Article Per Year (5 Year)
p-Index From 2021 - 2026
2.943
P-Index
This Author published in this journals
All Journal Jurnal Pekommas CogITo Smart Journal JURNAL PENDIDIKAN TAMBUSAI E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Jurnal Teknik Informatika (JUTIF) IAIC Transactions on Sustainable Digital Innovation (ITSDI) CSRID DIPANEGARA KOMPUTER TEKNOLOGI INFORMATIKA (DIPAKOMTI) DIPANEGARA KOMPUTER SISTEM INFORMASI (DIPAKOMSI)
Wilem Musu
Universitas Dipa Makassar
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Social Sciences

Published : 18 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : CogITo Smart Journal

 1 
Sistem Pakar Otomatisasi Baku Mutu Limbah Pertambangan Nikel Menggunakan Algoritma Supervised Mechine Komang Aryasa; Wilem Musu
CogITo Smart Journal Vol 2, No 1 (2016): CogITo Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1365.379 KB) | DOI: 10.31154/cogito.v2i1.12.28-41

Abstract

Metode buka tutup pintu pembuangan limbah secara manual  berdasarkan hasil uji laboratorium  membutuhkan waktu relatif lama. Ketika hasil uji laboratorium menyatakan proses pembuangan harus dihentikan, limbah yang tidak memenuhi standar kelayakan sudah ikut terbuang. Tujuan dari penelitian ini adalah  untuk merancang sistem pakar menggunakan algoritma Supervised Learning untuk otomatisasi standar baku limbah pertambangan nikel, algoritma ini digunakan untuk mengklasifikasikan besaran nilai kandungan unsur dalam limbah, dan digunakan untuk mengoptimalkan proses penentuan kelayakan buang limbah. Algoritma ini bekerja setelah menerima data dalam bentuk nilai-nilai kandungan unsur yang dibangkitkan oleh sebuah aplikasi simulator yang mendeteksi kadar kandungan unsur dalam air limbah. Hasil analisis tersebut digunakan untuk menentukan kelayakan pembuangan limbah. Dari 11 unsur yang dianalisis tujuh unsur memiliki bobot nilai tertinggi dalam setiap pengukuran yaitu pH, TSS, Cu, Zn, Cr(6+), Cr Total, dan Fe., sementara Support Vector Machine hanya empat unsur yang memiliki nilai bobot tertinggi dari setiap pengukuran, yaitu unsur Cd, Pb, Ni dan Co.
Meningkatkan Kinerja Akun TikTok dengan Identifikasi Pola Data Wilem Musu; Nadia Lempan; Indra Samsie
CogITo Smart Journal Vol. 10 No. 1 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i1.647.667-679

Abstract

 TikTok is a social media platform widely used to share information through short videos to achieve goals and interests in business, education, politics, government, and personal existence. Every activity on this platform is recorded and presented privately to each account owner. However, this data has not been utilized optimally to improve account performance. This research aims to offer a data analysis concept that integrates statistical and machine learning approaches to identify data patterns in each user's data collection, enabling the improvement of account performance. The approach utilizes Linear Regression, k-means, and Decision Tree methods. The results obtained show that the concept of identifying data patterns in TikTok account data has successfully developed a predictive model for video posts that can potentially increase total viewership, video plays, and audience engagement. This is achieved through optimizing video components such as captions, text, hashtags, sound genre, and video type. The outcome yielded a classification model that can predict capable component content to enhance account performance.
Co-Authors Ade Sri Devy Afrianto Palullu Andi Ariska Fajriananda Andi Irmayana Arifin, Arham Asvin Mahersatillah Suradi, Andi Bahtiar, Akbar Christiani Olivia Kondorura Cucut Susanto Dikadayanti Dikadayanti Erfan Hasmin Fajriananda, Andi Ariska Giandari Maulani, Giandari Hadis, Muhammad Sabirin Heri Saputra Idham Amri Isa Nirmawati Jannah, Fachriyahthul Juma, Muhammad Aryfuddyn Komang Aryasa Komang Aryasa Madyana Patasik Muh Taufik Reskiadi Muhammad Abdul Jabbar Muhammad Aryfuddyn Juma Muhammad Furqan Rasyid MUHAMMAD RIZAL Mushaf, Mushaf Nadia Lempan Nurdiana Nurdiana Nurul Aini Ridow Johanis, Andrew Salman Salman Samsie, Indra Samsu Alam Simpen, Wayan Sitti Aisa, Sitti Soetikno, Johny Soetikno, Y. Johny W. Sri Damayanti Sunardi Sunardi Syafruddin Muhtamar Taufik Zulhaq Jasman Wayan Simpen Windayanti Patandean Windayanti Patendean Yohannes Johny Soetikno Yulianadewi, Ina