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All Journal Jurnal Ilmu Komputer Jurnal Teknologi Informasi dan Ilmu Komputer JITK (Jurnal Ilmu Pengetahuan dan Komputer) Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Riset Informatika JUSIM (Jurnal Sistem Informasi Musirawas) EVOLUSI : Jurnal Sains dan Manajemen INTI Nusa Mandiri Jurnal Pengabdian Masyarakat Asia Jurnal AbdiMas Nusa Mandiri IMTechno: Journal of Industrial Management and Technology Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Academic Journal of Computer Science Research (AJCSR) Jurnal Inovasi Pengabdian dan Pemberdayaan Masyarakat Jurnal Pengabdian Kreatif Cemerlang Indonesia Akademika
Duwi Cahya Putri Buani
Universitas Nusa Mandiri
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Public Health Social Sciences Other

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Journal : Jurnal Riset Informatika

 1 
Implementation of Machine Learning Algorithms for Early Detection of Cervical Cancer Based on Behavioral Determinants Duwi Cahya Putri Buani; Indah Suryani
Jurnal Riset Informatika Vol 5 No 1 (2022): Priode of December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v5i1.453

Abstract

Cervical cancer is a disease that affects women and has the highest mortality rate after breast cancer. Early detection of cervical cancer is critical at this time, so cervical cancer patients are decreasing. Many women, especially in Indonesia, are less concerned about the dangers of cervical cancer, even though if detected earlier, this disease will be easier to treat. One alternative for early detection can use machine learning algorithms. The machine learning algorithms used in this study are Naïve Bayes (NB), Logistic Regression (LR), Decision Tree (DT), SVM, and Random Forest. In this study, a random under-sampling method was employed, which had no uses in any prior research. This technique makes the accuracy of the five algorithms even better. The research results show that NB has an accuracy rate of 91.67%, LR has an accuracy rate of 87.5%, DT has an accuracy rate of 81.81%, SVM has an accuracy rate of 75%, and RF has the highest accuracy rate of 94.45%. This research shows that the best model is RF or Random Forest
Implementation of Machine Learning Algorithms for Early Detection of Cervical Cancer Based on Behavioral Determinants Duwi Cahya Putri Buani; Indah Suryani
Jurnal Riset Informatika Vol. 5 No. 1 (2022): December 2022
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (981.068 KB) | DOI: 10.34288/jri.v5i1.167

Abstract

Cervical cancer is a disease that affects women and has the highest mortality rate after breast cancer. Early detection of cervical cancer is critical at this time, so cervical cancer patients are decreasing. Many women, especially in Indonesia, are less concerned about the dangers of cervical cancer, even though if detected earlier, this disease will be easier to treat. One alternative for early detection can use machine learning algorithms. The machine learning algorithms used in this study are Naïve Bayes (NB), Logistic Regression (LR), Decision Tree (DT), SVM, and Random Forest. In this study, a random under-sampling method was employed, which had no uses in any prior research. This technique makes the accuracy of the five algorithms even better. The research results show that NB has an accuracy rate of 91.67%, LR has an accuracy rate of 87.5%, DT has an accuracy rate of 81.81%, SVM has an accuracy rate of 75%, and RF has the highest accuracy rate of 94.45%. This research shows that the best model is RF or Random Forest.
Application of XGB Classifier for Obesity Rate Prediction Cahya Putri Buani, Duwi; Nuraeni, Nia
Jurnal Riset Informatika Vol. 6 No. 1 (2023): December 2023
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i1.260

Abstract

According to the Ministry of Health, the percentage of the population in Indonesia who are overweight is 13.5% for adults aged 18 years and over, while 28.7% are obese with BMI>=25 and obese with BMI>=27 as much as 15.4%. Meanwhile, at the age of children 5-12 years, 18.8% were overweight and 10.8% were obese. From these data, early detection of obesity levels is needed. From these data, prevention is needed so that the percentage of the population who experience obsediness can decrease, one of the efforts that can be done is to do early detection of obesity, to do early detection of obesity can be done using Machine Learning. In this study, it was discussed about the prediction of obestias levels using 7 (seven) models, namely Naive Bayes (NB), Random Forest (RF), K-NN, Decision Tree Classifier (DTC), SVM, XGB Classifier (XGB), Logistic Regression (LR) from the seven models used to predict the obesity level of XGB Classifier (XGB) which has the highest accuracy, namely Accurasy 0.96, with an f1-score of 0.96,  Precission and recall 0.96.
Co-Authors Abdussomad, Abdussomad Achyar Ibnu Hadjar Agnes Deny Pratama Al Fitra, Razky Gilang Alexandre, Michael Andriyanto Mantovandi Angger Eka Rhamadani Anggraeni Putri, Sukmawati Angraeni Putri, Sukmawati Apriliani, Resti Dhea Putri Deni Fitriani Eka Fitriani Emiliana, Meutia Raissa Estu Mulia Warna Diyanti Fathurrahman Dwi Ramtomo Fikriyansyah , Muhamad Furi Indriyani Ilham Kurniawan Ilham Kurniawan Ilham Ramadhan Indah Suryani Indah Suryani Indah Suryani - STMIK Nusa Mandiri Jakarta Ispandi Ispandi Johansyah, Septian Dwi Nur Karim Kamali , Muhammad Kusmayanti Solecha Lukman Hakim Mitchell Nere Nasrudin Nia Nuraeni Nia Nuraeni Nining Suryani Puji Astuti Puji Astuti Rahmawati, Ami Ratih Yulia Hayuningtyas Rizal Amegia Saputra Rizal Khoirul Amri Rizka Ayu Lestari Rizky Maulana Sartika, Bella Saudur Setiaji Setiaji, Setiaji Stefanus Yogi Gunawan Suandi, Arfian Rifki Sukmawati Anggraeni Putri Sukmawati Anggraeni Putri Widya Apriliah Widya Apriliah, Widya Yohanes Christofer Lodewico Abineno Yudhistira Primatama