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Comparing Neural Networks, Support Vector Machines, and Naïve Bayes Algorhythms for Classifying Banana Types Abwabul Jinan; Manutur Siregar; Vicky Rolanda; Dede Fika Suryani; Abdul Muis
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3381

One of the most significant fruits for human consumption is the banana. Fruit consumption not only promotes health but also lowers the risk of heart disease, stroke, digestive issues, hypertension, some cancers, cataracts in the eyes, skin ailments, cholesterol reduction, and, perhaps most importantly, boosts immunity.The study included secondary data, which is information gathered from online resources like Kaggle. Ten categories of bananas will be identified from the 531 total varieties of bananas used as a train dataset: Ambon bananas, Stone bananas, Cavendish bananas, Kepok bananas, Mas bananas, Red bananas, plantains, Milk bananas, Horn bananas, and Varigata bananas. The development of information technology for image object recognition has become a very intriguing topic along with the rapid advancement of society, and it is undoubtedly directly tied to information data. In order to examine Naive Bayes, Support Vector Machine, and Neural Network techniques for classifying banana types, researchers will use the SqueezeNet Deep Learning model to extract features from photos. The study's findings will provide empirical evidence for the distinctions between each algorithm's accuracy, recall, and precision. Based on the collected results, the Neural Network (NN) method is the best in terms of classification, with accuracy of 72.3%, precision of 72.1%, and recall of 72.3%.

Disguising Text Using Caesar Cipher, Reverse Cipher and Least Significant Bit (LSB) Algorithms in Video Siregar, Manutur; Jinan, Abwabul; Muhammad Raja Gunung, Tar
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.v6i3.4217

In communication, there is a process of transferring information from the sender to the recipient. The information sent must be the same as the information received. If there are differences, it means that there has been a data change process carried out by irresponsible parties. One technique for changing the content of information is man in the middle. The data changer will receive information from the sender, then change it and forward it to the recipient, so that the changed information appears to have come from the sender.To protect information, this can be done by utilizing the science of cryptography and steganography which aims to protect information by changing it to another form or by inserting the information into other media. In this research, to protect information the Caesar Cipher Algorithm is used, this algorithm will change the letters in plaintext to another letter (ciphertext) by using an alphabetical shift according to the number in the form of the key used, namely > 1 and < 26, then the Reverse Cipher algorithm is carried out, namely changing the position of the letters of the plaintext from the first order to the last order and so on. The encrypted information will then be inserted into a video using the Steganography Algorithm, namely Least Significant Bit (LSB). Before being inserted, the video will first be converted into several image frames, then in one frame the information will be inserted. This can be done because the frame is a collection of RGB arrays which have values 0-255 or 0 and 1. So the insertion is done in bit form. Frames containing information will then be converted back into a video.On the receiving side, the video will be converted into a frame, next is the process of retrieving the information that was previously inserted. The information that has been taken is then reversed in order and then shifted using the Caesar chipper algorithm according to the key used by the sender, then the first letter of each word is changed to capital, so that the information sent is the same as that received. The implication of this research is that it is a way to combine cryptography with steganography as an information security technique.

Implementasi Metode Case-Based Reasoning (CBR) dalam Sistem Pakar untuk Mendapatkan Diagnosis Anxiety Disorders Gunung, Tar Muhammad Raja; Lubis, Siti Sahara; Siregar, Manutur; Simanjuntak, Peter Jaya Negara; Jinan, Abwabul
Jurnal Teknologi Terpadu Vol 10 No 2 (2024): Desember, 2024
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v10i2.1480

This research aims to develop an expert system based on the case-based reasoning method for diagnosing anxiety disorders. Anxiety Disorder is a mental health disorder that is often experienced by the public but is often not detected correctly. The case-based reasoning method was chosen because of its ability to utilise previous cases to solve new problems that have similarities. Case-based reasoning uses four main stages: retrieval, reuse, revise, and retain. The case-based reasoning method is implemented using case data obtained from psychology clinics and interviews with mental health experts. Testing the case-based reasoning method shows a high level of accuracy in diagnosing various types of Anxiety Disorders, such as Generalised Anxiety Disorder, Panic Disorder, and Specific Phobias. The results of this study show that the case-based reasoning method can be an effective tool in helping mental health professionals diagnose Anxiety Disorders more quickly and accurately. After searching using the symptoms obtained, the percentage of each type of disease is the percentage of Generalised Anxiety Disorder 35.7%, the percentage of Panic Disorder 30.7%, and the percentage of Specific Phobias 65%.

Penerapan Algoritma Sorting dalam Penentuan Pekerja Pada Aplikasi Cari Kerja Oleh dan Untuk Warga Satu Kelurahan Dataran Tinggi Binjai Siregar, Manutur Pandapotan; Jinan, Abwabul; Siagian, Akbar Idaman Prince Peter S.
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp294-300

The current job search process often involves posting an announcement on paper or a banner on a notice board, or in front of the company’s location. Another common method is through job search applications, such as JobStreet and others. The first method has a drawback because people may not know when the job posting is published. Meanwhile, with the second method, many people hesitate to use these applications as they feel their skills may not be sufficient. To address these issues, an Android or web-based job search application is proposed to facilitate job sharing and job seeking within a nearby area, specifically within a single subdistrict. This application is targeted at individuals with a high school education level or lower, and the jobs shared are typically daily work requiring minimal skills, such as construction work, electrical repairs, gardening, cleaning, and similar tasks. A sorting algorithm will be implemented to help select the nearest and most suitable candidate for each job. To access the application, users must first register, enabling employers to post jobs and workers to find suitable positions.

Pengenalan Teknologi AI Berkelanjutan melalui Pelatihan Partisipatif dan Pendekatan Interdisipliner untuk Mendorong Inovasi Pendidikan di Kalangan Pelajar Harahap, Siti Sarah; Simamora, Windi Saputri; Hadistio, Ryan Rinaldi; Siregar, Manutur Pandapotan
Jurnal PKM: Pengabdian Kepada Masyarakat Vol 7, No 6 (2024): Jurnal PkM: Pengabdian kepada Masyarakat
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jurnalpkm.v7i6.26709

Comparing Neural Networks, Support Vector Machines, and Naïve Bayes Algorhythms for Classifying Banana Types Jinan, Abwabul; Siregar, Manutur; Rolanda, Vicky; Suryani, Dede Fika; Muis, Abdul
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3381

One of the most significant fruits for human consumption is the banana. Fruit consumption not only promotes health but also lowers the risk of heart disease, stroke, digestive issues, hypertension, some cancers, cataracts in the eyes, skin ailments, cholesterol reduction, and, perhaps most importantly, boosts immunity.The study included secondary data, which is information gathered from online resources like Kaggle. Ten categories of bananas will be identified from the 531 total varieties of bananas used as a train dataset: Ambon bananas, Stone bananas, Cavendish bananas, Kepok bananas, Mas bananas, Red bananas, plantains, Milk bananas, Horn bananas, and Varigata bananas. The development of information technology for image object recognition has become a very intriguing topic along with the rapid advancement of society, and it is undoubtedly directly tied to information data. In order to examine Naive Bayes, Support Vector Machine, and Neural Network techniques for classifying banana types, researchers will use the SqueezeNet Deep Learning model to extract features from photos. The study's findings will provide empirical evidence for the distinctions between each algorithm's accuracy, recall, and precision. Based on the collected results, the Neural Network (NN) method is the best in terms of classification, with accuracy of 72.3%, precision of 72.1%, and recall of 72.3%.

Desain dan Rancang Bangun Sistem E-Learning Menggunakan Framework Laravel Berbasis WEB Jinan, Abwabul; Siregar, Manutur Pandapotan; Suryani, Dede Fika; Rolanda, Vicky; Muis, Abdul
ROUTERS: Jurnal Sistem dan Teknologi Informasi Vol. 3 No. 2, Juli 2025 (In Progress)
Publisher : Program Studi Teknologi Rekayasa Internet, Politeknik Negeri Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25181/rt.v3i2.4182

The design and development of a web-based E-Learning system using the Laravel framework aims to provide an effective and structured digital learning solution. This system is developed to address the limitations of face-to-face learning time in traditional classrooms and to leverage technological advancements in order to enhance educational quality. Utilizing Laravel as the primary development framework, the system is built with PHP, HTML, CSS, and JavaScript technologies, and MySQL as the database engine. The E-Learning platform features core functionalities such as instructional material management, class administration, structured user accounts (admin, teacher, and student roles), as well as support for material download and task submission. Testing results indicate that the system performs effectively and supports flexible and efficient teaching and learning processes. It is expected that this system will serve as a reliable and sustainable learning medium to support technology-based academic activities.

SISTEM PAKAR PEMILIHAN SMARTPHONE BERDASARKAN KEBUTUHAN DAN PREFERENSI USER MENGGUNAKAN METODE CASE BASED REASONING Gunung, Tar Muhammad Raja; Egani Sitepu, Sengli; Pandapotan Siregar, Manutur; Muis, Abdul; Rolanda, Vicky
Djtechno: Jurnal Teknologi Informasi Vol 6, No 2 (2025): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i2.7167

Pemilihan smartphone yang sesuai dengan kebutuhan pengguna sering kali menjadi permasalahan tersendiri, terutama karena banyaknya pilihan produk dengan spesifikasi yang bervariasi. Penelitian ini bertujuan untuk menerapkan metode Case Based Reasoning (CBR) dalam proses rekomendasi smartphone berdasarkan preferensi pengguna. CBR bekerja dengan membandingkan kasus baru, yaitu kebutuhan dan kriteria pengguna, dengan kasus-kasus sebelumnya yang telah tersimpan dalam basis data untuk menentukan tingkat kemiripan. Pada penelitian ini, digunakan empat tahapan utama dalam metode CBR yaitu: Retrieve, Reuse, Revise, dan Retain.Hasil pengujian menunjukkan bahwa dari 13 alternatif smartphone yang dianalisis, Xiaomi Poco X5 Pro mendapatkan nilai kemiripan sebesar 100%, sedangkan perangkat lainnya seperti Realme Narzo 60x, Infinix Smart 8, Vivo V27, Samsung Galaxy A54, dan lainnya memperoleh nilai kemiripan 0%. Hal ini menunjukkan bahwa Xiaomi Poco X5 Pro merupakan pilihan paling sesuai dengan kebutuhan pengguna dalam studi kasus ini. Dengan demikian, metode CBR terbukti mampu memberikan rekomendasi yang tepat dan terukur, serta dapat menjadi dasar pengembangan sistem pakar atau sistem pendukung keputusan di masa mendatang.

Optimasi Implementasi Kriptografi Kunci Publik dalam Meningkatkan Keamanan dan Otentikasi Data pada Sistem Informasi Kampus Jinan, Abwabul; Siregar, Manutur Pandapotan; Suryani, Dede Fika; Muis, Abdul; Gunung, Tar Muhammad Raja
Digital Transformation Technology Vol. 5 No. 2 (2025): Periode September 2025
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v5i2.6425

Perkembangan teknologi digital dan kebutuhan akan keamanan sistem informasi menjadi semakin penting, terutama di lingkungan universitas. Penelitian ini berfokus pada optimalisasi implementasi kriptografi kunci publik untuk meningkatkan keamanan data dan otentikasi dalam sistem informasi kampus. Algoritma yang digunakan antara lain RSA (Rivest-Shamir-Adleman) untuk enkripsi data dan DSA (Digital Signature Algorithm) untuk otentikasi digital. Hasil penelitian menunjukkan bahwa kombinasi RSA dan DSA efektif dalam melindungi kerahasiaan dan integritas data, serta memastikan bahwa informasi tetap otentik selama transmisi. Implementasi sistem diuji berdasarkan kecepatan enkripsi, akurasi otentikasi, dan efektivitas keamanan. Selain itu, analisis pengoptimalan dilakukan untuk menyeimbangkan kinerja dan tingkat keamanan dengan menyesuaikan ukuran kunci dan proses enkripsi selektif. Penelitian ini menyimpulkan bahwa penerapan kriptografi kunci publik di lingkungan universitas tidak hanya meningkatkan keamanan tetapi juga meningkatkan kepercayaan pengguna dalam menggunakan sistem informasi akademik.

Penerapan Algoritma Sorting dalam Penentuan Pekerja Pada Aplikasi Cari Kerja Oleh dan Untuk Warga Satu Kelurahan Dataran Tinggi Binjai Siregar, Manutur Pandapotan; Jinan, Abwabul; Siagian, Akbar Idaman Prince Peter S.
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp294-300

The current job search process often involves posting an announcement on paper or a banner on a notice board, or in front of the company’s location. Another common method is through job search applications, such as JobStreet and others. The first method has a drawback because people may not know when the job posting is published. Meanwhile, with the second method, many people hesitate to use these applications as they feel their skills may not be sufficient. To address these issues, an Android or web-based job search application is proposed to facilitate job sharing and job seeking within a nearby area, specifically within a single subdistrict. This application is targeted at individuals with a high school education level or lower, and the jobs shared are typically daily work requiring minimal skills, such as construction work, electrical repairs, gardening, cleaning, and similar tasks. A sorting algorithm will be implemented to help select the nearest and most suitable candidate for each job. To access the application, users must first register, enabling employers to post jobs and workers to find suitable positions.

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