Iman, Annas Nuril (2021) Implementasi Sistem Prediksi Anomali Pendaftar Penerimaan Peserta Didik Baru dengan Algoritma Graf. Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Penerimaan Peserta Didik Baru (PPDB) Jawa Timur sebagai sebuah sistem, setiap tahunnya melayani pendaftaran melalui halaman website resmi PPDB Jawa Timur dan selalu mengalami pengembangan dan evaluasi bersama. Termasuk yang seringkali menjadi bahan evaluasi adalah pendaftaran jalur zonasi. Jalur zonasi erat kaitannya dengan kejadian manipulasi domisili atau lokasi tempat tinggal yang menjadi tolak ukur penerimaannya. Dari akar masalah tersebut dapat bertumbuh menjadi beberapa cabang masalah baru. Oleh karena itu sistem PPDB juga perlu meningkatkan keandalan individual dengan tetap melihat peluang tekonologi yang ada. Basis data graf menjadi pertimbangan besar untuk beralih dari basis data tradisional. Neo4j, sebuah layanan basis data graf yang membentuk relasi antar data dan tidak terikat struktur model yang didefinisikan sebelumnya. Mulai dari proyeksi data menjadi model graf, analisa relasi, dan pembentukan algoritma dalam satu bahasa kueri yaitu cypher query. Menggunakan bentukan algoritma graf di atas bahasa cypher query, memberikan hasil keluaran yang baik dalam mendeteksi anomali jarak pendaftar yang terlalu dekat, anomali pendaftar yang terlempar dari sistem pemeringkatan, dan anomali sebaran gap jarak dengan dibantu pustaka formula KDE (Kernel Density Estimation) yang teramplifikasi.
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The East Java Student Admission (PPDB) as a system, is serving
registration through the official page PPDB East Java once a year
and always do development and evaluation. One thing that is often
concerned as a subject of evaluation, is the zoning system. zoning
is closely related to events in the domicile line or places of
residence which are used as the measurement locations for
acceptance and could be assumed as the problem root. The root of
the problem could grow into several new problems. Therefore, the
PPDB system also needs to improve individual capabilities while
still looking at existing technological opportunities. Graphs
Database are a big consideration for switching from a traditional
database. Neo4j, a graph database that forms relationships
between data and does not depend on the previously defined
structural model. Starting from the estimation of data into graph
models, relational analysis, and the formation of algorithms in one
language, namely cypher query. By using a graph algorithm built
on top of the Cypher query language, it gives good results in
detecting registrant distance anomalies that are too close,
registrant anomalies thrown from the ranking system, and distance
gap distribution anomalies with the help of an amplified KDE
(Kernel Density Estimation) formula library.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Uncontrolled Keywords: | kasus, graf, Neo4j, cypher query, KDE, case, graph, Neo4j, cypher query |
| Subjects: | Q Science > QA Mathematics > QA9.58 Algorithms |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis |
| Depositing User: | Annas Nuril Iman |
| Date Deposited: | 14 Aug 2021 01:33 |
| Last Modified: | 14 Aug 2021 01:33 |
| URI: | http://repository.its.ac.id/id/eprint/84894 |
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