Article Per Year (5 Year)
p-Index From 2021 - 2026
4.309
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu Komputer dan Informasi JURNAL SISTEM INFORMASI BISNIS Jupiter Jurnal Teknik ITS IPTEK Journal of Proceedings Series Semantik Techno.Com: Jurnal Teknologi Informasi Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Sistem dan Informatika Journal of Information Systems Engineering and Business Intelligence Jurnal IPTEK Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Inspiration Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Informatika Jurnal Ilmiah FIFO Network Engineering Research Operation [NERO] Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Matrix : Jurnal Manajemen Teknologi dan Informatika Jurnal ULTIMA InfoSys Systemic: Information System and Informatics Journal Indonesian Journal of Electrical Engineering and Computer Science Journal of Applied Computer Science and Technology (JACOST) JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Melek IT: Information Technology Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi Sewagati
Siti Rochimah
Departemen Informatika Institut Teknologi Sepuluh Nopember
Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Public Health Social Sciences Other

Published : 84 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : Journal of Applied Computer Science and Technology (JACOST)

 1 
Pendekatan Metode Ensemble Learning untuk Prakiraan Cuaca menggunakan Soft Voting Classifier Steven Joses; Yulvida, Donata; Rochimah, Siti
Journal of Applied Computer Science and Technology Vol 5 No 1 (2024): Juni 2024
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v5i1.741

Abstract

Weather conditions are one of the crucial factors that need attention. Changes in weather conditions significantly impact various activities. Weather condition changes are determined by numerous factors, often occurring within a relatively short period in the atmosphere, such as pressure, wind speed, rainfall, temperature, and other atmospheric phenomena. Issues in weather forecasting arise due to several factors, namely the fluctuating atmospheric conditions. This research proposes the development of a weather forecasting model using the ensemble learning method approach. The weather data used consist of 33746 records with attributes used after preprocessing, namely Temperature, Dew Point, Humidity, Wind Speed, Wind Gust, Pressure, Precipitation, and Condition. Testing in this research employs several single-machine learning methods such as K-Nearest Neighbor (KNN), Logistic Regression, Random Forest, Naive Bayes, and Multi-Layer Perceptron. The Naive Bayes method using default parameters achieves a high accuracy of 99.00%. In the ensemble method, combinations of three methods exhibit excellent accuracy for all combinations. The best combination methods are found in the Soft Voting Classifier method (Random Forest, MLP, Naive Bayes), Soft Voting Classifier (Logistic Regression, MLP, Naive Bayes), and Soft Voting Classifier (Random Forest, KNN, Naive Bayes) with an accuracy of 99.03%.
Perbandingan Metode Random Forest, Convolutional Neural Network, dan Support Vector Machine Untuk Klasifikasi Jenis Mangga Mardianto, Ricky; Stefanie Quinevera; Rochimah, Siti
Journal of Applied Computer Science and Technology Vol 5 No 1 (2024): Juni 2024
Publisher : Indonesian Society of Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52158/jacost.v5i1.742

Abstract

Mango is a fruit known as the "King of Fruit" due to its rich flavor, vast variability, and high nutritional value. Classifying mangoes based on their external appearance is the initial step in the process of identifying and categorizing mango types conventionally. The classification process can be performed by examining external features such as fruit color, shape, and size. Classifying different types of mango fruits accurately can assist researchers in developing superior varieties and also aid farmers for cultivation purposes, sales, distribution, and selecting the right varieties for local growth and weather conditions. This research conducts the classification of mango types based on color from mango images using machine learning. The study compares three methods, namely Random Forest, Support Vector Machine (SVM), and Convolutional Neural Network (CNN), to determine the best method for classifying mango types based on their images. The dataset underwent preprocessing, where image sizes were standardized to 300 x 300 pixels, and color was changed to grayscale. The dataset was then divided into training and testing data with a ratio of 70:30. Subsequently, the dataset was processed using three methods, and their accuracy results were compared. The findings indicate that the Random Forest method yielded the highest accuracy compared to the other methods, with an accuracy rate of 96%. The accuracy of the SVM method was 95%, and the accuracy of the CNN method was 33%. From these results, it can be concluded that the Random Forest method is highly effective for classifying mango types based on their image compared to SVM and CNN methods.
Co-Authors ABDUL MUNIF Achmad Arwan Achmad Arwan Ahmadiyah, Adhatus Solichah Akbar, Fawwaz Ali Akbar, Rizky Januar Aldy Sefan Rezanaldy Alexander L. Romy Alirridlo, Maulana Alqis Rausanfita Amirullah, Afif Ana Tsalitsatun Ni'mah Andhik Ampuh Yunanto Andy Rachman Anggraini, Ratih Nur Esti Arifiani, Siska Arini R. Rosyadi Arrijal Nagara Yanottama Bagus Priambodo Balqis Hidayat, Sultana Bambang Jokonowo Bayu Priyambadha Bayu Priyambadha Bintang Nuralamsyah Butar Butar, Thio Marta Elisa Yuridis Chastine Fatichah Choiru Zain Daniel Oranova Daniel Oranova Siahaan Darlis Heru Murti Darlis Herumurti Denni Aldi Ramadhani Denni Aldi Ramadhani Denni Aldi Ramadhani Diana Purwitasari Dianni Yusuf Dimas Widya Liestio Pamungkas Dini Adni Navastara, Dini Adni Diniar Nabilah Ghassani Djoko Pramono Dwi Sunaryono Dyah Sulistyowati Rahayu Eko M. Yuniarno Eko Wahyu Wibowo Endang Wahyu Pamungkas Evi Triandini F.X. Arunanto Faizal Johan Fernandes Sinaga Galang Amanda Dwi P. Hadiningrum, Tiara Rahmania Haniefardy, Addien Haq, Arinal Hengki Suhartoyo Hidayatul Munawaroh I Gede Suardika Imam Kuswardayan Jan Claes Karolita, Devi Khairy, Muhammad Shulhan Kholed Langsari Kurniasari, Dias Tri Kurniawan, Adi Kusbandono Ari Bowo Laili Yuhana, Umi Lesmideyarti, Dwi Lukman Hakim Lutfi Rizal Gozali Mardiana, Bella Dwi Mardianto, Ricky Mauridhi Hery Purnomo Mohammad Ahmaluddin Zinni, Mohammad Ahmaluddin Montolalu, Billy Muhammad Iskandar Java Muhammad Sonhaji Akbar Muhammad Yusuf Muhsin Bayu Aji Fadhillah Mutia Rahmi Dewi Nisa, Maidina Choirun Nugroho, Supeno Mardi S. Nur Fajri Azhar Nuralamsyah, Bintang Oranova, Daniel Pamungkas, Dimas Widya Liestio Pertiwi, Kharisma Monika Dian Pradanita, Windy Rahmadia Prasetyo Putri, Divi Galih R. Firman Insan M. Rachman, Andy Rahmi Ika Noviana Ratih Nindyasari Relaci Aprilia Istiqomah Reza Fauzan Ridho Rahman Hariadi Ridwan, Mochammad Arief Riyanarto Sarno Rizky Januar Akbar Santoso, Bagus Jati Saptarini, Istiningdyah Sarwosri Sarwosri Sarwosri Sarwosri, - Septiyawan Rosetya Wardhana Setiawan, Wahyu Fajar Siska Arifiani Stefanie Quinevera Steven Joses Suhadi Lili Suhadi Lili Supeno Mardi S. Nugroho Tahara, Enrico Almer Tampubolon, Andrew Lomaksan Manuel Ulima Inas Shabrina Vico Ade Candra Widyanti Kartika Windy Rahmadia Pradanita Yanuar Risah Prayogi Yuhana, Umi Laili Yulvida, Donata Yuniarno, Eko M. Yusuf, Dianni Zulhaydar Fairozal Akbar