Article Per Year (5 Year)
p-Index From 2021 - 2026
2.765
P-Index
This Author published in this journals
All Journal CESS (Journal of Computer Engineering, System and Science) Sinkron : Jurnal dan Penelitian Teknik Informatika Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Jurnal Teknik Komputer AMIK BSI Paradigma Jurnal Pilar Nusa Mandiri Indonesian Journal of Artificial Intelligence and Data Mining JITK (Jurnal Ilmu Pengetahuan dan Komputer) JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Mantik Jurnal Informatika dan Rekayasa Elektronik Jurnal Infortech Jurnal Teknik Informatika (JUTIF) Jurnal Sistem Informasi Jurnal AbdiMas Nusa Mandiri Indonesian Journal of Networking and Security - IJNS Teknologika Journal of Applied Agricultural Science and Technology Paradigma Jurnal Ticom: Technology of Information and Communication
Verry Riyanto
Universitas Bina Sarana Informatika
Agriculture, Biological Sciences & Forestry 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 Library & Information Science Mathematics Mechanical Engineering Physics Social Sciences Other

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Paradigma

 1 
Grouping Data in Predicting Infant Mortality Using K-Means and Decision Tree Ridwansyah Ridwansyah; Verry Riyanto; Abdul Hamid; Sri Rahayu; Jajang Jaya Purnama
Paradigma Vol. 24 No. 2 (2022): September 2022 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (391.355 KB) | DOI: 10.31294/paradigma.v24i2.1399

Abstract

Death is something that we cannot avoid where, when and how death comes. The high infant mortality rate is the main thing and the Indonesian government must prioritize, one of the government's efforts to reduce infant mortality is by conducting a surveillance program, namely PWS KIA where the program is uniting the health of mothers and babies in the local area, basically there are several infant deaths that have causes from the time of pregnancy, accidents, disasters, diseases or because it is destiny from God, for that research is carried out in classifying infant mortality data. For grouping infant mortality data, a K-Means method is needed to analyze data by carrying out a data modeling process without supervision or also known as unsupervised learning. In showing the centroid in the early stages of the k-means algorithm, it is very influential on the results of the cluster carried out on the infant mortality dataset. taken from data.go.id with different centroid results. The results of the clustering model pattern that can be trusted by the government or the Health department to prevent infant mortality. From the clustering results, four labels are tested again using the decision tree algorithm.
Optimization of the YOLOv7 Object Detection Algorithm for Estimating the Amount of Apple Harvest Verry Riyanto; Imam Nawawi; Ridwansyah Ridwansyah; Ganda Wijaya; Toto Haryanto
Paradigma Vol. 25 No. 1 (2023): March 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i1.1809

Abstract

The increasing population consumed in high production and food needs for survival. Apples are one of the crop harvest products in Indonesia whose needs are increasing, because they are not only needed for human vitamins but can be used as hand fruit or a form of gratitude to those who receive the fruit. In the process of harvesting apples in agricultural land, harvesting is often found which is not feasible in the hands of consumers because it takes too long for apples to not be harvested when the condition of the fruit is feasible in maturity. Therefore, the authors approach this problem by processing the image results obtained to form a detection model, whether the apples are said to be feasible to be harvested immediately and from the image results it can also be calculated the number of fruits captured by the image model , feature enhancements Estimates on objects from this image model are expected to provide more timely harvest predictions in order to provide longer aging of apples and good fruit quality after reaching consumers
Co-Authors Abdul Hamid Abdul Hamid Achmad Maezar Bayu Aji Biktra Rudianto - STMIK Nusa Mandiri Jakarta Dahlia Dahlia Eni Pudjiarti Eri Riana Ganda Wijaya Ganda Wijaya Ganda Wijaya Ganda Wijaya, Ganda Hafis Nurdin Henny Destiana Herlambang Brawijaya Hikmah, Noer Imam Nawawi Jajang Jaya Purnama Marimin Marimin Mohammad Roffi Suhendry Muhamad Syukur Nafila, Dzhikrokhatun Niar Adisty Putra Nuraeni Herlinawati Rahmatul Husna Ridwansyah Ridwansyah Rudianto, Biktra Sartini Sartini Shelvie Nidya Neyman Shena Arrahima Qolby Siti Faizah Sri Nurdiati Sri Rahayu Sugiono, Sugiono Sumarna Sumarna . Sumarna Sumarna Sumarna Sumarna Suryadithia, Rachmat Susy Rosyida Toto Haryanto Tri Hartati, Tri WITRIANA ENDAH PANGESTI Yana Iqbal Maulana