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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro Industrial Engineering Online Journal The Journal of Pure and Applied Chemistry Research JAIS (Journal of Applied Intelligent System) Sinkron : Jurnal dan Penelitian Teknik Informatika JST ( Jurnal Sains Terapan ) JTT (Jurnal Teknologi Terpadu) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Teknologi Sistem Informasi dan Aplikasi JSHP (Jurnal Sosial Humaniora dan Pendidikan) Jurnal Akuntansi Kompetif Infotekmesin Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] Abdimasku : Jurnal Pengabdian Masyarakat Journal of Soft Computing Exploration Jurnal Politica Dinamika Masalah Politik Dalam Negeri dan Hubungan Internasional Warta AKAB Jurnal Akuntansi, Manajemen, Bisnis dan Teknologi Industrial Research Workshop and National Seminar Nusantara Civil Engineering Journal All Fields of Science Journal Liaison Academia and Sosiety Jurnal Ilmiah Sultan Agung JPM-AKA Journal Integration of Social Studies and Business Development Social Science Academic Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Journal of English Education Assoeltan: Indonesian Journal of Community Research and Engagement Beujroh : Jurnal Pemberdayaan dan Pengabdian pada Masyarakat KANGMAS: Karya Scientific Community Service is a journal Spektrum Industri Jurnal Pendidikan Ilmu Pengetahuan Alam Jurnal Pendidikan Ilmu Pengetahuan Alam
Candra Irawan
Politeknik Negeri Balikpapan
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Optimization of Heart Failure Classification on Imbalanced Data Using a Supervised Learning Approach Based on Logistic Regression, Random Forest, and K-Nearest Neighbor: Optimalisasi Klasifikasi Gagal Jantung pada Data Imbalanced Menggunakan Pendekatan Supervised Learning Berbasis Regresi Logistik, Random Forest, dan K-Nearest Neighbor agustina, feri; Irawan, Candra; Erawan, Lalang; Suprayogi; Award Widya Laksana, Deddy; Jatmoko, Cahaya; Sinaga, Daurat; Lestiawan, Heru
Jurnal Informatika Polinema Vol. 12 No. 1 (2025): Vol. 12 No. 1 (2025)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v12i1.9071

Abstract

Heart failure remains one of the leading causes of mortality worldwide, posing significant challenges for early diagnosis and patient management. One of the major obstacles in developing predictive models for heart failure is the class imbalance problem, where the number of surviving patients far exceeds those who experience death events. This imbalance often leads machine learning algorithms to bias toward the majority class, reducing sensitivity to critical minority cases. To address this issue, this study applies the Synthetic Minority Oversampling Technique (SMOTE) to balance the dataset and improve model performance. Three supervised learning algorithms, namely Logistic Regression (LR), Random Forest (RF), and K-Nearest Neighbor (KNN), were implemented and compared on the UCI Heart Failure Clinical Records dataset containing 299 patient samples with 13 clinical attributes. Experimental results show that the Random Forest model achieved the highest performance with 90% accuracy, precision, recall, and F1-score, outperforming both LR and KNN. The findings demonstrate that combining data balancing with ensemble learning effectively enhances prediction accuracy and sensitivity toward minority classes. The main contribution of this research lies in optimizing supervised models for medical data with skewed class distributions, providing a more reliable and interpretable approach for early heart failure detection. Future research may extend this work by integrating advanced ensemble or hybrid deep learning models and expanding the dataset for multi-institutional validation
Optimasi Ultrasound-Assisted Extraction pada Rimpang Bangle Hitam (Zingiber ottensii Valeton) serta Potensinya sebagai Antioksidan dan Antimikroba Putri, Imalia Dwi; Rosalina, Rosalina; Utami, Andita; Rahmatia, Lintannisa; Enriyani, Riri; Ismail, Ismail; Alminda, Alfian Fadhilah; Irawan, Candra
Journal Warta AKAB Vol 49, No 2 (2025): Desember 2025
Publisher : Politeknik AKA Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55075/wa.v49i2.289

Abstract

Penelitian ini bertujuan untuk mengoptimalkan metode Ultrasound-Assisted Extraction (UAE) pada rimpang bangle hitam (Zingiber ottensii Valeton) sebagai upaya pemanfaatan tanaman yang belum banyak terekspos, sekaligus menggantikan metode ekstraksi konvensional yang boros pereaksi dan kurang ramah lingkungan. Metode UAE dipilih karena lebih hemat pereaksi, efisien waktu, dan ramah lingkungan. Variasi waktu ekstraksi dan amplitudo diuji untuk memperoleh kondisi optimal. Pada penelitian ini dilakukan analisis scrining fitokimia, kemudian menentukan pengaruh pelarut terhadap aktivitas antioksidan dan antimikroba menggunakan pelarut etanol. Hasil penelitian menunjukkan bahwa aktivitas antioksidan tertinggi diperoleh pada perlakuan D, yaitu waktu ekstraksi 45 menit dengan amplitudo 65%, menghasilkan nilai EC₅₀ sebesar 62,69 mg/L, yang mengindikasikan aktivitas antioksidan kuat. Uji aktivitas antimikroba menunjukkan bahwa ekstrak etanol bangle hitam termasuk kategori sensitif terhadap Bacillus sp., Escherichia coli, dan Candida albicans, dengan potensi sebanding atau mendekati kontrol positif tetrasiklin. Kesimpulannya, ekstraksi rimpang bangle hitam dengan UAE pada kondisi optimal berpotensi menghasilkan senyawa bioaktif dengan aktivitas antioksidan dan antimikroba yang tinggi, sehingga memiliki prospek sebagai bahan nutrasetikal.
The Implementation of Job Safety and Occupational Health at PT. Wijaya Karya, based on Characteristics of Worker Delicia Angow; Candra Irawan; Mariatul Kiptiah
Nusantara Civil Engineering Journal Vol 1 No 1 (2002): Nusantara Civil Engineering Journal
Publisher : Civil Engineering Dept, Balikpapan State Polytechnics

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (532.662 KB) | DOI: 10.32487/nuce.v1i1.384

Abstract

Occupational health and safety is one important aspect in a company so that the company can minimize a work accident, where in case of a work accident then it can hamper the productivity of employees. The purpose of this study is to determine the application of occupational safety and health on the productivity of employees and how the influence of which is given of the application. This research method using quantitative analysis with the data analysis technique used is the analysis of descriptive statistics. In the analysis descriptive statistics variable values obtained for the variable health & Safety is equal to 3.62 which means very high then on the productivity variable that is equal 3,47 that is very high. It can be concluded that has been conducted on the application of occupational safety and health thereby increasing employee productivity.
Co-Authors Abu Salam Agus Winarno, Agus Agustina, Feri Akbar, Ilham Januar Al-Ghiffary, Maulana Malik Ibrahim Alfany, Fauzan Maulana Alhafish, Muhammad Radhi Almidawati Alminda, Alfian Fadhilah ALQORNI, NISA Alzami, Farrikh Award Widya Laksana, Deddy Azhar, Kheiza Noor Aulia Aziz, Fuad Abdul Azzahra, Faradhina Azzami, Salman Yuris Adila Barlah Rumhayati Basri Dahlan Bima, Aristides Bimo Seto, Kahfi Akmal Janitra Cahaya Jatmoko Cahyo, Nur Ryan Dwi Caturkusuma, Resha Meiranadi Christy Atika Sari Debi, Yoga Tegar Ardi Dedy Pratama Delicia Angow Diana Aqmala Edi Sugiarto Eko Hari Rachmawanto Eko Susanto Eni Sumanti Nasution Enriyani, Riri Fahmi Amiq Farida Farida Fikri Budiman Firmansyah, Aksal Fitri, Rahma Hadi, Heru Pramono Hari Purnama, Hari Hasbi, Hanif Maulana Henny Pratiwi Adi Heru Lestiawan Hilmansyah Huda, Masrul Ifan Rizqa Ika Novita Dewi Inzaghi, Reza Bayu Ahmad Irpan Kusyadi Isinkaye, Folasade Olubusola Ismail Ismail Kango, Riklan Krismawan, Andi Danang Kusumawati, Yupie Laksana, Deddy Award Widya Lalang Erawan Lili Romli, Lili Lisandi, Anisa Marendra, Fajar Mariatul Kiptiah Menhard, Menhard Monica, Lala Munawaroh Munawaroh Muslih Muslih MY. Teguh Sulistyono Nawang Retno Ningrum, Amanda Prawita Nohan, Rejendra Novi Hendriyanto, Novi Nugraha, Dida Septiya Nuraini Nuraini Nurhindarto, Aris Oryzanti, Parwa Piliang, Arfah Pramudya, Muhammad Kemal Caesar Aqidah Purnomo, Hari Agus Putri, Ade Aisyah Arifna Putri, Imalia Dwi Rachmat Mudiyono, Rachmat Rahmatia, Lintannisa Rajali, Muhammad Ramadhan Rakhmat Sani Randy Pradityo Rasmon Ratna Purwaningsih Rosalina Rosalina Rosalina RR. Ella Evrita Hestiandari Saputra, Randika Septian, Wira Aditia Sidhiq, Restu Fajar Simatupang, Lisnawaty Sinaga, Bunga Riama Sinaga, Daurat Solichul Huda, Solichul Sri Hartini Sri Utami Kholilla Mora Siregar Suharnawi Suharnawi Suhartini Suhartini Sukiman, Maman Sulistiana, Oktavera Sulistiyono, MY Teguh suprayogi Sutarni, Yayan Dwi Syukri, Muhammad Yazidus Tomy Andrianto Tumanggor, Mutawaqil Bilah Ulfa, Anis Aulia Umah Nur, Raisul Utami, Andita Wibowo, Isro' Rizky Widharto, Yusuf Widya Rahmawati WIRDAYANI WAHAB, WIRDAYANI Yudi Prana Hikmat Yulita, Rahma Zaenal Arifin Zubir, Zubir