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All Journal Elkom: Jurnal Elektronika dan Komputer KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sistemasi: Jurnal Sistem Informasi JITK (Jurnal Ilmu Pengetahuan dan Komputer) JTIK (Jurnal Teknik Informatika Kaputama) Jurnal Infortech KLIK: Kajian Ilmiah Informatika dan Komputer Indonesian Journal of Networking and Security - IJNS I'thisom: Jurnal Ekonomi Syariah

Muhammad Rifqi Firdaus

Universitas Bina Sarana Informatika

Author-ID : 3318531

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Library & Information Science

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CLASSIFICATION OF THE PROSPECTS FOR CITY TREES LIFE EXPECTANCY USING NAIVE BAYES METHOD Muhammad Rifqi Firdaus; Abdul Latif; Ipin Sugiyarto; Windu Gata
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 1 (2020): JITK Issue August 2020
Publisher : LPPM Nusa Mandiri

Besides the city is a large and extensive residential area. as a center for the activities of its citizens, both from economic, cultural, and development activities. Development in the city leads to the physical development of the city with the many facilities and infrastructure in the city, making activities in the city cause some pollution problems. To overcome this problem, the government often creates green open space in the middle of the city. Planting shade trees will help to balance the problem of pollution due to development. Trees can reduce temperatures, in addition to absorbing air and climate pollution. trees can help save energy. Naive Bayes is a classification with probability and statistical methods, namely predicting future opportunities based on experience based on the assumption of simplification that attribute values are conditionally free if given an output value. Data processing with Naive Bayes produces a Precision value of 0.840%, a recall value of 0.848%, and an AUC of 0.873%. These results indicate that the results are included in the excellent category.

COMPARATIVE ANALYSIS OF SOFTWARE EFFORT ESTIMATION USING DATA MINING TECHNIQUE AND FEATURE SELECTION Abdul Latif; Lady Agustin Fitriana; Muhammad Rifqi Firdaus
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol 6 No 2 (2021): JITK Issue February 2021
Publisher : LPPM Nusa Mandiri

Software development involves several interrelated factors that influence development efforts and productivity. Improving the estimation techniques available to project managers will facilitate more effective time and budget control in software development. Software Effort Estimation or software cost/effort estimation can help a software development company to overcome difficulties experienced in estimating software development efforts. This study aims to compare the Machine Learning method of Linear Regression (LR), Multilayer Perceptron (MLP), Radial Basis Function (RBF), and Decision Tree Random Forest (DTRF) to calculate estimated cost/effort software. Then these five approaches will be tested on a dataset of software development projects as many as 10 dataset projects. So that it can produce new knowledge about what machine learning and non-machine learning methods are the most accurate for estimating software business. As well as knowing between the selection between using Particle Swarm Optimization (PSO) for attributes selection and without PSO, which one can increase the accuracy for software business estimation. The data mining algorithm used to calculate the most optimal software effort estimate is the Linear Regression algorithm with an average RMSE value of 1603,024 for the 10 datasets tested. Then using the PSO feature selection can increase the accuracy or reduce the RMSE average value to 1552,999. The result indicates that, compared with the original regression linear model, the accuracy or error rate of software effort estimation has increased by 3.12% by applying PSO feature selection

Co-Authors Abdul Latif Abdul Latif Abdul Latif Adinda Thalia Salsa Bela Ainun Defrilia Amalia Nuril Hidayati Amin Nur Rais Arief Rama Sena Dinar Ismunandar Dini Silvi Purnia, Dini Silvi Elah Nurlelah Erika Mutiara Erni Ermawati Fuad Nur Hasan Gata, Windu Ipin Sugiyarto Irwan Herliawan Irwan Herliawan - Universitas Nusa Mandiri Kartika Handayani Lady Agustin Fitriana Lifia Revanata Lisnawanty Muhamad Abdul Ghani Muhamad Fahmi Julianto Muhammad Ifan Rifani Ihsan Nila Hardi Popon Handayani Rizka Dahlia Windu Gata Yuris Alkahfi Yuris Alkhalifi

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Journal : JITK (Jurnal Ilmu Pengetahuan dan Komputer)