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All Journal Teknosains: Media Informasi Sains dan Teknologi Jurnal INSYPRO (Information System and Processing) Jurnal Kesehatan Holistic
Mustikasari Mustikasari
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Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Health Professions Medicine & Pharmacology Nursing Physics Public Health

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EVALUASI BERBASIS NORMALIZE MUTUAL INFORMATION UNTUK PENGELOMPOKAN PENELITIAN DENGAN K-MEANS CLUSTERING Rahmat Rahmat; Mustikasari Mustikasari; Nur Afif
Teknosains Vol 16 No 1 (2022): Januari-April
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/teknosains.v16i1.23962

Abstract

Secara manual, aglomerasi dokumen dapat diklasifikasikan berdasarkan judul dokumen. Untuk jumlah dokumen yang tidak terlalu banyak, cara ini masih mungkin dilakukan, namun jika jumlah dokumen yang akan dikelompokkan bertambah, maka akan memakan waktu yang cukup lama. Metode yang digunakan dalam penelitian ini bekerja dengan mengklasifikasikan dokumen penelitian untuk memberikan informasi tentang hubungan antara isi penelitian yang satu dengan penelitian yang lain sehingga dapat dijadikan acuan bagi peneliti dengan fokus area yang berbeda, dalam memetakan skema kerjasama penelitian yang akan datang. Proses pengelompokan judul penelitian dilakukan dengan menggunakan metode k-Means Clustering pada sekumpulan judul penelitian dengan mengambil judul penelitian dan abstrak sebagai informasi yang dapat mewakili isi dokumen. Dokumen akan melalui proses preprocessing menggunakan metode text mining. Selanjutnya, judul dapat dikelompokkan menggunakan metode yang diterapkan. Hasilnya adalah membuat aplikasi yang secara otomatis dapat mengklasifikasikan judul penelitian untuk nilai k. Untuk mencapai keseimbangan dalam pemilihan jumlah cluster dan kualitas hasil pengelompokan, maka teknik pengujian kualitas cluster yang digunakan dalam penelitian ini adalah Normalized Mutual Information (NMI). Percobaan dilakukan dengan memasukkan jumlah cluster yang bervariasi untuk mendapatkan hasil pengelompokan terbaik dengan nilai NMI.
Terapi Kelompok Terapeutik dan Terapi Kognitif Perilaku Efektif Menurunkan Prodroma Remaja dengan Orang Tua Bercerai Malianti Silalahi; Novy H. C. Daulima; Mustikasari Mustikasari
Jurnal Kesehatan Holistic Vol 5 No 2 (2021): Jurnal Kesehatan Holistic Volume 5/Nomor 2/Juli 2021
Publisher : Sekolah Tinggi Ilmu Kesehatan RS Husada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (402.337 KB) | DOI: 10.33377/jkh.v5i2.102

Abstract

Adolescent is a growth phase that is quite vulnerable because it is a phase of searching for self-identity. At the stage of adolescent development, the role of parents is needed because it is a place for teens to ask in the process of finding their true identity. Some studies show that parental divorce primarily has a negative impact on adolescent psychology. Adolescent mental health due to divorce parents need to get treatment by knowing the initial signs and symptoms of early psychosis and providing nurses nurses' actions and specialist actions. The writing of this scientific paper explains the results of therapeutic measures of nurses, therapeutic group therapy and cognitive behavioral therapy in reducing the rate of prodroma in adolescents with divorced parents. The method used is case series. Analysis was carried out on 6 teenagers, ages 13-16 years and had divorced parents. Results: Adolescents with divorced parents had increased prodroma rates after receiving therapeutic group therapy, but there was an increase in the achievement of developmental tasks and an increase in cognitive, emotional and psychosocial developmental abilities that were the basis for reducing prodroma. Cognitive behavioral therapy reduces the rate of prodroma in adolescents with divorced parents. The need for further research related to the effectiveness of therapy with more samples.
ANALISIS KLASTER BERBASIS KEPADATAN DENGAN DBSCAN DAN OPTICS: ANALISIS KLASTER BERBASIS KEPADATAN DENGAN DBSCAN DAN OPTICS Mustikasari Mustikasari; Nur Salman
Jurnal INSYPRO (Information System and Processing) Vol 8 No 1 (2023)
Publisher : Prodi Sistem Informasi UIN Alauddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/insypro.v8i1.36347

Abstract

This paper describes the process of cluster analysis on the DBSCAN density-based clustering algorithm and the OPTICS augmentation algorithm implemented in R.. Compared to other implementations, DBSCAN offers an implementation that can leverage advanced data such as k-d trees to speed up calculations. An important advantage of this implementation is the ability of both algorithms to handle data, especially granular data with various forms, which conventional distance-based separation algorithms often cannot handle because of the difficulty of identifying the center of a data cluster. A simple comparison is shown to give insight into the advantages of this density-based method. Experiments with the implementation of DBSCAN and OPTICS compared to other popular algorithms show that DBSCAN implemented in R provides a fast, strong, and efficient solution.
Co-Authors Anny Rosiana Masithoh Budi Ana Keliat Budi Anna Keliat Novy H. C. Daulima Nur Afif Nur Salman Rahmat Rahmat Silalahi, Malianti