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All Journal Media Mesin: Majalah Teknik Mesin INFORMAL: Informatics Journal Jurnal Teknik Sipil Bina Insani ICT Journal Information System for Educators and Professionals : Journal of Information System JTAM (Jurnal Teori dan Aplikasi Matematika) JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) JSAI (Journal Scientific and Applied Informatics) Jurnal Teknologi Informasi dan Terapan (J-TIT) Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi INTEGRITAS : Jurnal Pengabdian JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) G-Tech : Jurnal Teknologi Terapan Jurnal Computer Science and Information Technology (CoSciTech) Journal of Community Development Journal of Information System and Technology (JOINT) JIWAKERTA: Jurnal Ilmiah Wawasan Kuliah Kerja Nyata BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Abdimas Awang Long: Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesian Community Journal Dedikasi: Jurnal Pengabdian Kepada Masyarakat Jutech: Jurnal Teknologi Informasi INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Jurnal Informatika dan Teknologi Pendidikan Smart Techno (Smart Technology, Informatic and Technopreneurship) JUSTIFY : Jurnal Sistem Informasi Ibrahimy J-ENSITEC (Journal of Engineering and Sustainable Technology) Jurnal Aplikasi Sistem Informasi dan Elektronika Jurnal Penelitian Teknologi Informasi dan Sains Journal of Digital Literacy and Volunteering (JRSIKOM) Jurnal Riset Sistem Informasi dan Aplikasi Komputer JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Oktavianto, Hardian
Universitas Muhammadiyah Jember
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Journal : INFORMAL: Informatics Journal

 1 
Pencarian Pola Asosiasi Keluhan Pasien Menggunakan Teknik Association Rule Mining Ulya Anisatur Rosyidah; Hardian Oktavianto
INFORMAL: Informatics Journal Vol 3 No 1 (2018): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v3i1.5541

Abstract

Perkembangan dan pertumbuhan data di bidang kesehatan semakin meningkat dan bertambah, baik dari kualitas maupun kuantitas, dilihat dari sisi kualitas, perkembangan data ini mengalami perubahan dari bentuk dokumen tulis menjadi dokumen digital atau yang biasanya kita sebut dengan file. Isu yang muncul adalah apakah informasi yang bisa diambil atau didapatkan dari sekian banyak data medis yang tersedia hanya berupa informasi – informasi pada umumnya, sedangkan dari suatu basis data yang tersedia seringkali memuat beberapa variabel sekaligus, bahkan apabila diteliti lebih jauh lagi, basis data yang berbeda bisa jadi memuat beberapa variabel yang sama, dari isu tersebut maka diperlukan suatu metode untuk bisa menggali lebih dalam informasi – informasi yang belum diketahui. Berkaitan dengan data medis serta data mining, maka penelitian kali ini akan membahas tentang implementasi atau kegunaan dari data mining pada data kunjungan pasien dengan cara menerapkan association rule mining untuk mendapatkan pola – pola asosiasi dari basis data kunjungan pasien yang tersedia menggunakan algoritma apriori dan algoritma FP-Growth. Baik algoritma apriori dan algoritma FP-Growth menghasilkan output yang sama. Perbedaan hasil uji coba terletak pada jumlah rule asosiasi yang ditemukan, dengan menggunakan algoritma apriori ditemukan 3 buah rule asosiasi, sedangkan ketika digunakan algoritma FP-Growth ditemukan 2 buah rule asosiasi, hal ini terjadi pada saat uji coba yang dilakukan menggunakan confidence sebesar 80%.
Analisis Klasifikasi Kanker Payudara Menggunakan Algoritma Naive Bayes Hardian Oktavianto; Rahman Puji Handri
INFORMAL: Informatics Journal Vol 4 No 3 (2019): INFORMAL - Informatics Journal
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v4i3.14170

Abstract

Breast cancer is one of the highest causes of death among women, this disease ranks second cause of death after lung cancer. According to the world health organization, 1 million women get a diagnosis of breast cancer every year and half of them die, in general this is due to early treatment and slow treatment resulting in new cancers being detected after entering the final stage. In the field of health and medicine, machine learning-based classification has been carried out to help doctors and health professionals in classifying the types of cancer, to determine which treatment measures should be performed. In this study breast cancer classification will be carried out using the Naive Bayes algorithm to group the types of cancer. The dataset used is from the Wisconsin breast cancer database. The results of this study are the ability of the Naive Bayes algorithm for the classification of breast cancer produces a good value, where the average percentage of correctly classified data reaches 96.9% and the average percentage of data is classified as incorrect only 3.1%. While the level of effectiveness of classification with naive bayes is high, where the average value of precision and recall is around 0.96. The highest precision and recall values are when the test data uses a percentage split of 40% with the respective values reaching 0.974 and 0.973.
Optimasi Algoritma XGBoost Classifier Menggunakan Hyperparameter Gridesearch dan Random Search Pada Klasifikasi Penyakit Diabetes Ginanjar Abdurrahman; Hardian Oktavianto; Mukti Sintawati
INFORMAL: Informatics Journal Vol 7 No 3 (2022): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v7i3.35441

Abstract

Classification using XGBoost in this study was applied to diabetes data originating from the UCI Machine Learning website. The initial step in this research is to deal with missing values. Missing value is found in several features. These missing values need to be handled otherwise the XGBoost algorithm will not work. Missing value handling is done by adding a meaningful value as a substitute for the missing value. At the time of modeling, the dataset is divided into training data and test data. The training data used is 80% of the number of patients, while the test data is 20%. In this study, the dataset that had imputed missing values was subjected to three treatments, first without hyperparameters, secondly hyperparameter tuning using gridsearch, and third hyperparameter tuning using random search. In the first treatment, classification using XGBoost without hyperparameters obtained a negative log loss value of 25%, which means that the performance accuracy of the algorithm reaches 75%. As for the second treatment and the third treatment, namely by using gridsearch and random search, it produces the same negative log loss value, which is 5%, which means that the performance of the algorithm reaches 95%. Thus, the performance of gridsearch and random search can significantly increase the accuracy value
Co-Authors A'yun, Qurrota Abdul Azis Aditya Surya Manggala Agil Wahyu Royan Agung Nilogiri Ahmad Yusril Ghali Taufiqul Haq aji brahma nugroho, aji brahma Al Faruq, Habibatul Azizah Alfain, Asfik Amilia, Indi Rosifatul Anggar Wahyu Hadiyatullah Ardhi Fathonisyam Putra Nusantara Ardhi, Nusantara Fathonisyam Putra Ari Eko Wardoyo Ari Eko Wardoyo Budi Satria Bakti Chaidir, Reza Daryanto Daryanto Dasuki, Moh Dewi Lusiana Dewi Lusiana Pater Dewi, Sofia Rhosma Dimas D K Dimas Nur Hazikin Dimas Pradana Ega Yusni Habibie Firdaussani, Ahmad fitriyah, nur qodariah Fitriyah, Nur Qodariyah Ginanjar Abdurrahman Hadijatmiko, Hadijatmiko Hasbullah Hasbullah Hasbullah Hasbullah Hidayat, Muhammad Hafid Iftitah Sita Devi Andani Irawan, Dudi Izzati Muhimmah Kiki Diah Ayu Puspita Luqman Hakim Lusiana, Dewi Marganingsih, Dirgahayu Maulana, Oka Wahyu Moh Khoirul Anam Moh. Dasuki Mokh Hairul Bahri Mubarok, Fikril Muh Nur I.F Muhammad Rivansyah Muhammad Zainur Ridlo Muharom, Lutfi Ali Mukti Sintawati Nanang Saiful Rizal Nely Ana Mufarida Nugroho, Dimas Widia Adi Permata, Arindha Dyah Probowulan, Diyah Qurotta A’yun Qurrota A’yun Rahayu, Yeni Dwi Rahman Puji Handri Rahman, Miftahur Rahman, MIftahur Rasuki, Muhlisin Rega Sukmawati Ria Angin, Ria Rizky, Mohammad Royan, Agil Wahyu Saifudin, Ilham Saputra, Septiyan Tri Septian Dwi Chandra Sofia Ariyani Suharso, Wiwik Sulistyo, Henny Wahyu TAUFIQ HIDAYAT Taufiq Timur Warisaji Triawan Adi Cahyanto Ulya Anisatur Rosyidah Umar Dani Umilasari, Reni Warisaji, Taufiq Timur Wijaya, Guruh Zainul Arifin Zainul Arifin ZAINUL ARIFIN Zakiyyah, Amalina Maryam