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Dimas Aulia Trianggana
Universitas Dehasen Bengkulu
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Penerapan Metode Moora Dalam Menentukan Pegawai Terbaik Pada Fakultas Ekonomi Dan Bisnis Universitas Bengkulu Muhammad David Bekam; Dimas Aulia Trianggana; Ahmad Arif Alfarisy
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.v22i1.9888

Abstract

Determining the best employees is an effort to provide appreciation while also motivating employee performance within the Faculty of Economics and Business at Universitas Bengkulu. This study applies the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to provide recommendations for the best employees in an objective, systematic, and data-driven manner. The method is used because it can process data based on relevant criteria and produce consistent rankings. The assessment process involves collecting data from 11 employees based on registration data for the year 2024, which is then processed using the MOORA method to obtain rankings from highest to lowest. The best employee recommendations are established for the top three rankings. Based on the calculations, the three best employees identified are Tiharman, SH, Sutomo, S.Sos, and Dahril Alpansi, SH. The results of this research are expected to serve as a reference for the faculty in determining the best employees more accurately and transparently each year
Analisis Perbandingan Metode Simple Multi Attribute Rating Technique (SMART) Dan Metode Preference Selection Index (PSI) Dalam Penentuan Guru Terbaik SD N 14 Seluma Docky Agresma; Dimas Aulia Trianggana; Desi Mahdalena
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.v22i1.10095

Abstract

Objective teacher performance assessment is an important step in improving the quality of education in schools. This study aims to analyze the comparison between the SMART (Simple Multi Attribute Rating Technique) method and the PSI (Preference Selection Index) method in determining the best teachers at SD Negeri 14 Seluma based on teacher performance assessment data for the 2023/2024 academic year. The comparison was conducted through three main aspects, namely processing time, final assessment results, and accuracy levels measured using a confusion matrix. The results showed that the SMART method had a faster processing time than the PSI method. However, both methods produced the same final results in determining the best teachers, with identical rankings. In terms of accuracy, both the SMART and PSI methods showed the same accuracy level of 80%. System testing using the blackbox method also showed that the developed application functions well and is capable of providing accurate recommendations for the best teachers each year.
The Development Of Application For Selecting Programmer Experts At The Communication, Information, And Statistics Agency Of Bengkulu Province Using Simple Additive Weighting (Saw) Method Apriani Purwita Sari; Khairil Khairil; Dimas Aulia Trianggana
Journal of Multidisciplinary Research Vol. 2 No. 2 (2026): January
Publisher : Utami Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70963/jmr.v2i2.489

Abstract

The Communication, Information, and Statistics Agency of Bengkulu Province are a local government agency that plays a role in managing public information and supporting the development of digital services. One of the agency's important needs is the availability of competent expert programmers to support the operation and development of information systems. This study aims to develop a web-based decision support system using the PHP programming language with the CodeIgniter Framework and MySQL database to facilitate the selection process of expert programmers. The Simple Additive Weighting (SAW) method was applied to produce objective assessments based on several criteria, namely age, work experience, certificates, portfolios, interviews, and competency tests, with the greatest weight given to the competency test aspect. A passing grade of 0.75 was set as the threshold for determining which applicants met the qualifications. The results of the study show that the system is capable of automatically calculating scores and rankings according to the predetermined criteria weights. The selection process is faster, more objective, and reduces the potential for errors compared to manual methods. In addition, the system reduces the need for manual recording, thereby increasing administrative efficiency. Thus, this decision support system has been proven to assist agencies in determining prospective programmer experts more accurately and transparently, and has the potential to be applied to the selection process in other government agencies.
Application Of The K-Means Algorithm in Clustering Medical Records Of BPJS Participants At Bhayangkara Hospital In Bengkulu Wahyu Rizki Rasuanto; Devi Sartika; Dimas Aulia Trianggana
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.v5i1.8941

Abstract

Grouping is to separate labels from unknown data and grouping is expected to be able to identify data groups to then be labeled as desired. Cluster analysis is a multivariate analysis technique to find and organize information about variables so that they can be relatively grouped into homogeneous groups or "clusters" can be formed.The purpose of data clustering work can be divided into two, namely grouping for understanding and grouping for use. If the goal is for understanding, the formed groups must capture the natural structure of the data, usually the grouping process in this goal is only an initial process to then be continued with core work such as summarization (average, standard deviation), class labeling in each group to then be used as classification training data and so on. K-Means is one of the clustering algorithms included in the Unsupervised Learning group which is used to divide data into several groups with a partition system. This algorithm accepts input in the form of data without class labels. In the K-Means algorithm, the computer groups the data that is its input without first knowing the target class. The input received is data or objects and k desired groups (clusters).
The Implementation Of Data Mining In Predicting The Number Of Marriages Using Least Squares Method At KUA Ulu Musi Widian Sulistio; Maryaningsih Maryaningsih; Dimas Aulia Trianggana
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.v5i1.9029

Abstract

KUA Ulu Musi Sub-district is one of KUA offices in Empat Lawang Regency that plays an important role in recording and facilitating marriage processes, including issuing permits, recording, and issuing related documents. Until now, data processing at KUA Ulu Musi has been done manually through data recording books, and the number of marriages is written on a board provided as information. Given that the number of marriages fluctuates annually from 2014 to 2023, KUA sometimes faces difficulties in ensuring the availability of documents, managing wedding queues, and preparing the necessary facilities. The implementation of data mining in predicting the number of marriages using the least squares method at KUA Ulu Musi can provide information regarding the predicted number of marriages for the following year, enabling KUA to prepare sufficient administrative staff and personnel to serve prospective couples optimally and avoid case backlogs during certain periods. Based on test data with two data conditions—odd numbers (2014–2022) and even numbers (2014–2023) the predicted number of marriages for 2023 was 166, and for 2024, it was 168. From the accuracy level testing, the accuracy level calculation yielded a MAPE error percentage of 18.43%, indicating good accuracy. This shows that the least squares method is sufficiently reliable in predicting the number of marriages at KUA Ulu Musi.
Implementasi Metode Topsis Dalam Memberikan Rekomendasi Tailor Di Kota Bengkulu M. Endri Hardinata; Liza Yulianti; Dimas Aulia Trianggana
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.v5i1.9107

Abstract

The general public requires high-quality tailoring services that are fast and within their budget. However, many consumers still struggle to choose the right tailor due to a lack of objective information about quality, price, and services offered. The implementation of the TOPSIS method in providing tailor recommendations in Bengkulu City can offer the best tailor recommendations in Bengkulu City based on consumer criteria such as price, facilities, and turnaround time, as well as provide information on each tailor in Bengkulu City, including address, contact number, operating hours, facilities, and prices. To facilitate the implementation of the TOPSIS method, a web-based application was developed using the PHP programming language with a MySQL database. The application for implementing the TOPSIS method in providing tailor recommendations in Bengkulu City can be accessed online via the URL link http://tailorkotabengkulu.online/. Based on the system testing conducted, it can be concluded that the application for implementing the TOPSIS method in providing tailor recommendations in Bengkulu City has functioned well as expected and is capable of providing tailor recommendations that align with consumer preferences.
IMPLEMENTASI METODE WEIGHTED PRODUCT UNTUK PENILAIAN PESERTA PELATIHAN TENAGA KERJA BERBASIS KOMPETENSI PADA DISNAKER KABUPATEN BENGKULU TENGAH Adjie Danang Aprianto; Devi Sartika; Dimas Aulia Trianggana
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol. 9 No. 1 (2026): February 2026
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v9i1.5750

Abstract

Abstract: The assessment of competency-based labor training participants is an important aspect in ensuring the quality and effectiveness of training programs organized by DISNAKER of Central Bengkulu Regency. However, the manual assessment process is often subjective and time-consuming. To overcome this problem, this study implemented Weighted Product (WP) method as a decision support method in the training participant assessment process. WP method was chosen for its ability to handle various assessment criteria by assigning weights according to their level of importance. This study involved several assessment criteria, such as attendance, theoretical evaluation results, practical evaluation results, and attitude during training. The results of the implementation show that WP method can provide accurate and consistent rankings and assist DISNAKER in determining the best participants objectively. Thus, this WP-based assessment system is expected to improve transparency and efficiency in the workforce training evaluation process at DISNAKER of Central Bengkulu Regency. Keywords: Weighted Product (WP), Decision Support System, Participant Assessment, Workforce Training, DISNAKER. Abstrak: Penilaian peserta pelatihan tenaga kerja berbasis kompetensi merupakan aspek penting dalam memastikan kualitas dan efektivitas program pelatihan yang diselenggarakan oleh Dinas Tenaga Kerja (Disnaker) Kabupaten Bengkulu Tengah. Namun, proses penilaian yang dilakukan secara manual seringkali kurang objektif dan memerlukan waktu yang cukup lama. Untuk mengatasi permasalahan tersebut, penelitian ini mengimplementasikan metode Weighted Product (WP) sebagai metode pendukung keputusan dalam proses penilaian peserta pelatihan. Metode WP dipilih karena kemampuannya dalam menangani berbagai kriteria penilaian dengan memberikan bobot sesuai tingkat kepentingannya. Penelitian ini melibatkan beberapa kriteria penilaian, seperti kehadiran, hasil evaluasi teori, hasil evaluasi praktik, dan sikap selama pelatihan. Hasil implementasi menunjukkan bahwa metode WP dapat memberikan hasil peringkat yang akurat, konsisten, dan membantu pihak Disnaker dalam menentukan peserta terbaik secara objektif. Dengan demikian, sistem penilaian berbasis WP ini diharapkan dapat meningkatkan transparansi dan efisiensi dalam proses evaluasi pelatihan tenaga kerja di lingkungan Disnaker Kabupaten Bengkulu Tengah. Kata Kunci: Weighted Product(WP), Sistem Pendukung Keputusan, Penilaian Peserta, Pelatihan Tenaga Kerja, Disnaker
Co-Authors Achmad Rudi Antoni Adjie Danang Aprianto Ahmad Arif Alfarisy Apriani Purwita Sari Aprianto, Adjie Danang Bella Oktavia Bima Dwi Cahya Bima Trisentyia Charles, Reno Delon Hadi Winata Desi Mahdalena Deti Karmanita Devi Sartika Dewi Suranti Docky Agresma Gitarya, Leci Hafiz Pandu Tizaldi Haryono, Mimpira Hendri Alamsyah Herlina Latipa Sari Hermawansyah, Hermawansyah Iluh Frensia Paramita Indra Kanedi Kanedi, Indra Kanedi Khairil Khairil Khairil Khairil Liandra, Viko Liza Yulianti M. Endri Hardinata Made Suardha Puspa Mardian, Harjo Maryaningsih Maryaningsih Maryaningsih, Maryaningsih Merry Rullyanti Muhammad David Bekam Mupiansa Mupiansa Nurul Aini Putri Fajar Wati Rangga Gading Satria Gading Satria sapri sapri Saputra, Virdian Sartika, Devi Syahudin, Zaki Imam Talafebher, Dos-q Cincin Tiara Pia Toibah Umi Kalsum Tutut Dwinka Utari Wahyu Rizki Rasuanto Widian Sulistio Wiwin Irianto Saputra Wulandari, Nora Yupianti, Yupianti