cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Perani Rosyani
Contact Email
journal.mediapublikasi@gmail.com
Phone
+6288210433859
Journal Mail Official
admin@journal.mediapublikasi.id
Editorial Address
Permata Tangerang, Pasar Kemis Tangerang
Location
Kota tangerang,
Banten
INDONESIA
OKTAL : Jurnal Ilmu Komputer dan Sains
Published by CV. Multi Kreasi Media
ISSN : -     EISSN : 28282442     DOI : -
Core Subject : Science, Social, Engineering,
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences
1. Komputasi Lunak, 2. Sistem Cerdas Terdistribusi, Manajemen Basis Data, dan Pengambilan Informasi, 3. Komputasi evolusioner dan komputasi DNA/seluler/molekuler, 4. Deteksi kesalahan, 5. Sistem Energi Hijau dan Terbarukan, 6. Antarmuka Manusia, 7. Interaksi Manusia-Komputer, 8. Hibrida dan Algoritma Terdistribusi Pemrosesan Informasi Manusia, 9. Komputasi Berkinerja Tinggi, 10. Penyimpanan informasi, 11. Keamanan, integritas, privasi, dan kepercayaan, 12. Pemrosesan Sinyal Gambar dan Ucapan, 13. Sistem Berbasis Pengetahuan, 14. Jaringan Pengetahuan, 15. Multimedia dan Aplikasi, 16. Sistem Kontrol Jaringan, 17. Klasifikasi Pola Pemrosesan Bahasa Alami, 18. Pengenalan dan sintesis ucapan, 19. Kecerdasan Robot, 20. Analisis Kekokohan, 21. Kecerdasan Sosial, 22. Statistic 23. Komputasi grid dan kinerja tinggi, 24. Realitas Virtual dalam Aplikasi Rekayasa, 25. Intelijen Web dan Seluler, 26. Data Besar, 27. Manajemen Informatika, 28. Sistem Informasi, 29. Desain Permainan, 30. Sistem Multimedia, 31. Pemrosesan Gambar, 32. IOT 33. Pemrograman Seluler, 34. Desain Basis Data, 35. Pemrograman Jaringan, 36. Sistem Terdistribusi, 37. Sistem Pendukung Keputusan, 38. Sistem Pakar, 39. Kriptografi, 40. Model dan Simulasi, 41. Jaringan 42. Perhitungan 43. Metematika 44. Kimia 45. Teknik Elektro 46. Robotik 47. Fisika
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,093 Documents
 95   96   97   98   99 
Literatur Review: Klasifikasi Penyakit Menular Seksual (PMS) Menggunakan Naïve Bayes dan Metode Machine Learning Terkait Raharja Adhi Putrayana; Rizki Ramadhan; Rangga Irgi Saputra; Rahmat Abdul Sahid
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 09 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Sexually transmitted diseases (STD) are a significant health problem worldwide. Correct identification and classification of this disease is essential to support early diagnosis and effective treatment. Various machine learning methods, including Naïve Bayes, have been used to automatically classify these diseases. This article reviews existing literature regarding the use of the Naïve Bayes method and other machine learning techniques in PMS classification. Based on analysis of at least five research journals, Naïve Bayes shows good performance in disease classification, although the results still depend on data quality. Several other methods such as Decision Tree, Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) are also often used as comparisons in this research. This review provides insight into the strengths and weaknesses of each method in PMS classification as well as the potential for their integration to increase the accuracy and speed of diagnosis.
Literatur Review: Klasifikasi Penyakit Jantung Koroner Menggunakan Extreme Learning Machine Marwan Kosasih; Sahrul Ramadhani; Arni Susanti Ndruru; Reihan Renaldi; Muhamad Rahmat Fadila
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 09 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Coronary Heart Disease (CHD) is a leading cardiovascular disease and one of the primary causes of death worldwide. Early and accurate classification of CHD can aid in effective prevention and appropriate treatment. This study aims to develop a CHD classification model using the Extreme Learning Machine (ELM) method. The research methodology includes gathering CHD data from the Cleveland Heart Disease Dataset, data preprocessing, dividing data into training and testing sets, and implementing the ELM algorithm for classification. Additionally, a literature review was conducted to identify related studies on heart disease classification using machine learning methods. The results indicate that the ELM model can classify CHD effectively and efficiently compared to other methods such as Support Vector Machine (SVM) and Artificial Neural Network (ANN). Therefore, ELM presents a promising alternative for early CHD diagnosis.
LITERATUR RIVIEW: KLASIFIKASI PENYAKIT TANAMAN CABAI DENGAN PENDEKATAN CNN DAN TRANSFER LEARNING Falah Nurdiansyah; Leadrin Fandyani; Muhammad Ilyas Faisal; Reza Rohman Fadhilah
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 11 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Diseases in chili plants are a serious problem that can significantly reduce crop yields and production quality, making early detection essential to assist farmers. This study uses a Convolutional Neural Network (CNN) approach with Transfer Learning methods to classify diseases on chili plant leaves. Infected chili leaf image data is processed and trained using a pre-trained CNN model to improve classification accuracy, even with limited data. The results show that this approach successfully identifies various types of diseases on chili leaves with a high level of accuracy. This approach is expected to be an effective solution for the agricultural sector to achieve faster and more efficient plant disease detection.
IMPLIKASI STRUKTUR USIA TENAGA PENDIDIK TERHADAP KUALITAS PENDIDIKAN: STUDI KASUS DI PROVINSI BANTEN, DKI JAKARTA, JAWA TENGAH, DAN SUMATERA SELATAN Humaidah; Rolen Hardi Irawan Zai; Bayu Samudra; Naufal Dhika Alriansyah; Julia Postelia Wea Buro
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 09 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study examines the effect of the age structure of the teaching force on education quality in four provinces in Indonesia. Quantitative data for 2023/2024 was analyzed to find the relationship between the age of the teaching force and education quality indicators, such as average national exam scores and graduation rates. The results show that a balance between young and senior educators contributes positively to improving education quality. Younger educators are usually quicker to adapt to technology while senior educators have more extensive teaching experience. This study recommends the need for policies that support the professional development of educators according to their age and current educational needs.
DISTRIBUSI USIA TENAGA KEPENDIDIKAN DARI EMPAT PROVINSI BEDASARKAN DATA KEMENDIKBUDRISTEK TAHUN 2023 Ridho Firdaus; Hafid Dwi Januar; Haikal Muzakkii; Satrio Dwi Cahyo
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 11 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to understand the age distribution of educators in four provinces in Indonesia, to identify potential age gaps. The methods used are quantitative and descriptive statistical analysis, using data from the Ministry of Education and Culture portal in 2023. Analysis includes measures of centralization and deployment, as well as visualization of data. The results of the study show that private education personnel are dominated by the age group of 26-30 years, with a significant difference in the number of teachers in public schools compared to private schools. This study provides recommendations related to the management of educators, especially recruitment and regeneration, as well as avoiding the age gap between regions. These findings can be an input for policymakers in managing educator resources in Indonesia.
Implikasi Divergensi Usia Pengajar terhadap Tingkat Penyelesaian pendidikan di Sulawesi Selatan, Utara, Tenggara, Selatan tahun 2023 Andi Aisyah Humairah; Irwandha Dwi Iestya; Wina Sunarti
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 09 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research and journal aims to analyze the implications of teacher age divergence on education completion rates in South, North, Central, and Southeast Sulawesi Provinces using education completion data from 2023. We employed quantitative research methods to collect and analyze data from various sources. The results show that teacher age does not have a significant influence on education completion rates in South, North, Central, and Southeast Sulawesi Provinces.
Klasifikasi Penyakit Paru-paru Menggunakan Metode Decision Tree Rilo Pambudi; Abdul Rahman Harahap; Farhan Dwitama Saputra; Muhamad Jusub
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 09 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Lung disease is a health problem that greatly affects the quality of life and various types, such as pneumonia, bronchitis, tuberculosis, asthma and COPD require special attention. Accurate classification is essential to ensure effective treatment and prevent complications. The research used the C4.5 Decision Tree Algorithm method to classify lung cancer risk using a dataset that included 16 attributes, symptoms such as and risk factors including age, shortness of breath, and smoking habits, for a total of 309 data. The train_test_split method from Scikit-learn is used to split the data into 70% for training and 30% for testing. With 89% accuracy, 70% precision, and 74.5% recall on test data assessed using the Confusion Matrix, the C4.5 model demonstrated strong performance. These findings show that 83 of the 93 predictions in the test data were correct. This research concludes that the Decision Tree Algorithm has been proven to support the diagnosis of lung cancer. however, the model performance can be improved by comparing it with other algorithms to get more optimal results.
ANALISIS RATA-RATA, MEDIAN, DAN VISUALISASI JUMLAH KEPALA SEKOLAH DAN GURU BERDASARKAN KELOMPOK UMUR DI PROV. LAMPUNG, PROV. RIAU, PROV. ACEH, PROV. PAPUA BARAT Hibatullah Dzaky Ikram Hakim; Ahmad Yusuf Syaifullah; Agung Januardi; Henry Mufid
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 11 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This journal analyzes data on the number of school principals and teachers in four provinces in Indonesia (Lampung, Riau, Aceh, and West Papua) by age group. The analysis was carried out by calculating the average and median scores of the number of principals and teachers in each age group. Data visualization was also carried out in the form of histograms, frequency polygons, and ogive to show the distribution and distribution of the number of educators by age group in each province.
Analisis Regenerasi Guru Berdasarkan Kelompok Umur di Maluku, Bali, Bangka Belitung, dan Gorontalo Bima Ardiansyah Haz; Dimas Febrian; Rizki Syafrizal
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 11 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research discusses the age distribution of school principals and teachers and the problems that arise related to age imbalance in the teaching staff. This imbalance can affect the regeneration and quality of education, especially if the majority of teachers are approaching retirement age. Each age group has its own challenges and advantages in adapting to technology and curriculum changes. This research uses secondary data from educational statistical reports and government agency databases. The aim is to analyze age distribution, identify regeneration needs, and provide policy recommendations regarding the recruitment and training of teaching staff.
Klasifikasi Penyakit Mata Pada Data OCT Menggunakan Convolutional Neural Network (CNN) Fausta Vita Austrin; Jefri Danil; Rahmat Ibnu Iman; Meidina Rahmawati Putri; Perani Rosyani
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 09 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Optical Coherence Tomography (OCT) is a non-invasive medical imaging technique used to diagnose various eye diseases, such as age-related macular degeneration, glaucoma, and diabetic retinopathy. In this study, we developed a Convolutional Neural Network (CNN) model to classify eye diseases on OCT data. Our CNN model consists of several convolution, pooling, and fully connected layers trained on an OCT dataset comprising 7 common classes of eye diseases. Further analysis reveals that the features learned by the CNN model effectively capture the visual characteristics that distinguish between different eye disease classes. We believe that the proposed CNN-based approach can be a useful tool for ophthalmologists to assist in the early and accurate diagnosis of eye diseases using OCT data.

Page 97 of 110 | Total Record : 1093

 95   96   97   98   99 

Filter by Year

2022 2025


Reset
Filter By Issues
All Issue Vol 4 No 12 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains (INPRESS) Vol 4 No 11 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 10 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 09 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 08 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 07 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 06 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 05 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 04 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 4 No 03 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 12 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 11 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 10 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 09 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 08 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 07 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 06 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 05 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 04 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 03 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 02 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 3 No 01 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 12 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 11 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 10 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 09 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 08 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 07 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 06 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 05 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 04 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 03 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 02 (2023): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 2 No 01 (2023): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 12 (2022): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 11 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 10 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 09 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 08 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 07 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 06 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 05 (2022): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 04 (2022): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 03 (2022): OKTAL : Jurnal Ilmu Komputer dan Sains Vol 1 No 02 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains Vol 1 No 01 (2022): OKTAL : Jurnal Ilmu Komputer Dan Sains More Issue