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Journal : Jurnal Media Infotama

MENENTUKAN POLA PEGAWAI HONORER DI DINAS PERUMAHAN KAWASAN PEMUKIMAN DAN PERTANAHAN DALAM PENERAPAN METODE K-MEANS Alinse, Rizka Tri; Sari, Venny Novita; Sallaby, Achmad Fikri
Jurnal Media Infotama Vol 17 No 1 (2021)
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v17i1.1316

Abstract

The Housing, Settlement Areas and Land Service of Bengkulu Province is a government agency in Bengkulu Province. Performance assessment using a predetermined form. This agency has 11 honorary employees. Every year an evaluation of the performance of honorary employees will be carried out to make decisions and consideration for honorary employee contracts. The aim of this research was to apply the K-Means Method to determine the pattern of honorary employees in the Housing, Settlement and Land Service of Bengkulu Province and to create an application that could provide information on the pattern of honorary employees in the Housing, Settlement and Land Service of Bengkulu Province. The application of the K-Means Method in determining the Pattern of Honorary Employees in the Housing, Settlement and Land Services Department of Bengkulu Province was made using the Visual Basic .Net programming language and SQL Server 2008 Database. The grouping of honorary employee data is based on the results of performance assessments that have been carried out, which in this case There are two to four groups that can be used to differentiate between one honorary employee and another. The results of this grouping can later be used as consideration for the Bengkulu Province Housing, Settlement and Land Services Department to determine who will be contracted for the following year. Based on the results of the tests that have been carried out, the application in determining the pattern of honorary employees can provide information to the Housing, Settlement and Land Services Department of Bengkulu Province as to who is eligible to be given a new contract from the results of grouping performance assessment data for honorary employees.
Pengelompokan Barang Menggunakan Metode K-Means Clustering Berdasarkan Hasil Penjualan Di Toko Widya Bengkulu Sallaby, Achmad Fikri; Alinse, Rizka Tri; Sari, Venny Novita; Ramadani, Tri
Jurnal Media Infotama Vol 18 No 1 (2022): April
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v18i1.2126

Abstract

The Widya shop sells various kinds of hijab products that are tailored to the needs of fashion development. The Widya Bengkulu store also sells various kinds of women's needs such as clothes, accessories, bags, wallets, soft lenses, cosmetics and other fancy items. So far, Widya Store has not used computers as a data processing medium. All processes of selling goods and inventory of goods are still carried out with book records, and do not yet have an application that can help the process of managing the data of these goods. In addition, in managing inventory, Toko Widya only sees stock based on sales results, if the stock on one of the items runs out, an order will be made to the supplier. Implementation of the K-Means Clustering Method in Grouping Goods Based on Sales Results at the Widya Bengkulu Store was made using the Visual Basic .Net programming language and SQL Server 2008 database. In the Grouping of Goods Based on Sales Results at the Widya Bengkulu Store, it will be processed to seek knowledge from chunks of data, namely goods sales data. Cluster I is a Very Selling Item, Cluster II is a Self Selling Item, and Cluster III is a Less Selling Item. Based on the results of the tests that have been carried out, the application of Grouping Goods Based on Sales Results at the Widya Bengkulu Store can provide information on the best-selling items sold at the Widya Store.
Rancang Bangun Aplikasi Pemesanan Makanan Di Kedai Bakso Solo Mas Tulus Berbasis Android Dengan Metode Highest Ratio Next (Hrn) Nova, Tria; Kalsum, Toibah Umi; Alinse, Rizka Tri
Jurnal Media Infotama Vol 18 No 2 (2022): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v18i2.2654

Abstract

ABSTRACT The Food Ordering Application at Kedai Bakso Solo Mas Tulus aims to change the ordering system that previously only used general applications to become special applications and provide the best to customers therefore customers get maximum service. To get the best service by using a special application using the Highest Ratio Next method, the order will be calculated based on the arrival of the order and the length of time the order is processed so that consumers who order with different arrival times and with different processing times will get a fair order completion time. For Kedai Bakso Mas Tulus, with this special application and with the Highest Ratio Next method, it will change the presentation process of orders that were made previously. Therefore, with the development of a Food Ordering Application at Kedai Bakso Solo Mas Tulus based on Android with the Highest Ratio Next (HRN) it can assist in the process of serving food orders made by consumers. This system can help Kedai Bakso Mas Tulus in determining the best food presentation quickly and precisely. Keywords: Food Ordering Application Design, HRN, Kedai Bakso Mas Tulus.
Penerapan Metode Smart Dalam Memilih Ekstrakurikuler Siswa Di SMA Negeri 08 Seluma Arliyan, Arliyan; Sapri, Sapri; Alinse, Rizka Tri
Jurnal Media Infotama Vol 20 No 2 (2024): Oktober
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i2.6565

Abstract

High school 08 Seluma has 7 (seven) extracurricular activities that students can choose, namely male volleyball, female volleyball, male futsal, female futsal, Paskibraka, Pramuka and Tahsin. In helping students to choose the appropriate extracurricular recommendations, there are assessment criteria consisting of 5 criteria, namely interest, talent, experience, parents’ permission and extracurricular achievement. The implementation of SMART Method in choosing extracurricular activities at High school 08 Seluma can help provide extracurricular recommendations for students that are appropriate and in accordance with student assessment criteria, and it can be used as a forum for managing extracurricular activity data at High school 08 Seluma. Based on the tests that have been carried out, the results show that the implementation of SMART method in choosing extracurricular activities at High school 08 Seluma has run well and in accordance with expectations and the application can provide information on the results of recommendations for selecting student extracurricular activities based on the score values that have been given.
Penerapan Metode Regresi Linear Dalam Prediksi Hasil Penangkapan Ikan Pada Dinas Kelautan Dan Perikanan Provinsi Bengkulu Anto, Gebi Andre; Kanedi, Indra; Alinse, Rizka Tri
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.v21i1.7541

Abstract

Abstract— The Department of Marine and Fisheries of Bengkulu Province is one of the government agencies in Bengkulu Province. At the Department, every year data collection is carried out per semester of capture fisheries production that occurs in each regency / city in Bengkulu Province. The purpose of the research is to determine the predicted value of capture fisheries production in the coming year. The implementation of the linear regression method in predicting fishing yields at The Department of Marine and Fisheries of Bengkulu Province can help provide an estimated prediction of the amount of capture fisheries production in the following year based on the results of processing previous time series data through the Linear Regression Method. In addition, it can be used as an evaluation material for the Department of Marine and Fisheries of Bengkulu Province in making strategic plans (renstra), especially capture fisheries production. Based on the test data used, the results show that the prediction of the amount of fishing (marine fisheries) in the Regency / City of Bengkulu Province in 2024 is South Bengkulu Regency, 2726.3 Central Bengkulu Regency, 1663.62 North Bengkulu Regency, 7709.04 Kaur Regency, 8140.2 Bengkulu City, 44457.32 Muko-muko Regency, 19691.99 and Seluma Regency, 2633.8. It can be seen that the highest number of fishing products is Bengkulu City and the least is Central Bengkulu Regency from the results of prediction analysis using the linear regression method. Keywords: Linear Regression Method, Prediction, Fishing Result.
Penerapan Metode K-Means Dalam Pengelompokan Data Siswa Berdasarkan Masalah Akademik Di SMA Negeri Selangit Asher, Chindy; Fredricka, Jhoanne; Alinse, Rizka Tri
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.v21i2.9370

Abstract

Selangit State High School does not yet have a system that can help identify students' academic problems. Until now, the school has only manually recorded each student's disciplinary violations as a point system by observing the violations committed by students, and at the end of the semester, all violation points are calculated. However, this process takes a considerable amount of time, as each student's violation points must be calculated individually, resulting in a lengthy process to determine the appropriate sanctions for each student. The application of the k-means method in grouping student data based on academic issues at Selangit State Senior High School can help the school obtain more specific information regarding students' academic issues and can be used as a benchmark in assisting with evaluations and counseling for students grouped based on academic issues. Based on the test data used in the odd semester of the 2024/2025 academic year, involving 30 students who committed violations, the results showed that cluster C1 had 12 students with sanctions in the form of reprimands, cluster C2 had 10 students with written warnings, cluster C3 had 0 students with suspension warnings, cluster C4 had 5 students with disciplinary action, and cluster C5 had 3 students.