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PENERAPAN DATA MINING UNTUK MENGANALISA POLA PERMINTAAN PEMASANGAN CCTV DENGAN MENGGUNAKAN METODE MARKET BASKET ANALYSIS STUDY KASUS CV. MITRA JAYA PERKASA Ramadhan Pandapotan Siringo–Ringo; Melda Panjaitan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1627

Abstract

CV. MITRA JAYA PERKASA is a company engaged in CCTV installation services where demand for CCTV installation is one of the important factors. Therefore it is very important to know the cctv installation request pattern so that it can adjust to the warehouse stock and the cctv goods linkage. With the help of computers can be used as a solution to the problem, where by building a data mining system which is a knowledge-based computer program that provides solutions to problems and get information from large data warehouses. In this case the company can analyze the cctv installation request pattern using the market basket analysis method. It is expected that this data mining can provide information on the cctv installation request pattern and adjust the warehouse stock. The results of this study are an application that can help analyze the cctv installation request patterns and analyze the relationship of goods using the market basket analysis method.Keywords: Data Mining, Market Basket Analysis, cctv installation request patterns.
Active Tectonic Segmentation on the Micro Plate of Northern Sumatra Based on Distribution of Earthquake Epicenter in July 2020 Nesia Sabrina Marbun; Melda Panjaitan; Triya Fachriyeni; Eridawati
Journal of Computation Physics and Earth Science (JoCPES) Vol 1 No 2 (2021): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63581/JoCPES.v1i2.01

Abstract

The main goal of this study to increase awareness of earthquake activity due to local faults that have so far received "less attention". Continuous observations can be made on site (on active faults), by using portable seismographs and/or by utilizing the Indonesia Tsunami Early Warning System (Ina-TEWS) network broadband sensors adjacent to these active faults. However, observing using a Portable Seismograph for a long period of time will certainly require a large amount of money. Therefore, it will be more effective to utilize data from seismic sensors that are relatively close to the suspected faults. Based on the analysis that has been carried out, it can be concluded that, in the period from July 1, 2020 to July 31, 2020, there have been 79 earthquakes in the North Sumatra region, with magnitudes between 2.0 – 5.2. The location of the earthquake was dominated by land earthquakes with shallow depths, namely 0-60 km with 54 events and at sea 25 occurrences. The most earthquake occurrences in the period 01 July 2020 - 31 July 2020 occurred around Cluster 1 (local fault Aceh Central, Batee-A, Aceh South, Pidie Jaya and Lot Aceh North, Seulimeum-South), namely 15 earthquake events, so it is classified as a cluster. which is very active in the July 2020 period. In the July 2020 period, seismic activity around the Tripa 2 and Oreng local faults was low compared to other local faults in Northern Sumatra, while in June 2020 there was no seismic activity around the Tripa local faults. 2, and the Oreng fault.
Optimasi Penerimaan Siswa Baru dengan Penerapan Algortima Text Mining dan TF-IDF Y Ayu Putri Gabriella S; Guidio L Ginting; Melda Panjaitan
Journal of Computing and Informatics Research Vol 2 No 3 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/comforch.v2i3.941

Abstract

Sekolah Menengah Pertama Yayasan Perguruan merupakan salah satu sekolah yang banyak diminati oleh beberapa kalangan, dikarenakan jurusan yang bermacam-macam yang ada pada sekolah tersebut. Pada saat ini sekolah tersebut masih terbilang banyak memiliki permasalahan dalam penerimaan siswa baru nya. Banyak data yangmasuk tidak sesuai dengan apa yang telah diterima, dengan demikian sekolah perlu menerapkanperancangan aplikasi dalam penerimaan siswa baru agar dokumen dan data yang diterima lebih konkret, tidak hanya itu dengan menerapkan metode tersebut, pengerjaan dan proses pemasukan data dapat memberikan hasil yang maksimal. Metode yang digunakan dalam penelitian ini yaitu text mining dan TF- IDF,text mining sendiri yaitu metode yang memiliki tahapan untuk menemukan data menjadi lebih efektif dan akurat. Selain itu metode TF-IDF pun memiliki cara pengerjaan yang dapat dikatakan efisien dengan cara menghitung bobot pada setiap kata. Sistem penerimaan siswa baru ini dibangun menggunakan software dreamweaver, dan bahasa pemograman HTML, CSS, dan JavaScript serta menggunakan database MySQL sebagai database server. Hasil dari penelitian menggunakan metode ini dapat memberikan kemudahan pihak sekolah dan calon siswa dalam penerimaan siswa baru yang dilakukan secara online maupun offline, sehingga pendataan, dan penerimaan siswa baru dapat dilakukan dengan sistem otomatis yang tidak perlu menggunakan cara kerja yang bertele-tele.