma K-Means Clustering Untuk Program Bantuan Sosial Artha Dwika Santosa; Herlina Latipa Sari; Prahasti Prahasti
Jurnal Media Infotama Vol 22 No 1 (2026): April 2026
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v22i1.11031

Abstract

Population data clustering in Penembang Village using K-Means Clustering Algorithm-Means Clustering can help manage population data in Penembang Village, particularly in relation to social assistance. It can provide information on the results of population data grouping, which has been divided into two clusters, namely Cluster C1 (in dire need of assistance) and Cluster C2 (not in need of assistance). It can also help Penembang Village Office in determining the priority of residents who are in dire need of assistance so that social assistance programs are targeted appropriately. The desktop-based population data clustering application uses the Visual Basic.Net programming language with SQL Server database. Based on tests conducted using data from 12.5% of the total 241 households in 2024, namely 30 households, the results show that the group in dire need of assistance (Cluster C1) consists of 12 households with a percentage of 40%, and the group that does not need assistance (Cluster C2) consists of 18 households with a percentage of 60%. Based on testing of the program demo in Penembang Village Office, it is found that the population data grouping application is very easy to operate and very helpful in obtaining population data clustering information, thereby supporting the decision-making process in determining social assistance recipients in Penembang Village Office.
Revitalisasi Gotong Royong Untuk Pengelolaan Sampah Di Kelurahan Sawah Lebar Kota Bengkulu Maria Agustina Br.Nambela; Aditya Dwi Kurniawan; Ofta Prastiyo Apriansyah; Panji Dwi Atmojo; Muhammad Bendy; Prahasti Prahasti; Leni Natalia Zulita; Karona Cahya Susena
Jurnal Karya Nyata Pengabdian Vol. 2 No. 2 (2026): April
Publisher : Utami Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jknp.v2i2.568

Abstract

Gotong royong is a noble tradition of the Indonesian people that has declined in the modern era, particularly in urban areas. This study examines the revitalisation of the gotong royong culture as a strategy for sustainable waste management in RT 08 RW 02, Sawah Lebar Village, Bengkulu City. The main issues include low resident participation in collective activities, a lack of awareness regarding waste sorting, and a shortage of environmental education materials. Implementation methods included Focus Group Discussions, scheduled community work sessions, the installation of visual educational materials, waste sorting training, and a partnership with the Waste Bank. The results of the activities showed an increase in resident participation to 75%, the installation of educational signs on waste decomposition periods, the implementation of a mandatory reporting system for boarding house residents, and the successful deposit of plastic waste at the Waste Bank. This programme successfully fostered collective community awareness in maintaining environmental cleanliness by utilising the local wisdom of community cooperation.
Decision Support System For Evaluating The Performance Of Medical Personnel At Klinik Pratama Alwid Baroqah Using Vikor Method Wahyu Al-Amar; Herlina Latipa Sari; Prahasti Prahasti
Jurnal Media Computer Science Vol 5 No 1 (2026): Januari
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i1.8996

Abstract

Klinik Pratama Alwid Baroqah is one of the health clinics located in Bengkulu City. Until now, the evaluation of medical staff performance has not been systematic, making it difficult for the management of Klinik Pratama Alwid Baroqah to make appropriate decisions regarding recommendations for contract extensions, termination of employment, or employment relationships. The Decision Support System for Evaluating the Performance of Medical Staff at Klinik Pratama Alwid Baroqah using Vikor Method can serve as an alternative in decision-making for evaluating the performance of medical staff at the clinic and can assist in providing performance evaluations of medical staff at the clinic, thereby making the evaluation process more structured and systematic. This Decision Support System was developed using Visual Basic Net programming language with SQL Server database. From the test data used, involving 10 medical staff during the evaluation period from July to December 2023, the results showed that with a Vikor index value range of 0.000–0.750, 8 medical staff had their employment contracts extended, while with a Vikor index value range of 0.917–1.000, 2 medical staff did not have their employment contracts extended. Based on the system testing conducted, it can be concluded that the decision support system application for evaluating the performance of medical staff at the Klinik Pratama Alwid Baroqah has been functioning well and successfully implemented Vikor method on the performance evaluation data of medical staff according to the evaluation period and year, and displayed recommendation results for decision-making regarding each medical staff member.
Implementation Of The SAW Method In A Decision Support System To Determine The Best-Selling Products At Kz Allshop Lidia Nur Hafiza; Hari Aspriyono; Prahasti Prahasti
Jurnal Media Computer Science Vol 5 No 1 (2026): Januari
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i1.9021

Abstract

The rapid development of the business world requires quick and precise decisions in determining the best-selling products to increase sales. KZ Allshop faces challenges in determining which products have the highest demand and should get more attention. For this reason, this research aims to implement the Simple Additive Weighting (SAW) method in a decision support system (SPK) to help determine the best-selling products. SAW method was chosen for its ability to give weights to various relevant criteria, such as price, quality, and number of sales. This research collects data from various products available in the store and calculates the preference value of each product based on predetermined criteria. The implementation results show that SAW method can effectively identify the best-selling products, which helps management in making more objective and data-driven decisions. Thus, the use of SAW method in this decision support system can be an effective solution in improving the efficiency of product management at KZ Allshop.
A Decision Support System In Determining The Admission Of New Student To TJKT Vocational Program At SMK Negeri 3 Bengkulu City Using SAW Method Wijaya Anugerah Kusuma; Indra Kanedi; Prahasti Prahasti
Jurnal Media Computer Science Vol 5 No 1 (2026): Januari
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i1.10156

Abstract

The admissions of New student are an important process that determines the quality of students at a school. Until now, the selection process for prospective students at SMK Negeri 3 Bengkulu City, particularly in the Computer Network and Telecommunications Engineering (TJKT) program, has been carried out manually, which is time-consuming and prone to subjectivity in decision-making. To overcome this, this study aims to develop a Decision Support System (DSS) for new student admissions using Simple Additive Weighting (SAW) method, which can help schools determine eligible prospective students more quickly, accurately, and objectively. This system was developed using PHP programming language with MySQL database and tested using the black box method to ensure that all functions ran as required. The results of testing 15 prospective new student data for the 2025/2026 academic year showed that the system was able to display the calculation results automatically and provide recommendations on eligibility for admission. From this test, 7 prospective students were accepted and 8 prospective students were not accepted..
PENERAPAN BIG DATA ANALYTICS DALAM PREDIKSI TREN E-COMMERCE DI INDONESIA Deti Karmanita; Feri Hari Utami; Prahasti Prahasti; Dewi Harwini
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 8 No. 4 (2025): November 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i4.4587

Abstract

Abstract: The growth of e-commerce in Indonesia has been accelerating, driven by increasing internet penetration and the widespread use of mobile devices. The large, complex, and diverse volume of transaction data requires appropriate analytical methods to produce accurate trend predictions. This study aims to apply Big Data Analytics in analyzing consumer shopping patterns, popular product trends, and factors influencing purchasing decisions. Data were collected from various e-commerce platforms, processed using Hadoop and Spark, and further analyzed through predictive modeling with Machine Learning algorithms. The results indicate that integrating Big Data Analytics can improve trend prediction accuracy by up to 85% compared to conventional methods. These findings are expected to support strategic decision-making in Indonesia’s e-commerce sector. Keywords: Big Data Analytics, E-commerce, Machine Learning, Trend Prediction, Indonesia Abstrak: Pertumbuhan e-commerce di Indonesia semakin pesat, didorong oleh penetrasi internet dan meningkatnya penggunaan perangkat mobile. Data transaksi yang besar, kompleks, dan beragam membutuhkan metode analisis yang tepat untuk menghasilkan prediksi tren yang akurat. Penelitian ini bertujuan untuk menerapkan Big Data Analytics dalam menganalisis pola belanja konsumen, tren produk populer, serta faktor yang memengaruhi keputusan pembelian. Metode yang digunakan mencakup pengumpulan data dari berbagai platform e-commerce, pemrosesan menggunakan Hadoop dan Spark, serta analisis prediktif dengan algoritma Machine Learning. Hasil penelitian menunjukkan bahwa integrasi Big Data Analytics mampu meningkatkan akurasi prediksi tren hingga 85% dibanding metode konvensional, sehingga dapat mendukung strategi bisnis e-commerce di Indonesia. Kata kunci: Big Data Analytics, E-commerce, Machine Learning, Prediksi Tren, Indonesia
Co-Authors Aditya Dwi Kurniawan Agung Aprianto Agung Pradana Iskandar Ahmad Asyhari Artha Dwika Santosa Asnawati Asnawati Desi Mahdalena Deti Karmanita Devi Sartika Dewi Harwini Eko Suryana Ferdynan Mashaq Feri Hari Feri Feri Hari Utami Feri Ramadiansyah Haluan Saputra Andalah Hari Aspriyono Helvi Ramadhanti Rossa Herlina Latipa Sari Herlina Latipa Sari Jusuf Wahyudi Kanedi, Indra Kanedi Karona Cahya Susena Leni Natalia Zulita Lidia Nur Hafiza Liza Yulianti Mardiansa Mardiansa Maria Agustina Br.Nambela Maryaningsih Maryaningsih Mirnawati Mirnawati Muhammad Bendy Muhammad Sihab Nofi Qurniati Ockhy Jey Fhiter Wassalam Ofta Prastiyo Apriansyah Panji Dwi Atmojo Rahmad Arfandi Ricky Zulfiandri Sallaby, Achmad Fikri Sapri Sapri Sayka Damayanti Shely Priselia Deyanti Sriyanto Sriyanto Toibah Umi Kalsum Tri Ramadani Venny Novita Sari Victor Yonathan Gultom Wahyu Al-Amar Wijaya Anugerah Kusuma Yessi Mardiana Yupianti, Yupianti