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All Journal ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JIKEM: Jurnal Ilmu Komputer, Ekonomi dan Manajemen Journal of Informatics Management and Information Technology
Diansyah, T.M
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Humanities Computer Science & IT Economics, Econometrics & Finance Environmental Science Library & Information Science

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Clustering Pola Penjualan yang Efektif dan Transparan Menggunakan Metode K-Means pada PT MNC Kabel Medicom Pauzi, Riky; Diansyah, T.M; Budiman, Arief
JIKEM: Jurnal Ilmu Komputer, Ekonomi dan Manajemen Vol 5 No 1 (2025): JIKEM: Jurnal Ilmu Komputer, Ekonomi dan Manajemen
Publisher : Universitas Muhammadiyah Enrekang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

PT. MNC Kabel Mediacom merupakan penyedia layanan televisi kabel dan internet berlangganan berbasi serat optik. PT.MNC kabel Mediacom didirikan pada januari 2013 sebagi bagian dari Global Mediacom (MNC Group) yang fokus Dengan menggunakan infrastruktur terkini Fiber to the Home (FTTH) Fiber to the x (FTTX) merupakan suatu format penghantaran isyarat optik dari pusat penyedia (provider) ke kawasan pengguna dengan menggunakan serat optik sebagai medium penghantaran. Perkembangan teknologi ini tidak terlepas dari kemajuan perkembangan teknologi serat optik yang dapat mengantikan penggunaan kabel konvensional.DAFTAR LAMPIRAN. PT.MNC Kabel Mediacom saat ini telah banyak melakukan transaksi penjualan khususnya di Kota Medan Sumatera Utara. Sistem pola penjualan pada Mediacom saat ini memiliki masalah yaitu kurang efektif dan transparan dalam penjualan seperti sisa kabel yang di pasang akan di salah digunakan atau pun di transaksikan kepada teknisi provider yang lain, serta ada kecurangan harga di lapangan atas unsur kerjasama oleh karyawan pada saat transaksi sehingga kinerja kurang transparan. Oleh karena itu penulis ingin mengetahui sejauh mana tinggak efektivitas dan efesien clustering kebel Mediacom ini di terapkan pada saat pemasangan pada rumah, kantor, dan perusahaan.Solusi dari masalah yang terjadi pada PT.MNC Kabel Mediacom maka dalam penelitian ini penulis menggunakan data mining untuk pemecahan masalah ini. Di mana data mining adalah suatu proses ekstrasi atau penggalian data dan informasi yang benar yang belum di ketahui sebelumnya, namun dapat di pahami berguna dari database yang besar serta digunakan untuk membuat suatu keputusan bisnis yang sangat besar. Fungsinya adalah mengidenfikasi fakta-fakta kesimpulan yang disarankan berdasarkan penyaringan melalui data untuk menjelajahi pola-pola atau anomali-anomali data. Dari hasil data normalisasi di atas, menunjukkan bahwa tingkat transparan dalam melakukan penjualan kabel mediacom terletak pada cluster kedua dan dilakukan oleh dua orang yaitu Mariani dan heru dartono, dan karyawan berikutnya juga berpotensi untuk terlibat dalam penjualan kabel mediacom, karyawan tersebut bernama Ratna Sari, Surya Ningsih, dan Indiani. Cluster tersebut lebih dominan berpengaruh karena tingkat hasil normalisasi datanya pada metode yang digunakan cenderung lebih terperinci dan cenderung transparan dan efesien dalam penjualan kabel mediacom tersebut.
Implementasi Algoritma Promethee Dalam Melakukan Analisa Performa Matauang Virtual Karim, Ahmad; Diansyah, T.M; Liza, Rizko
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 6, No 2 (2022): November 2022
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v6i2.13837

Abstract

Over the last few years, digital currencies have been rapidly gaining public attention: When cryptocurrencies are created, all confirmed transactions are stored in a general ledger. All coin owner identities are encrypted to ensure the validity of the listing. Because the currency is decentralized, when the owner owns the digital coin Neither the government nor the bank has control over it. The number of performance (criteria) of each virtual currency certainly requires an appropriate method to accommodate these criteria. Virtual currency performance analysis can be used as an answer to this problem. Analysis of the performance of virtual currencies is useful for getting the best investment commodities. Performances (criteria) that can be used as a benchmark for the success of a virtual currency as an investment commodity include the price per coin, Market Capitalization, the number of twitter followers, google trends, coin price increases, the number of coins that have been traded (circulating). supply) and the total number of coins available (max supply). The result of this research is an analysis of virtual currency performance with the promethea algorithm. The purpose of this study is to analyze the level of investment need for people who want to do business in the cryptocurrency field and produce a multi-criteria preference index analysis using Promethee. Keywords: Cryptocurrency, virtual money, algorithm
Klasifikasi User Berdasarkan Trafik Http/Https Menggunakan Metode Naïve Bayes Prayoga, Eko; Diansyah, T.M; Liza, Risko
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 7, No 1 (2023): April 2023
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v7i1.15698

Abstract

Along with the times and accompanied by advances in information and communication technology, it is undeniable that at this time all activities use information technology. One of the activities is to use the internet. The research will conduct a classification based on internet usage data obtained through questionnaires using data mining techniques. The attributes that will be used in doing the classification are Name, Age, Gender, Last Education. The method used is the Naïve Bayes method, which is one of the classification techniques in data mining. Based on the research conducted, it was concluded that based on internet user data used as training data, the Naïve Bayes method succeeded in classifying 32 data from 50 data tested. So the Naïve Bayes method succeeded in predicting the magnitude of the percentage of accuracy by 64%. Keywords : Data Mining, Classification, Naïve Bayes
Pemanfaatan Algoritma K-Means Clustering Pada Sistem Rental Mobil Maesaroh, Sri Wulandari; Diansyah, T.M; Liza, Risko; Lubis, Yessi Fitri Annisa
Journal of Informatics Management and Information Technology Vol. 5 No. 3 (2025): July 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i3.391

Abstract

PT. Station Armada Indonesia is one of the companies engaged in the car rental service sector. With the many types of car choices offered, it is not uncommon for many customers to feel confused in choosing what type of car suits their needs. This problem is often experienced by customers who are confused by the many choices of car types available. In this study, the k-means algorithm was used to group cars based on several attributes. The k-means algorithm can be used to group car type data to help provide recommendations for choosing a car type. The purpose of this study is to make it easier for customers to choose the type of car that is most in demand and as material for PT. Station Armada Indonesia to respond better to market changes and achieve better results. Grouping car rental fleets based on rental prices and mileage by utilizing the k-means algorithm can help PT. Station Armada Indonesia group car types. From the grouping results, two cluster groups were obtained with the character of the first cluster being less in demand by customers and the second cluster group being the most in demand by customers. So that the company can easily prepare the type of fleet that is most in demand. In the application of data mining methods using k-means is very helpful and makes it easier for PT. Station Armada Indonesia to develop more effective marketing and offering strategies. By grouping car types with the implementation of k-means can facilitate customer knowledge in choosing car types based on customer needs.
Co-Authors Arief Budiman Karim, Ahmad Liza, Risko Liza, Rizko Lubis, Yessi Fitri Annisa Maesaroh, Sri Wulandari Pauzi, Riky Prayoga, Eko