Article Per Year (5 Year)
p-Index From 2020 - 2025
1.633
P-Index
This Author published in this journals
All Journal JTIK (Jurnal Teknik Informatika Kaputama) Journal of Artificial Intelligence and Engineering Applications (JAIEA) Indonesian Journal of Science, Technology, and Humanities Modem : Jurnal Informatika dan Sains Teknologi Repeater: Publikasi Teknik Informatika dan Jaringan Switch: Jurnal Sains dan Teknologi Informasi Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Saturnus: Jurnal Teknologi dan Sistem Informasi
I Gusti Prahmana
Unknown Affiliation
Religion Automotive Engineering Computer Science & IT Control & Systems Engineering Mathematics Social Sciences

Published : 10 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 10 Documents
Search

 1 
IMPLEMENTASI ALGORITMA OTP DAN STEGANOGRAFI EOF DALAM PENYISIPAN PESAN TEKS PADA CITRA muhammad arief; magdalena simanjuntak; I Gusti Prahmana
JTIK (Jurnal Teknik Informatika Kaputama) Vol 6, No 2 (2022): Volume 6, Nomor 2 Juli 2022
Publisher : STMIK KAPUTAMA

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

Abstract

Penggunaan informasi media citra mempunyai beberapa kelemahan, salah satunya adalah mudahnya dimanipulasi oleh pihak-pihak tertentu dengan bantuan teknologi yang berkembang sekarang ini. Upaya yang dapat dilakukan dalam peningkatan pengamanan pengiriman informasi citra adalah kriptografi, yaitu ilmu dan seni untuk menjaga keamanan pesan. Pada penelitian ini diterapkan metode One Time Pad dan Stegnografi End Of File yang bertujuan untuk memperoleh cipher yang lebih kuat dengan menyisipkan pesan kedalam citra sehingga susah untuk di sadap. Algoritma One Time Pad untuk mengenkripsi dan dekripsi, Stegnografi End Of File yang digunakan untuk mengencoding dan mendecoding citra. Hasil dari penelitian ini menunjukkan bahwa dengan menerapkan algoritma One Time Pad dan Stegnografi End Of File dapat mengamankan pesan yang disisipkan kedalam citra dan mengamankan kunci untuk kebutuhan data. Waktu proses encoding dan decoding di pengaruhi oleh banyaknya pesan yang akan dirahasiakan.
Grouping Number of Library Members For Determining the Location of Socialization Using Clustering Method Sella Dwi Pratiwi; Achmad Fauzi; I Gusti Prahmana
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.270

Abstract

The high use of smartphones at this time led to a decline in public interest in reading books in the library directly. Especially students and students. This is certainly a problem for the Langkat Regency Archives and Libraries Office. Socialization is needed to increase efforts to read interest in the community. The right socialization location must have several criteria so that the socialization carried out is right on target. The existence of a database for each member of the library will facilitate the location selection process. Data mining techniques can classify the number of library members based on the results of large data analysis into information in the form of patterns. The clustering method is a method in data mining that can analyze data with the aim of grouping data based on the same characteristics. The K-Means algorithm is a simple algorithm for classifying a large number of objects with certain attributes into clusters which are usually used in data mining.
Rancang Bangun Prototype Alat Smart Parkir Memonitoring Tempat Parkir Kosong Secara Real Time Menggunakan Internet of Things Desva Karliana br Sembiring; Relita Buaton; I Gusti Prahmana
Indonesian Journal of Science, Technology and Humanities Vol. 2 No. 2 (2024): IJSTECH - October 2024
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/ijstech.v2i2.740

Abstract

Sistem berbasis Internet of Things (IoT) telah dikembangkan untuk memantau kadar asap rokok di dalam ruangan secara real-time menggunakan sensor MQ-2. Sensor ini menunjukkan kinerja optimal dalam mendeteksi berbagai jenis gas, termasuk asap rokok, dengan sensitivitas yang memadai. Implementasi sistem ini memungkinkan data pemantauan diakses jarak jauh melalui aplikasi Blynk, menyediakan kontrol dan notifikasi otomatis. Sistem ini dapat mengaktifkan alarm atau ventilasi ruangan secara otomatis ketika kadar asap melebihi batas aman, serta memberikan notifikasi langsung kepada pengguna saat kondisi berbahaya terdeteksi. Hasil pengujian mengkonfirmasi keakuratan deteksi dan efektivitas sistem dalam menjaga kualitas udara dalam ruangan.
Diagnosa Penyakit Obsessive-Compulsive Disorder Menggunakan Metode Certainty Factor Artika Dini Anggriani; Akim M.H. Pardede; I Gusti Prahmana
Modem : Jurnal Informatika dan Sains Teknologi. Vol. 2 No. 4 (2024): Oktober : Modem : Jurnal Informatika dan Sains Teknologi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/modem.v2i4.227

Abstract

Obsessive-Compulsive Disorder (OCD) is a psychiatric disorder characterized by uncontrollable obsessive thoughts and compulsive behaviors. The disorder triggers anxiety in sufferers that often drives them to avoid situations or places that can trigger obsessions, such as shaking hands or using public restrooms. Proper treatment is necessary to prevent further impact on the quality of life of OCD sufferers. However, early diagnosis is often constrained by limited time and access to medical experts. To overcome this, an expert system based on the Certainty Factor method was developed. This system mimics the thought process of a medical expert in diagnosing OCD using symptoms selected by the user. Certainty Factor is used to calculate the certainty level of each diagnosis based on the inputted symptoms. From the analysis, the system is able to provide diagnoses with high accuracy, even reaching 100% for some OCD cases. These results show that expert systems can be an effective tool in detecting OCD early, thus accelerating the process of proper handling and treatment
Penerapan Metode Case Based Reasoning untuk Mendiagnosa Penyakit Demensia Elsa Risqi Amalia; Magdalena Simanjuntak; I Gusti Prahmana
Switch : Jurnal Sains dan Teknologi Informasi Vol. 2 No. 5 (2024): September : Switch: Jurnal Sains dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/switch.v2i5.176

Abstract

Dementia is a growing global health challenge due to the aging population and lifestyle changes. Early and accurate diagnosis is crucial but often difficult and costly. The Case-Based Reasoning (CBR) method in artificial intelligence offers a solution by mimicking human problem-solving based on past experiences. This study aims to develop and implement an efficient and reliable CBR-based dementia diagnosis system. The system is expected to analyze and compare patient symptoms and medical histories with documented cases to provide faster and more accurate diagnostic recommendations. The implementation of CBR in a web-based expert system using PHP and MySQL has proven effective, significantly contributing to the improvement of patient quality of life and healthcare system effectiveness.
Improving the Quality of Digital Images on Identity Cards Using Contrast Stretching and Retinex Methods Salsabilla, Nur; Achmad Fauzi; I Gusti Prahmana
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.645

Abstract

Enhancing the image quality of the Indonesian Identity Card is crucial to ensure the clarity and accuracy of information in various applications, such as identity verification, administration, and security. This study aims to improve the digital image quality of Identity Card using the Contrast Stretching and Retinex methods. Contrast Stretching is employed to enhance image contrast, while the Retinex method is used to maintain and improve the clarity of colors and image details. The implementation of these methods is carried out using Python. The test results show that these methods are effective in improving the quality of Identity Card images, making the information on the images clearer and easier to read. This research contributes to the development of more advanced image processing technology, which can be applied to various verification and administrative needs that require high reliability.
Super Encryption Feal Algorithm and Base64 Algorithm Image File Security Br Bangun, Tiara; Achmad Fauzi; I Gusti Prahmana
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.647

Abstract

In the rapidly advancing digital era, image file security has become a critical issue, especially with the increasing risks of data breaches and attacks on digital files. This study aims to enhance the security of image files by implementing a combination of two cryptographic algorithms: Fast Data Encipherment Algorithm- 4 (FEAL-4) and Base64. FEAL-4 is a symmetric encryption algorithm known for its high speed and processing efficiency, while Base64 is used for encoding binary data into ASCII format to ensure safer transmission. This research develops a super encryption system that integrates these two algorithms to protect the integrity and confidentiality of image files, particularly for BMP, JPEG, and PNG formats. The implementation was carried out using the Visual Basic programming language. The results of the study show that the combination of FEAL-4 and Base64 algorithms significantly enhances the security of image files, with a high success rate in the encryption and decryption processes.
Dinamika Sentimen Komunikasi Mahasiswa dan Dosen dengan Pemanfaatan Analisis Pesan Whatsapp Akademis Menggunakan Machine Learning Abdi Prayogi; Novriyenny Novriyenny; I Gusti Prahmana
Repeater : Publikasi Teknik Informatika dan Jaringan Vol. 3 No. 2 (2025): Repeater : Publikasi Teknik Informatika dan Jaringan
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/repeater.v3i2.404

Abstract

Communication is the process of exchanging information, ideas, thoughts, and feelings between individuals or groups through the use of words, signs, or actions. This process can take place verbally or non-verbally and involves various media and channels, such as face-to-face conversations, writing, gestures, facial expressions, and digital technology. This research was conducted at STMIK Kaputama Binjai, namely the WhatsApp group between lecturers and students. This study uses the Support Vector Machine (SVM) method. SVM is a type of supervised learning machine learning that requires sample data. Support Vector Machine (SVM) is an algorithm developed by Boser, Guyon, and Vapnik in 1992. Support Vector Machine (SVM) has a concept that is combined with previous computational theories. This method can transform training data into higher dimensions using non-linear patterns. The results of the Support Vector Machine method classification with a total of 16 positive sentiments, 40 neutral sentiments and 71 negative sentiments. Accuracy value 67%, margin error 39%. Positive prediction precision 75%, neutral prediction precision 83% and negative prediction precision 88%..
Optimasi Penyusunan Koleksi Buku Dinas Perpustakaan Berdasarkan Pola Peminjaman dengan Metode Apriori : (Studi Kasus: Dinas Perpustakaan) Dinda Firdawati Simamora; Rusmin Saragih; I Gusti Prahmana
Saturnus : Jurnal Teknologi dan Sistem Informasi Vol. 2 No. 4 (2024): Oktober : Saturnus : Jurnal Teknologi dan Sistem Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/saturnus.v2i4.360

Abstract

A library is a facility or place that provides reading materials. Good book arrangement can help the library in obtaining good reading sources. The arrangement of library service book collections based on borrowing patterns, there is an alignment between user needs and the availability of reading materials available in the library. Analysis of book borrowing patterns provides valuable insights for library staff in determining the books that are most in demand and often needed by users. Data mining is defined as mining data or efforts to dig up valuable and useful information in a very large database. The most important thing in data mining techniques is the rule for finding high frequency patterns between sets of itemsets called Association Rules. The method used in this study is Apriori (Association Rule). This technique is used to find relationships or associations between items or variables in data. Well-known algorithms such as Apriori and Eclat are used to find association rules in transactional data. The purpose of this study is to find out library visitor data using the Apriori Algorithm method and to find out the application of data mining for compiling book collections based on borrowing patterns. The results of this study are the multiplication of support and confidence, choose the one with the largest multiplication result. The largest result of the multiplication of these multiplications is the rule used when borrowing books. Because the results of the multiplication of the 4 borrowings have the same value, all of them can be used as rules.
Penerapan Metode Teorema Bayes untuk Memprediksi Penyakit pada Tanaman Kopi Zulkifli Zulkifli; Relita Buaton; I Gusti Prahmana
Neptunus: Jurnal Ilmu Komputer Dan Teknologi Informasi Vol. 3 No. 3 (2025): Agustus : Neptunus : Jurnal Ilmu Komputer Dan Teknologi Informasi
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/neptunus.v3i3.1025

Abstract

Coffee is a leading commodity in Indonesia's agricultural sector, possessing high economic value and providing a livelihood for many farmers. However, coffee plant productivity often declines significantly due to various diseases affecting the leaves, stems, and berries. This situation is exacerbated by the lack of knowledge among most farmers in recognizing early disease symptoms, resulting in delayed treatment. Consequently, crop losses are unavoidable. Based on these challenges, this study aims to design and build an expert system capable of diagnosing coffee plant diseases quickly, precisely, and accurately using the Bayesian Theorem method. This method was chosen because it can calculate the probability of a disease occurring based on observed symptoms in plants. The Bayesian approach allows the system to provide more reliable diagnostic results by updating the probability values ​​as new evidence is introduced. The developed expert system is web-based, making it easily accessible to users, both farmers and other interested parties. Users simply select the symptoms observed in coffee plants, and the system will then provide a diagnostic result in the form of possible diseases and their probability levels. Test results indicate that the system is capable of providing fairly accurate diagnostic results and can be used as a basis for farmers in making initial decisions regarding coffee plant disease management. With this expert system, farmers are expected to improve their ability to detect coffee plant diseases early, thereby maintaining crop productivity. This expert system is expected to be an effective decision support tool for farmers to reduce crop losses and improve agricultural sustainability.
Co-Authors Abdi Prayogi Artika Dini Anggriani Br Bangun, Tiara Buaton, Relita Desva Karliana br Sembiring Dinda Firdawati Simamora Elsa Risqi Amalia Fauzi, Achmad Magdalena Simanjuntak magdalena simanjuntak muhammad arief Novriyenny Novriyenny Pardede, Akim Manaor Hara Rusmin Saragih, Rusmin Salsabilla, Nur Sella Dwi Pratiwi Zulkifli Zulkifli