Article Per Year (5 Year)
p-Index From 2021 - 2026
1.037
P-Index
This Author published in this journals
All Journal Technomedia Journal JISA (Jurnal Informatika dan Sains) G-Tech : Jurnal Teknologi Terapan Jurnal Cahaya Mandalika ABDINE Jurnal Pengabdian Masyarakat
Oleh Soleh, Oleh
Unknown Affiliation
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Other

Published : 6 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 6 Documents
Search

 1 
Perancangan Aplikasi Steganografi Dengan Teknik LSB dan AlgoritmaRC4 & Base64 Encoding Soleh, Oleh; Alfiah, Fifit; Yusuf, Budi
Technomedia Journal Vol 3 No 1 Agustus (2018): Technomedia Journal
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (686.377 KB) | DOI: 10.33050/tmj.v3i1.493

Abstract

The concealment of secret messages by inserting messages into an image file or more commonly known as steganography is the development of cryptography. This hidden secret message with steganography does not attract attention because the message is simply inserted into a file. Many methods are used to hide messages with steganography. Some methods of steganographic algorithms use a combination to perform the task of concealment of secret messages. From the existing method, of course has its own shortcomings and advantages. The method used is LSB (Least Significant Bit) method, RC4 algorithm and Encoding Base64. This method combines cryptographic techniques with steganography techniques. The message is encrypted before it is inserted into a file. Implementation of this method can later help users to send messages safely without being noticed by others.
Analisa Sistem Informasi Manajemen Sumber Daya Manusia Pada Proses Rekrutmen, Demosi dan Mutasi di PT. Yasunli Abadi Utama Plastik Soleh, Oleh; Hidayat, Wahyu; Rustanti S, Fitri Widya
Technomedia Journal Vol 3 No 2 Februari (2019): Technomedia Journal
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (610.53 KB) | DOI: 10.33050/tmj.v3i2.634

Abstract

It takes A good system is needed to monitor all activities, productivity, discipline and career path of employees in a developing company, because the current conditions are all done manually. This can cause errors in making decisions for these employees. To facilitate the company in making decisions and actions against these employees, we need a system that can make a summary of the results of employee performance in terms of activity, productivity, discipline and career path. This needs to be analyzed in the Human Resources (HR) system or more commonly known as Human Resource and for the analytical method used today uses three methods, observation, literature and analysis. The object used in this problem is PT. Yasunli Abadi Utama Plastik. The target of achievement in this case is to take action and make decisions against high achieving or quick-achieving employees. Keywords: System, Human Resources, Human Resource, Yasunli Abadi Utama Plastik.
Peran Teknologi Cloud Computing dalam Transformasi Infrastruktur TI Perusahaan: Studi Analisis Implementasi di Industri Manufaktur Allo, Bartolomeus Rante; Naim, Yanto; Soleh, Oleh; Lazinu, Virjayanti; Nurkim, Nurkim
Jurnal Cahaya Mandalika ISSN 2721-4796 (online) Vol. 3 No. 3 (2022)
Publisher : Institut Penelitian Dan Pengambangan Mandalika Indonesia (IP2MI)

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

Abstract

Teknologi cloud computing telah menjadi pusat perhatian dalam transformasi infrastruktur TI perusahaan, khususnya di industri manufaktur. Artikel ini bertujuan untuk menganalisis peran teknologi cloud computing dalam transformasi infrastruktur TI perusahaan melalui pendekatan kualitatif menggunakan metode studi literatur dan library research. Melalui tinjauan terhadap berbagai sumber literatur, artikel ini mengidentifikasi implikasi penggunaan teknologi cloud computing dalam meningkatkan efisiensi, fleksibilitas, dan skalabilitas infrastruktur TI perusahaan manufaktur. Temuan dari penelitian ini memberikan wawasan yang mendalam tentang bagaimana implementasi teknologi cloud computing dapat mendukung transformasi infrastruktur TI perusahaan dan meningkatkan daya saing di pasar global.
Pelatihan Deteksi Diabetic Foot Ulcer (DFU) Berbasis Citra Digital Menggunakan Deep Learning untuk Tenaga Kesehatan di Puskesmas Ayu Wijaya Kusumaningrum, Sekar; Soleh, Oleh; Apriani, Desy
ABDINE: Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2025): ABDINE : Jurnal Pengabdian Masyarakat
Publisher : Sekolah Tinggi Teknologi Dumai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/abdine.v5i2.1760

Abstract

Diabetic Foot Ulcer (DFU) merupakan komplikasi serius Diabetes Melitus yang seringkali terlambat dideteksi di Fasilitas Kesehatan Tingkat Pertama (FKTP), seperti Puskesmas, akibat keterbatasan objektivitas dan akurasi tenaga kesehatan (nakes). Keterlambatan ini berujung pada peningkatan risiko amputasi dan beban biaya kesehatan. Kegiatan pengabdian ini bertujuan untuk mentransformasi kompetensi nakes di Puskesmas Jatiuwung, Kota Tangerang, dalam deteksi DFU melalui implementasi dan pelatihan sistem berbasis Deep Learning (Jaringan Saraf Tiruan Konvolusional/CNN) untuk analisis citra digital luka. Metode pengabdian yang digunakan meliputi survei awal (pre-test), pengembangan prototipe aplikasi deteksi, sesi pelatihan teoretis dan praktik intensif, serta evaluasi keberhasilan menggunakan post-test dan kuesioner kepercayaan diri (skala Likert). Hasil kegiatan menunjukkan peningkatan pengetahuan teoretis nakes secara signifikan, dengan rata-rata skor meningkat dari 48,3% menjadi 85,1% (p < 0.001). Selain itu, hasil kuesioner menunjukkan bahwa 96% peserta merasa Yakin atau Sangat Yakin untuk mengoperasikan sistem prototipe dalam alur kerja harian. Pelatihan ini berhasil mentransfer inovasi teknologi, secara efektif meningkatkan pengetahuan dan keterampilan praktis nakes, sekaligus menyediakan solusi deteksi dini yang objektif dan siap diintegrasikan ke dalam alur pemeriksaan Puskesmas untuk pencegahan amputasi dini.
Comparative Analysis of Machine Learning Methods in Predicting Diabetes Risk Based on Genetic Data Kusumaningrum, Sekar Ayu Wijaya; Soleh, Oleh; Yusup, Muhamad
JISA(Jurnal Informatika dan Sains) Vol 8, No 2 (2025): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v8i2.2486

Abstract

Type 2 Diabetes Mellitus (T2DM) is a global chronic disease caused by the interaction of genetic and environmental factors. The use of genetic data offers great potential for early detection and personalized intervention. However, the complex analysis of genetic data requires sophisticated approaches like machine learning. This study aims to compare the performance of three machine learning algorithms Logistic Regression, Random Forest, and K-Nearest Neighbors (KNN) in predicting T2DM risk based on genetic data. By using a Systematic Literature Review of studies published between 2019 and 2024, the accuracy data from each algorithm was compared. The analysis results show that Random Forest has the best performance with an accuracy of 99.3%. This algorithm excels due to its ability to handle high-dimensional datasets and reduce overfitting. In comparison, KNN achieved an accuracy of 87% and Logistic Regression 82%. These findings support the integration of machine learning into early detection systems and more precise and efficient clinical decision-making for T2DM management.
Design of an Expert System for Early Detection of Domestic Violence Using Keyword Matching, Sentiment Analysis and Forward Chaining Kusumaningrum, Sekar Ayu Wijaya; Soleh, Oleh; Azizah, Nur
G-Tech: Jurnal Teknologi Terapan Vol 10 No 1 (2026): G-Tech, Vol. 10 No. 1 January 2026
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/g-tech.v10i1.8977

Abstract

Domestic Violence (KDRT) is a critical humanitarian issue where victims often under-report due to fear, dependence, and stigma. Consequently, many victims turn to social media to express distress implicitly using vague language, rendering existing passive reporting systems and manual detection ineffective against unstructured narratives. This research aims to design a Hybrid Expert System architecture that integrates Keyword Matching and Sentiment Analysis with Forward Chaining to objectively detect indications of KDRT in Indonesian text, specifically targeting implicit venting that lacks explicit violence keywords. The study employs a systematic development method involving knowledge acquisition from psychological (cycle of abuse) and legal  domains to construct a robust knowledge base. The technical architecture combines sentiment analysis to gauge emotional intensity with Forward Chaining inference logic. This logic utilizes dynamic frequency parameters to validate findings through case tracing simulations. The results demonstrate that the proposed architecture successfully classifies various violence types, including physical, verbal, economic, and multi-type violence. The simulation confirms the system’s capability to distinguish between common household conflicts and specific abuse patterns by applying zero-tolerance thresholds for acute violence and repetition filters for chronic psychological abuse. Consequently, this system functions as a robust decision support tool, providing measurable risk assessments and appropriate intervention recommendations for early detection.
Co-Authors Alfiah, Fifit Aliftiar, Praditya Ayu Wijaya Kusumaningrum, Sekar Bartolomeus Rante Allo Desy Apriani Kusumaningrum, Sekar Ayu Wijaya Lazinu, Virjayanti Muhamad Yusup Naim, Yanto Nur Azizah Nurkim, Nurkim Rustanti S, Fitri Widya Sabalidowati, Trie Mayhera Wahyu Hidayat Yusuf, Budi