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Implementasi Steganografi Menggunakan Metode End of File (EOF) untuk Menyisipkan File Detail Drawing Engineering dalam Gambar Effendi, Muhammad Makmun; Sen , Tjong Wan; Zy, Ahmad Turmudi; Isarianto, Isarianto
Techno.Com Vol. 24 No. 3 (2025): Agustus 2025
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/tc.v24i3.13227

Abstract

Penelitian ini bertujuan mengembangkan sistem steganografi berbasis web dengan menerapkan pendekatan End of File (EOF) guna menyisipkan file PDF berisi detail gambar teknik ke dalam file citra digital (.jpg dan .png) pada skenario industri manufaktur. Perlindungan informasi teknis yang bersifat rahasia sangat esensial untuk mencegah akses tidak sah selama proses transmisi digital melalui berbagai kanal komunikasi. Pendekatan EOF memungkinkan penyisipan file secara tidak terlihat tanpa mengubah struktur asli media gambar, sehingga tidak menurunkan kualitas visual. Sistem dibangun dengan HTML, PHP, JavaScript, dan MySQL sebagai basis backend dan frontend. Pengujian mencakup validasi format file, performa proses enkripsi-dekripsi, serta efektivitas distribusi file melalui WhatsApp, email, dan media penyimpanan fisik. Hasilnya menunjukkan bahwa metode EOF berhasil menyisipkan dan mengekstrak file secara akurat, dengan mutu visual gambar yang tetap terjaga. Sistem yang dihasilkan terbukti dapat menjadi solusi proteksi data yang efektif, fleksibel, dan aplikatif bagi kebutuhan industri.   Kata Kunci : steganografi; End of File; keamanan data; penyisipan file PDF; steganografi gambar
Sentiment Analysis of Oppenheimer Movie Reviews: Naïve Bayes Algorithm for Public Opinion Noviansyah, Berliana; Effendi, Muhammad Makmun; Achmad, Yudianto
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4393

Abstract

The development of information and communication technology has revolutionized the way people consume and engage with media, particularly in the realm of film. Online platforms such as Netflix, Amazon Prime Video, and YouTube have transformed movie consumption habits, providing a vast array of options for viewers to explore and enjoy. A crucial aspect of this digital landscape is the proliferation of movie reviews, which serve as valuable guides for users seeking to discover films aligned with their preferences. However, the abundance of reviews, often varying in quality and objectivity, necessitates tools capable of effectively processing and understanding these textual data. This research delves into sentiment classification of Oppenheimer movie reviews, utilizing the Naive Bayes algorithm to categorize reviews into positive, negative, and neutral sentiments. The dataset comprising audience reviews and numerical ratings undergoes preprocessing using the TF-IDF method to facilitate numerical representation. Subsequently, the Naïve Bayes algorithm is trained on this processed data to accurately classify sentiments. The model demonstrates exceptional performance, achieving an accuracy rate of 97.45% in distinguishing between positive, negative, and neutral sentiments within Oppenheimer movie reviews. This study underscores the efficacy of the Naive Bayes algorithm in sentiment classification and emphasizes the significance of employing techniques like TF-IDF for enhancing sentiment analysis in the domain of movie reviews.
Analysis Prediksi Wilayah Rawan Banjir dengan Algoritma K-Means Effendi, Muhammad Makmun; Inka, Inka; Siswandi, Arif
Journal of Information System Research (JOSH) Vol 5 No 2 (2024): Januari 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v5i2.4770

Abstract

Along with the high amount of rainfall in Bekasi -West Java, floods have started to inundate several areas of Bekasi , one of the causes is the high rainfall factor. According to (Regional Disaster Management Agency) BPBD, the most flood points are in the Bekasi area, causing several activities of the surrounding community to be disrupted, transportation hampered, and also the emergence of disease problems such as skin diseases, diarrhea, and so on. The problem of flooding is a shared responsibility that requires a solution. also the role of technology to help facilitate the provision of information to the public regarding flood-prone areas in the Bekasi area. One technique that can be used is using the K-Means Clustering Algorithm to group flood-prone areas. The flood dataset was processed using the RapidMiner application, for the dataset taken to carry out this analysis from January to December 2022, there were 24 data from areas affected by flooding from various sub-districts and villages in the city of Bekasi. The results of the research produced 3 clusters, namely, the high flood, medium flood and low flood categories, which received a Davies Bouldin index value of -0.452.
Integrasi Programmable Logic Control Outseal Mega V.2 dengan NodeMCU ESP826 dengan menerapkan Internet of Things Effendi, Muhammad Makmun; Taufiq Khasanah; Nurhadi Sirojudin
TEKNOLOGI: Jurnal Ilmiah Sistem Informasi Vol 13 No 1 (2023): January
Publisher : Universitas Pesantren Tinggi Darul 'Ulum (Unipdu) Jombang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/teknologi.v13i1.3868

Abstract

Kemajuan dan Perkembangan Teknologi yang sangat pesat, sehingga di dalam dunia industri memerlukan alat bantu yang lebih modern dan bekerja secara otomatisasi.   Pada saat ini dunia industri terutama mesin injection dan mesin press stamping produksi sudah menggunakan PLC namun belum bekerja secara otomatisasi dan belum terintegrasi dengan Internet of Thing’s. Untuk mempermudah aktivitas produksi maka penulis membuat hardware untuk mesin industri otomatisasi berbasis PLC Outseal Mega V.2 sebagai alternatif mesin industri tersebut dengan metode pendekatan kualitatif. Hardware yang dibuat dengan menggunakan NodeMCU ESP8266 dan modbus RTU serial RS485 dan Arduino Nano dan Blynk diinstalasi secara terstruktur dengan mekanisme adalah NodeMCU ESP8266 terintegrasi dengan modbus RTU serial RS485, sedangkan PLC Outseal Mega V.2 Slim, Arduino Nano terhubung dan terintegrasi dengan modbus RTU serial RS485 dan untuk Blynk NodeMCU ESP8266 terintegrasi dengan wifi. Setelah dirangkai selanjutnya dilakukan pengujian dengan jarak 15 meter PLC outseal Mega V.2 dapat dikontrol Blynknya berbasis Android sehingga integrasi PLC outseal Mega V.2 dapat digunakan dan bekerja di mesin injection maupu mesin pres stamping dapat bekerja secara otomatisasi.