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Journal : KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal)

ANALYSIS OF MODIFIED K-MEANS CLUSTERING IN DECISION SUPPORT OF INDUSTRIAL PARTNER GROUPING Billy Sabella; Veri Julianto; Ahmad Rusadi Arrahimi
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 9, No 1 (2022)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v9i1.429

Abstract

Internship is part of achieving the competencies expected in the educational process. Therefore, the suitability of students to companies that serve as a place for street vendors is something important to pay attention to. Weaknesses in the previous system, there are still many students who are not right in choosing companies/agencies. They are still not paying attention to the competencies expected in this internship process. This study aims to help group industrial partners according to the competency achievements of each department. The method used in this research is Modified K-Means Clustering in the grouping process. While the criteria used are the suitability of the company's field with the department, credibility, company ecosystem, company track record in the field of education, and the facilities provided. In carrying out this work, a system will be developed to process the data resulting from the questionnaire so that groups from each company are obtained. The results of the study were obtained from 86 respondents who were apprentices who had been in 37 companies or agencies. 22 questions that build 7 criteria resulted in 4 stable clusters after 8 iterations.Keywords: internship, decision support system, Modified K-Means Clustering.
SISTEM PAKAR PENYAKIT KESEHATAN MENTAL REMAJA MENGGUNAKAN METODE FORWARD CHAINING DAN CERTAINTY FACTOR Eka Wahyu Sholeha; Billy Sabella; Wiwik Kusrini; Shanty Komalasari
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 10, No 1 (2023)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v10i1.523

Abstract

Mental health is something that every individual must have. It is important to understand about mental health from an early age, especially in adolescents. The initial diagnosis of mental health is currently still visiting a psychologist or psychiatrist. This is what makes teenagers feel embarrassed to visit a psychologist or psychiatrist. Expert systems can help diagnose mental health diseases early. Solving problems for early diagnosing adolescent mental health disorders using an expert system with the Forward Chaining and Certainty Factor methods. The research was aimed at adolescents in the South Kalimantan region. The expert data in this study were taken from a psychologist in Banjarbaru, South Kalimantan. The results showed that the Expert System for Adolescent Mental Health Diseases Using the Forward Chaining and Certainty Factor Methods had an accuracy rate of 86.67% of the 15 data held by experts, 13 data were the same as the system.Keywords: expert system, Forward Chaining, and Certainty Factor Kesehatan mental merupakan sesuatu yang pasti dimiliki oleh setiap individu. Pentingnya untuk memahami mengenai kesehatan mental sejak dini terutama pada remaja.  Diagnosa awal kesehatan mental saat ini masih mengunjungi psikolog atau psikiater.  Hal ini yang membuat remaja merasa malu untuk berkunjung ke  psikolog atau psikiater.  Sistem pakar dapat membantu mendiagnosa awal penyakit Kesehatan mental. Penyelesaian masalah untuk mendiagnosa secara dini gangguan kesehatan mental remaja menggunakan sistem pakar dengan metode Forward Chaining dan Certainty Factor. Penelitian ditujukan kepada remaja wilayah Kalimantan Selatan. Data pakar dalam penelitian diambil dari salah satu psikologi yang berada di Banjarbaru, Kalimantan Selatan. Hasil penelitian menunjukkan Sistem Pakar Penyakit Kesehatan Mental Remaja Menggunakan Metode Forward Chaining dan Certainty Factor memiliki tingkat akurasi yaitu 86,67% dari 15 data yang dimiliki pakar, 13 data sama dengan sistem. Kata kunci: sistem pakar,  Forward Chaining, dan Certainty Factor