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All Journal JURNAL ILMIAH INFORMATIKA Jurnal Teknologi dan Informasi Merpati: Media Publikasi Pengabdian Kepada Masyarakat Politeknik Pos Indonesia
Woro Isti Rahayu
Jurusan Teknik Informatika, Politeknik Pos Indonesia
Humanities Computer Science & IT Education

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IMPLEMENTASI ALGORITMA K-MEANS CLUSTERING TINGKAT KEPENTINGAN TAGIHAN RUMAH SAKIT DI PT PERTAMINA (PERSERO) ema ainun novia; Woro Isti Rahayu; Syafrial Fachri Pane
JURNAL ILMIAH INFORMATIKA Vol 8 No 01 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (580.059 KB) | DOI: 10.33884/jif.v8i01.1844

Abstract

Claims are claims that can be in the form of money, services or goods that are the obligations of another party to an entity. Problems that occur in this department do not yet have information about the bills to be paid based on their level of importance.Therefore this study aims to create a billing grouping system based on the level of importance in each hospital using a data mining algorithm with the K-means method. This method is considered appropriate because of group data based on the closest cluster center point with the data. Billing based on hospitals into 2 clusters namely urgent cluster (C1) and non-urgent cluster (C2).From the calculation of 104 data samples consisting of 4 hospitals, 14 data are in the "Urgent" cluster (C1), 90 data are in the "Not Urgent" cluster (C2). The results are then grouped again based on hospitals so that the grouping obtained at Pertamina Center hospitals cluster 1 there are 3 data and cluster 2 there are 2 data. Pertamina Jaya hospital for cluster 1, there is 1 data and in cluster 2 there are 44 data. In Pertamina Balikpapan hospital for cluster 1, there is 7 data and for cluster 2 there are 25 data. And at Pertamina Plaju hospital for cluster 1 there is 1 data and for cluster 2 there is 13 data.
ANALISIS DAN PERANCANGAN SISTEM TICKETING MANAGEMENT SERVICE OPERATION PADA PT TELKOM INDONESIA MENGGUNAKAN METODE WEIGHTED PRODUCT Annisa Cahyani; Woro Isti Rahayu
JURNAL ILMIAH INFORMATIKA Vol 8 No 02 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i02.1863

Abstract

Based on observations where is conducted at PT. Telkom Indonesia in the JABAR REGIONAL 3 Bandung office, especially in the MSO (Management Service Operation) division, is one of the divisions at PT. Telkom Indonesia, which has roles and responsibilities in the construction and maintenance of networks and others. However, the current implementation of the MSO (Management Service Operation) division still has constraints, where the constraints experienced lead to the handling of disturbances which are sometimes less than optimal. The less-than-maximum service in question is the handling of ticketing complaints of disturbances experienced by users or users who are waiting to do the ticket request assignment by the back end (specialist) so that the problem is immediately handled and resolved. Another problem experienced is if there are several reports of complaints of interference PT. Telkom Indonesia is experiencing problems on the network that are not handled quickly, because it is difficult to determine the priority handling of interference complaint tickets. So to overcome these problems, an application of the ticketing management service operation system is used to determine the priority of the handling of the noise ticketing response to disturbance using the weighted product method. Based on the available alternatives will be processed in accordance with the weight of the criteria to obtain the final results and ranking, from the results of the ranking can be known interference complaints which should be prioritized based on the calculation results.
SISTEM APLIKASI DATA PEGAWAI PENSIUN MENGGUNAKAN METODE K-MEANS Seta Permana; Woro Isti Rahayu
JURNAL ILMIAH INFORMATIKA Vol 8 No 02 (2020): Jurnal Ilmiah Informatika (JIF)
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/jif.v8i02.1883

Abstract

Division or work unit of Human Resources (HR) in PT. Kawasan Berikat Nusantara (PT. KBN) (Persero) has job desks including finding and accepting new employees at PT. KBN, handles the process of receiving employee salaries, handles employee data management including employee retirement data. The problem with managing employee pension data is that there is no system that can handle this. So this research aims to be able to help in making a system that fits the needs for managing retirement employee data. By determining the pension application for employees at the age of 51-53 years with an existing position at PT. KBN, namely, head of division, section head, section head, and executive. In determining this, the Clustering method will be used, namely K-means. This method is considered appropriate because it can group data based on the Cluster 's closest center point with the data. Classification of employees based on age and position into 2 groups, namely the submission of pensions at the age of 51 years filing a pension submission of retirement at the age of 53. From the results that have been calculated from 56 data of employees aged 51-53 years resulted in 21 employees being submitted in retirement age 51 years, 35 employees in filing retirement 53 years.
Pengembangan Aplikasi Layanan Surat Keterangan (Studi Kasus Desa Ciwaruga) Rifqi Fathurrohman; Rakasona; Woro Isti Rahayu; Noviana riza; Santoso
Merpati: Media Publikasi Pengabdian Kepada Masyarakat Politeknik Pos Indonesia Vol. 4 No. 1 (2022): Merpati
Publisher : LPPM Politeknik Pos Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36618/merpati.v4i1.2398

Abstract

Jurnal ini mengulas tentang implementasi aplikasi surat pelayanan desa menggunakkan media online yang semula dilakukan secara offline menjadi online. Selama ini sistem pelayanan pembuatan surat di kantor desa ciwaruga menggunakan pelayanan dalam bentuk sistem informasi manual, dibuatlah sistem informasi berbasis online untuk mempermudah dalam pengerjaan kegiatan surat menyurat di desa ciwaruga, penelitian ini bertujuan untuk mempermudah prasarana yang ada dalam kantor desa ciwaruga kabupaten bandung barat.
Optimalisasi Strategi Pemasaran dengan Segmentasi Pelanggan Menggunakan Penerapan K-Means Clustering pada Transaksi Online Retail Eriskiannisa Febrianty Luchia Awalina; Woro Isti Rahayu
Jurnal Teknologi dan Informasi (JATI) Vol 13 No 2 (2023): Jurnal Teknologi dan Informasi (JATI)
Publisher : Program Studi Sistem Informasi, Fakultas Teknik dan Ilmu Komputer, Universitas Komputer Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/jati.v13i2.10090

Abstract

Pemahaman yang baik mengenai pelanggan sangat penting untuk menjalankan bisnis bagi suatu perusahaan. Mengenali dan memahami setiap pelanggan dapat membantu menciptakan komunikasi dalam menyampaikan penawaran produk dengan menyesuaikan kebutuhan dan memberikan layanan yang disesuaikan setiap pelanggan. Namun, dalam mengidentifikasi setiap kebutuhan pelanggan tidak mudah, karena faktanya menganalisis pelanggan adalah area yang sangat luas. Hal ini dapat mencakup berbagai karakteristik dan perilaku pelanggan yang berbeda. Oleh karena itu, diperlukan segmentasi pelanggan untuk mengelompokkan pelanggan berdasarkan perilaku dan karakteristik. Untuk melakukan segmentasi pelanggan berdasarkan data, banyak model dan algoritma telah digunakan, dan dalam penelitian ini, metode clustering menggunakan algoritma K-means menjadi salah satu pilihan yang efektif. Metode ini telah menjadi tren dan banyak digunakan dimana hal tersebut dibuktikan dengan banyak nya jurnal terkait dari rentang tahun 2018 - 2022. Penelitian ini menggunakan pemrograman python untuk proses data mining dan pre-processing yang dilakukan pada data melalui exploratory data analysis untuk memahami informasi dari data yang digunakan sebelum melakukan klasterisasi. Dalam penerapan metode K-means, digunakan metode elbow untuk menentukan jumlah klaster yang optimal. Hasil dari metode elbow menunjukkan bahwa penggunaan 4 klaster adalah pilihan yang tepat dalam kasus ini. Selanjutnya, pemodelan K-means dengan 4 klaster dilakukan menggunakan variabel quantity, unit price, dan customer id, dan menghasilkan 4 klaster yang berbeda dengan karakteristik yang spesifik pada masing-masingnya. dapat diamati bahwa kuantitas dan harga satuan berperan penting dalam mempengaruhi perilaku pelanggan.
Co-Authors Annisa Cahyani ema ainun novia Eriskiannisa Febrianty Luchia Awalina Noviana Riza Rakasona Rifqi Fathurrohman Santoso Seta Permana Syafrial Fachri Pane