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All Journal Jurnal Ilmiah Teknologi dan Rekayasa Jurnal Mantik Journal of Computer System and Informatics (JoSYC)
Handayani, Endah Tri Esti
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Automotive Engineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology

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IMPLEMENTASI DATA MINING UNTUK MENENTUKAN TINGKAT PENJUALAN PAKET DATA TELKOMSEL MENGGUNAKAN METODE K-MEANS CLUSTERING Handoko, Suhandio; Fauziah, Fauziah; Handayani, Endah Tri Esti
Jurnal Ilmiah Teknologi dan Rekayasa Vol 25, No 1 (2020)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/tr.2020.v25i1.2677

Abstract

Perkembangan industri telekomunikasi saat ini sangat pesat karena telekomunikasi sudah menjadi kebutuhan utama bagi masyarakat sehingga banyak perusahaan yang bergerak di industry telekomunikasi. Banyaknya industry Telekomunikasi menuntut para pengembang untuk menemukan strategi atau suatu pola yang dapat meningkatkan penjualan dan pemasaran produk, salah satu strateginya adalah dengan memanfaatkan data transaksi. Paket data merupakan produk dibidang telekomunikasi. Proses Clustering saat ini masih di lakukan secara manual sehingga membutuhkan waktu, proses perhitungan dan ketelitian yang tinggi. Pada penelitian ini dibuat aplikasi berbasis website dengan tujuan untuk mempermudah Clustering data sehingga dapat digunakan sebagai referensi dalam perencanaan promosi produk telkomsel ke berbagai daerah. Metode yang digunakan untuk mengatasi permasalahan tersebut yaitu metode Clustering dengan menggunakan Algoritma K-Means. Algoritma K-Means merupakan algoritma pengelompokkan sejumlah data menjadi menjadi kelompok-kelompok data tertentu. Pada penelitian ini data penjualan dikelompokkan menjadi 3 yaitu data penjualan rendah, data penjualan sedang dan data penjualan tinggi. Pengujian clustering dengan algoritma K-Means pada aplikasi terhadap data transaksi penjualan paket telkomsel diperoleh persentase kesesuaian yaitu 100% dibandingkan dengan clustering manual.
Implementation of the Waterfall Method for Designing Sisar (Archive Information System) at the National University: Implementation of the Waterfall Method for Designing Sisar (Archive Information System) at the National University Inastiana, Fardila; Triayudi, Agung; Handayani, Endah Tri Esti
Jurnal Mantik Vol. 4 No. 1 (2020): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

Often with the development of increasingly sophisticated times we are required to follow it. One of them is in making system that can be applied to the community in various ways to facilitate its use. In an organization/institution a system is needed to facilitate the regulation of incoming and outgoing data. Especially in the case of letter archiving. Because after conducting a case study at the National University Administration Bureau, it was found that managing the filing of letters was still done manually and was not well organized, therefore a neat and orderly information system was needed. In this archive system it is necessary to store, update incoming and outgoing letters and provide reports of incoming outgoing letters if needed. It is hoped that with the realization of this archive system, managing correspondence is more structured and helps in the complete information process.
Kombinasi Metode Certainty Factor dan Fuzzy Tsukamoto dalam Pradiagnosa Penyakit Gagal Ginjal Kronis Adityawan, Rudi; Triayudi, Agung; Handayani, Endah Tri Esti
Journal of Computer System and Informatics (JoSYC) Vol 4 No 2 (2023): Februari 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i2.2911

Abstract

Expert systems aim to combine human knowledge with systems, that is, so that computers can solve problems in the same way that experts usually do. Expert systems can also be used in diagnosing disease to determine the type of disease suffered as an initial diagnosis based on the symptoms to be followed up. In this study, the method used to develop an expert system for chronic kidney failure was using the Fuzzy Tsukamoto and Certainty Factor methods. The data search process starts from the symptoms experienced by the user and lab results of anemia, creatinine and eGFR then the final results obtained from this study are an Expert System Application for pre-diagnosing Kidney Disease with the Tsukamoto Method and Certainty Factor. The results obtained from this study, namely the certainty factor method obtained a patient's disease confidence level of 99.48% where according to these results according to experts and with the Fuzzy Tsukamoto method the results obtained for the stage of chronic kidney failure were 73.9 where these results were included in the VV High Risk category.
Co-Authors Adityawan, Rudi Agung Triayudi Fauziah Fauziah Handoko, Suhandio Inastiana, Fardila