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All Journal Elkom: Jurnal Elektronika dan Komputer STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Journal of Information System, Applied, Management, Accounting and Research Cakrawala Pedagogik Jurnal Pendidikan dan Konseling Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Jurnal PkM (Pengabdian kepada Masyarakat) Aptekmas : Jurnal Pengabdian Kepada Masyarakat Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Jurnal Rekayasa Komputasi Terapan Jurnal Sains Student Research
Siti Julaeha
Universitas Indraprasta PGRI
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Penerapan Algoritma Genetika untuk Memprediksi Penjadwalan Jasa Pasang Pada PT. Reka Graha Semesta Aida Septiani Aida; Nilma; Siti Julaeha
JOURNAL SAINS STUDENT RESEARCH Vol. 1 No. 1 (2023): Oktober: Jurnal Sains Student Research
Publisher : CV. KAMPUS AKADEMIK PUBLISING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61722/jssr.v1i1.200

Abstract

The installation service scheduling stage is the most important stage in ensuring the company's operational efficiency, especially in the service industry which involves the repair or installation of various products or services. In addition, scheduling installation services is a complex challenge, this is because it involves the allocation of resources, time and priorities to complete various installations and avoid conflicts. To overcome the complexity of scheduling problems, genetic algorithms have become an attractive and effective approach, because they can solve multi-criteria and multi-objective problems to solve problems that are modeled by biological and evolutionary processes. The genetic algorithm represents the candidate scheduling solution into a chromosome at random and will be evaluated using the fitness function, after which selection is carried out, then crossing over or mutation is carried out. Then in each generation the chromosomes are evaluated based on the value of the fitness function, so the genetic algorithm will produce the best chromosome or is an optimal solution approach. System implementation in this study uses web-based applications to make it easier to use because there is no installation process from the user's side, and the programming language used is Hypertext Preprocessing (PHP), and MySQL as a database that makes it easier to store data that is safe and easy to access.
IMPLEMENTATION OF KNOWLEDGE MANAGEMENT IN ENHANCING TEACHERS’ COMPETENCE AT ISLAMIC JUNIOR HIGH SCHOOLS (MADRASAH TSANAWIYAH): A RECENT LITERATURE REVIEW Dedy Yusuf Aditya; Ai Solihah; Siti Julaeha; Gita Kencanawaty
Cakrawala Pedagogik Vol 9 No 3 (2025): Cakrawala Pedagogik
Publisher : Sekolah Tinggi Keguruan dan Pendidikan Syekh Manshur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51499/cp.v9i3.826

Abstract

This study aims to analyze the strengthening of knowledge management to enhance teacher engagement toward the organization at MTs Darussa’adah Pandeglang. Knowledge management is regarded as a crucial strategy for developing a sustainable learning culture within Islamic schools. The study employs a qualitative descriptive approach through literature review and field observation. The findings reveal that the key dimensions of knowledge management—creation, storage, sharing, and application of knowledge—significantly contribute to improving teachers’ involvement in organizational activities and instructional innovation. Moreover, leadership support and collaboration among teachers within professional learning communities strengthen motivation and a sense of belonging to the institution. The study recommends implementing a digital collaboration platform to facilitate knowledge sharing and foster a learning organization culture in the madrasa context.
Application of Deep Learning for Email Spam Detection Using Artificial Neural Network Dewi Leyla Rahmah; Irnawati; Dewi Mustari; Bertha Meyke Waty Hutajulu; Halimatus Sa'diah; Siti Julaeha
Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Vol. 5 No. 1 (2026): Juni 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juktisi.v5i1.1086

Abstract

The rapid development of digital communication technology has significantly increased the use of email, followed by the growing threat of spam emails that may disrupt user security and convenience. Spam emails are commonly used for advertisements, phishing attacks, and malware distribution, potentially causing financial losses and data theft. This study aims to implement a Deep Learning method based on Artificial Neural Network (ANN) to automatically detect spam emails and analyze the model performance using classification evaluation parameters. The research employed a quantitative experimental approach using a dataset of 10,000 emails consisting of spam and non-spam categories. The research stages included data preprocessing, text transformation using TF-IDF, ANN model training, system testing, and performance evaluation using accuracy, precision, recall, and F1-score metrics. The results showed that the ANN model achieved an accuracy of 96.4%, precision of 95.9%, recall of 96.7%, and F1-score of 96.3%. In addition, the pre-test and post-test results indicated a performance improvement of more than 11% after implementing the Deep Learning method. Based on these findings, the ANN method proved effective in improving the performance of spam email detection systems and can be utilized as a solution to support digital communication security more effectively.
Co-Authors Ai Solihah Aida Septiani Aida Aulia Ar Rakhman Awaludin Avini Nurazhimah Arfa Bertha Meyke Waty Hutajulu Caka Gatot Priambodo Dedy Yusuf Aditya Dewi Leyla Rahmah Dewi Mustari Dona Katarina Halimatus Sa'diah Heri Satria Iim Marfu'ah Irnawati Kencanawaty, Gita KUSTIAN, NUNU Makiyah Inaya Nilma Novi Aprian Nunu Kustian Nunu Kustian Reko Syarief Hidayatullah Rizki Ridwan somawati somawati Syamsiah