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Dimas Aulia Trianggana
Universitas Dehasen Bengkulu
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Journal : jurnal media computer science

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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.
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