The Sriwijaya University Library

  • Home
  • Information
  • News
  • Help
  • Librarian
  • Login
  • Member Area
  • Select Language :
    Arabic Bengali Brazilian Portuguese English Espanol German Indonesian Japanese Malay Persian Russian Thai Turkish Urdu

Search by :

ALL Author Subject ISBN/ISSN Advanced Search

Last search:

{{tmpObj[k].text}}
Image of KLASIFIKASI KECENDERUNGAN TINGKAT DEPRESI MAHASISWA MENGGUNAKAN LEARNING VECTOR QUANTIZATION 3

Text

KLASIFIKASI KECENDERUNGAN TINGKAT DEPRESI MAHASISWA MENGGUNAKAN LEARNING VECTOR QUANTIZATION 3

Putri, Desry Kencana - Personal Name;

Penilaian

0,0

dari 5
Penilaian anda saat ini :  

Depression is a serious health problem experienced by students and is often not realized. Depression needs to be known early on to reduce depression or prevent students from experiencing depression. This study aims to classify the tendency of the level of depression experienced by students which consists of three classification classes, namely, mild depression, moderate depression, and major depression. Classification in this study was carried out using the learning vector quantization 3 (LVQ 3) method. The LVQ 3 algorithm has two winning distances, namely the first closest distance (Dc) and the second closest distance (Dr). In this study, the input data used amounted to 120 data based on filling out The Patient Health Questionnaire (PHQ-9) questionnaire by the respondents. The input variables used are name, gender, semester, and symptoms of depression. Based on the results of testing on 120 data with the distribution of training data and test data of 90:10, 80:20, and 70:30 as well as a combination of specified learning parameters, the highest average accuracy reaches 99.35% at 90:10 data sharing. The best combination of learning parameters are learning rate 0.3, windows 0.3 and 0.4, epsilon 0.2, minimum learning rate 0.02 and learning reduction 0.1. Keywords: Depression, learning vector quantization 3, classification, college students, PHQ-9.


Availability
Inventory Code Barcode Call Number Location Status
2207003126T77213T772132022Central Library (Referens)Available but not for loan - Not for Loan
Detail Information
Series Title
-
Call Number
T772132022
Publisher
Inderalaya : Jurusan Teknik Informatika, Fakultas Ilmu Komputer Universitas Sriwijaya., 2022
Collation
xxiii, 154 hlm.; ilus.; 29 cm
Language
Indonesia
ISBN/ISSN
-
Classification
005.730 7
Content Type
-
Media Type
-
Carrier Type
-
Edition
-
Subject(s)
Jurusan Teknik Informatika
Struktur Data
Specific Detail Info
-
Statement of Responsibility
SEPTA
Other version/related

No other version available

File Attachment
  • KLASIFIKASI KECENDERUNGAN TINGKAT DEPRESI MAHASISWA MENGGUNAKAN LEARNING VECTOR QUANTIZATION 3
Comments

You must be logged in to post a comment

The Sriwijaya University Library
  • Information
  • Services
  • Librarian
  • Member Area

About Us

As a complete Library Management System, SLiMS (Senayan Library Management System) has many features that will help libraries and librarians to do their job easily and quickly. Follow this link to show some features provided by SLiMS.

Search

start it by typing one or more keywords for title, author or subject

Keep SLiMS Alive Want to Contribute?

© 2025 — Senayan Developer Community

Powered by SLiMS
Select the topic you are interested in
  • Computer Science, Information & General Works
  • Philosophy & Psychology
  • Religion
  • Social Sciences
  • Language
  • Pure Science
  • Applied Sciences
  • Art & Recreation
  • Literature
  • History & Geography
Icons made by Freepik from www.flaticon.com
Advanced Search