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All Journal Jurnal Pengabdian UntukMu NegeRI Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Innovation in Research of Informatics (INNOVATICS) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) Journal of Software Engineering and Information System (SEIS)
Mualfah, Desti
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Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Social Sciences

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Journal : Journal of Software Engineering and Information System (SEIS)

 1 
ANALISIS PERBANDINGAN IPv4 DENGAN IPv6 PENGGUNAAN CCTV BERBASIS AREA TRAFFICT CONTROL SECURITY (ATCS) Mualfah, Desti; Putra, Gope Mandala; Firdaus, Rahmad
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 2 No. 1 (2022)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (670.031 KB) | DOI: 10.37859/seis.v2i1.3339

Abstract

Internet access is an activity that cannot be separated from the needs of the community, it can be seen from the many activities that use TCP/IP-based internet access. The use of the internet protocol using IPv4 which is currently starting to not meet human needs, it is recommended to be able to implement IPv6 which has a simple header and has a better QoS (Quality of Service). One of these IPv6 is applied to traffic CCTV cameras based on ATCS (Area Traffic Control Security) which works to unify and record traffic activities for 24 hours in the hope that the video streaming results have better network quality.
AKUISISI BUKTI DIGITAL PADA APLIKASI TAMTAM MESSENGER MENGGUNAKAN METODE NATIONAL INSTITUTE OF JUSTICE Mualfah, Desti; Viransa, Afdel; Amran, Hasanatul Fu’adah
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 3 No. 1 (2023)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (750.131 KB) | DOI: 10.37859/seis.v3i1.4548

Abstract

Smartphones are one of the tools used in carrying out daily work activities, the number of active social media users in Indonesia in January 2019 reached 150 million, 130 million of whom accessed social media using smartphones. With the development of smartphones in social media, many are misused using instant messaging applications, one of which is cybercrime such as cyberbullying, human trafficking systems, fraud and so on. Cyberbullying is one of the negative impacts in cyber crime through the use of applications that are often used, namely the TamTam Messenger social media. The problem that will be discussed in this study is the digital forensic process, especially mobile forensics in order to find digital evidence that was deleted on the TamTam Messenger application using the MobileEdit forensic tools and the National Institute of Justice method. The results of this study show that using the MobileEdit forensic tools and the National Institute of Justice method succeeded in recovering digital evidence that had been deleted by the perpetrator on the TamTam Messenger application.
KLASIFIKASI BUAH JERUK LEMON BERDASARKAN TINGKAT KEMATANGAN MENGGUNAKAN METODE SVM DAN NAIVE BAYES Mualfah, Desti; Rivaldi, Hardi; Januar Al Amin; Sunanto
Jurnal Rekayasa Perangkat Lunak dan Sistem Informasi Vol. 5 No. 2 (2025)
Publisher : Department of Information System Muhammadiyah University of Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/seis.v5i2.9952

Abstract

This study aims to develop a classification model for determining the ripeness level of lemons (Citrus limon) using digital image analysis. Two methods, namely Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC), were compared to evaluate their performance in terms of accuracy and prediction consistency. The results show that SVM outperformed NBC with an accuracy of 97%, along with precision, recall, and F1-Score of 97% each. The model consistently determined lemon ripeness levels in percentage terms, such as 85% or 95%. In contrast, NBC achieved an accuracy of 82%, with precision, recall, and F1-Score of 83%, 82%, and 83%, respectively. However, NBC was more prone to classification errors, especially in distinguishing between ripe and unripe lemons. In conclusion, the SVM method proved superior to NBC in determining lemon ripeness levels, particularly in handling complex data. SVM's ability to provide accurate and consistent predictions makes it a more effective choice for helping farmers optimize the quality and quantity of lemon production. This study contributes significantly to the application of image processing technology in the agricultural sector.
Co-Authors Admojo, Fadhila Tangguh Aminuyati Amran, Hasanatul Fu’adah Baidarus Evans Fuad Fadila, Wahyu Gea, Meiriladiwis Gunawan, Rahmad Gunawan, Sulka Israndi, Febri Januar Al Amin Kamal Saputra, Taufiq Mahesa, Pandu Majid, Sidratul Salsabila Malindo, Qori Mardiah, Adilla Muhammad Innuddin Muhammad Iqbal Syam Novia5, Sherlin Okta Prihatin, Ananda Putra, Gope Mandala Rahmad Firdaus Rahmad Firdaus Rahmadeli, Safitri Rajif, Iqbal Ramadhan, Rizdqi Akbar Rivaldi, Hardi Rizki, Yoze Ronaldo, Aditya Rudi Ardiansyah Sandi, Ganesa Heru Slamet Risnanto Sunanto Viransa, Afdel Windiawati, Ai Wulan Zacki, Moh Soulthan