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All Journal JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Information Technology and Computer Science (JOINTECS) Zero : Jurnal Sains, Matematika, dan Terapan INFOKUM Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknologi Informasi dan Komunikasi Syntax: Journal of Software Engineering, Computer Science and Information Technology Instal : Jurnal Komputer JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Mathematics and Scientific Computing With Applications Journal of Computer Science and Informatics Engineering Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Jurnal Ilmiah Teknik Informatika dan Komunikasi Journal Of Informatics And Busisnes Jurnal Ilmiah Research Student
Mhd Ikhsan Rifki
Universitas Islam Negeri Sumatera Utara
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences

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KLASIFIKASI PENYAKIT PADA DAUN CABAI MENGGUNAKAN GRAY LEVEL CO-OCCURRENCE MATRIX DAN K-NEAREST NEIGHBOR Pulungan, Miftahul Rizky; Furqan, Mhd; Rifki, Mhd Ikhsan
Syntax : Journal of Software Engineering, Computer Science and Information Technology Vol 5, No 2 (2024): Desember 2024
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/syntax.v5i2.5386

Abstract

Penyakit tanaman cabai dapat menyebabkan penurunan produksi yang signifikan, sehingga membuat keberlanjutan pertanian dan pangan. Penelitian ini mengembangkan sistem untuk mengkategorikan daun cabai menggunakan Gray Level Co-occurrence Matrix (GLCM) untuk ekstraksi tekstur dan K-Nearest Neighbors (KNN) untuk klasifikasi. Data citra daun cabai yang digunakan meliputi jenis penyakit virus mosaik cabai, layu fusarium, virus kuning, dan bercak daun. Proses tersebut meliputi pemilihan citra, ekstraksi fitur menggunakan GLCM, dan klasifikasi menggunakan KNN. Hasil penelitian menunjukkan bahwa rasio tersebut dapat mencapai hingga 90%, tergantung pada parameter K. Temuan ini penting bagi dunia pertanian, karena dapat menjadi dasar pengembangan sistem deteksi dini berbasis teknologi, sehingga petani dapat mengambil tindakan lebih cepat dan efektif dalam mengendalikan penyebaran penyakit. Implementasi metode ini memiliki potensi besar untuk meningkatkan efisiensi pengelolaan tanaman, mengurangi kerugian ekonomi, dan mendukung pertanian berkelanjutan.Kata kunci: Penyakit daun cabai, K-Nearest Neighbor, GLCM, Klasifikasi. ABSTRACT Chili plant diseases can cause significant production declines, thus making the sustainability of agriculture and food. This study develops a system to categorize chili leaves using Gray Level Co-occurrence Matrix (GLCM) for texture extraction and K-Nearest Neighbors (KNN) for classification. The chili leaf image data used includes types of chili mosaic virus diseases, fusarium wilt, yellow virus, and leaf spots. The process includes image selection, feature extraction using GLCM, and classification using KNN. The results of the study show that the ratio can reach up to 90%, depending on the K parameter. This finding is important for the world of agriculture, because it can be the basis for the development of a technology-based early detection system, so that farmers can take faster and more effective action in controlling the spread of disease. The implementation of this method has great potential to improve the efficiency of crop management, reduce economic losses, and support sustainable agriculture. Keywords: Chile leaf disease, K-Nearest Neighbor, GLCM, Classification.
Performance Evaluation of RSSI Prediction Methods in Wireless Communication Networks Rifki, Mhd Ikhsan; Ikhwan, Ali; Muhammad, Faisal
ZERO: Jurnal Sains, Matematika dan Terapan Vol 8, No 1 (2024): Zero: Jurnal Sains Matematika dan Terapan
Publisher : UIN Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/zero.v8i1.19420

Abstract

Continuous communication services that ensure user connectivity with the communication network are important. The communication network should be able to accommodate erratic user movements with high mobility. This research studies the performance of three different RSSI prediction methods: decision trees, random forests, and linear regression. Evaluation is carried out using statistical metrics, including mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and percentage accuracy. This analysis was carried out to understand how well each model predicted RSSI values based on distance. The research results show that Decision Tree Performance has an accuracy of 83.333%, Random Forest has a high accuracy of 97.2545%, and the Linear Regression Model provides quite good predictions with an accuracy of 91.6667% in predicting RSSI values.
Rancang Bangun Sistem Informasi Pengelolaan Arsip Dokumen Berbasis WEB pada PT. BPRS Amanah Insan Cita Julianti, Miranda; Aulia, M. Arif; Rifki, Muhammad Ikhsan
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 3 No. 3 (2023): November: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v3i3.2303

Abstract

Sistem informasi berbasis web adalah kombinasi dari teknologi informasi berdasarkan suatu situs pada jaringan internet yang dilengkapi dengan fitur-fitur dan didesain sedemikian rupa sesuai kebutuhan pada penginputan suatu data tertentu bertujuan untuk mempermudah dan mempercepat data yang diolah meskipun pengguna tersebut merupakan pemula. Perusahaan memanfaatkan perkembangan teknologi internet dan sistem Informasi yang berkembang pesat saat ini. PT. BPRS Amanah Insan Cita adalah lembaga keuangan yang kegiatannya menghimpun dana, menyediakan pembiayaan dan penempatan dana kepada masyarakat Indonesia khususnya masyarakat kota medan dan sekitarnya berdasarkan prinsip syariah dan bagi hasil yang telah disepakati kedua belah pihak baik nasabah maupun bank. Metode yang diterapkan dalam penelitian ini adalah metode waterfall yang merupakan sebuah model metode penelitian sistematis dan sequence yang layak diterapkan dalam melakukan penelitian ini karena metode ini menyajikan tahap demi tahap yang sangat sesuai dengan keadaan di lapangan. Dengan adanya sistem informasi ini, maka dapat memberikan informasi yang tepat dan cepat terkait data arsip dokumen pada PT BPRS Amanah Insan Cita.
Rancang Bangun Sistem Informasi Pengelolaan Inventaris Berbasis WEB pada PT BPRS Amanah Insan Cita Hasibuan, Ainun Mardiah; Nasution, Fadhilah Ramadhani; Rifki, Muhammad Ikhsan
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 3 No. 3 (2023): November: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v3i3.2304

Abstract

Sistem informasi berbasis web adalah kombinasi dari teknologi informasi berdasarkan suatu situs pada jaringan internet yang dilengkapi dengan fitur-fitur dan didesain sedemikian rupa sesuai kebutuhan pada penginputan suatu data tertentu bertujuan untuk mempermudah dan mempercepat data yang diolah meskipun pengguna tersebut merupakan pemula. Perusahaan memanfaatkan perkembangan teknologi internet dan sistem Informasi yang berkembang pesat saat ini. PT. BPRS Amanah Insan Cita adalah lembaga keuangan yang kegiatannya menghimpun dana, menyediakan pembiayaan dan penempatan dana kepada masyarakat Indonesia khususnya masyarakat kota medan dan sekitarnya berdasarkan prinsip syariah dan bagi hasil yang telah disepakati kedua belah pihak baik nasabah maupun bank. Metode yang diterapkan dalam penelitian ini adalah metode waterfall yang merupakan sebuah model metode penelitian sistematis dan sequence yang layak diterapkan dalam melakukan penelitian ini karena metode ini menyajikan tahap demi tahap yang sangat sesuai dengan keadaan dilapangan. Dengan adanya sistem informasi ini, maka dapat memberikan informasi yang tepat dan cepat terhadap ketersediaan inventaris pada PT BPRS Amanah Insan Cita.
IMPLEMENTATION OF A CULINARY TOURISM RECOMMENDATION SYSTEM FOR MEDAN CITY USING THE COLLABORATIVE FILTERING METHOD Adha Hasibuan, Aidillia; Khalil Gibran, M.; Ikhsan Rifki, Mhd
Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 1 (2025)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v6i1.988

Abstract

Culinary tourism has its own appeal for tourists visiting an area, but the tourists who come may not necessarily know the culinary offerings in that area, so a system is needed that can provide recommendations to tourists. A recommendation system is a system that can provide suggestions to its users regarding a particular item, and the suggestions given are used in various decision-making processes. The method used is Collaborative Filtering. The problem is how to apply the Collaborative Filtering method to recommend food with many influencing factors, resulting in a relevant recommendation. The recommendation process involves grouping users into a specific group through the clustering process using the K-Mean method, after which the software calculates the similarity between the user and the group members. The calculation of similarity between users and their group members uses the Pearson correlation coefficient formula. The determination of the recommendation results provided uses a ranking system with the highest recommendation values. The data used consists of 18 food data, 100 training data, and 10 testing data. The results of the relevance percentage test reached 80%.
IMPLEMENTATION OF A CULINARY TOURISM RECOMMENDATION SYSTEM FOR MEDAN CITY USING THE COLLABORATIVE FILTERING METHOD Adha Hasibuan, Aidillia; Khalil Gibran, M.; Ikhsan Rifki, Mhd
Journal of Mathematics and Scientific Computing With Applications Vol. 6 No. 1 (2025)
Publisher : Pena Cendekia Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53806/jmscowa.v6i1.988

Abstract

Culinary tourism has its own appeal for tourists visiting an area, but the tourists who come may not necessarily know the culinary offerings in that area, so a system is needed that can provide recommendations to tourists. A recommendation system is a system that can provide suggestions to its users regarding a particular item, and the suggestions given are used in various decision-making processes. The method used is Collaborative Filtering. The problem is how to apply the Collaborative Filtering method to recommend food with many influencing factors, resulting in a relevant recommendation. The recommendation process involves grouping users into a specific group through the clustering process using the K-Mean method, after which the software calculates the similarity between the user and the group members. The calculation of similarity between users and their group members uses the Pearson correlation coefficient formula. The determination of the recommendation results provided uses a ranking system with the highest recommendation values. The data used consists of 18 food data, 100 training data, and 10 testing data. The results of the relevance percentage test reached 80%.
Text Data Security Application Using a Mobile-Based Base64 Algorithm Rifki, Mhd Ikhsan; Muhammad Ezar Raditya; Abdul Halim Hasugian
Bahasa Indonesia Vol 15 No 02 (2023): Instal : Jurnal Komputer Periode (Juli-Desember)
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i02.146

Abstract

During the process of sending data or information on a communications network, various types of data and important information related to personal data and identity are often transacted on the network. This can be exploited by irresponsible parties to gain personal gain by duplicating personal data or information. So, protection is needed for data sent via communication networks. According to Law No. 27 of 2022, personal data protection includes all efforts to protect personal data and guarantee the constitutional rights of personal data subjects. Based on this, the research objective is to provide users with options to provide additional security for text data in the form of personal data. The base64 application provides data security by changing plaintext into ciphertext, which has an information structure that is very different from the original form of information. The text data security application using the base64 algorithm was designed using the Unified Modeling Language (UML) system development method. Regarding application development, the framework used is modular. So, with this application, text data has additional data security options to avoid behavior that could be detrimental.
Analisis Sentimen Masyarakat pada Platform Media Sosial X (Twitter) terhadap Pelantikan Kabinet Merah Putih Menggunakan Bernoulli Naïve Bayes Rambe, M. Riski Andika; Zufria, Ilka; Rifki, Mhd. Ikhsan
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 1: JUNI 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i1.6360

Abstract

Penelitian ini bertujuan untuk menganalisis sentimen masyarakat terhadap pelantikan Kabinet Merah Putih melalui platform media sosial X (sebelumnya Twitter) menggunakan algoritma Bernoulli Naive Bayes. Data sebanyak 1.000 tweet dikumpulkan dan diproses melalui tahapan preprocessing, tokenisasi, penghapusan stopwords, stemming, serta pembobotan menggunakan TF-IDF. Selanjutnya, data diklasifikasikan ke dalam sentimen positif dan negatif. Model dilatih dengan 700 data dan diuji dengan 300 data. Hasil evaluasi menunjukkan bahwa model mencapai akurasi sebesar 78%, dengan precision untuk kelas positif sebesar 0.775 dan recall sebesar 0.677, sedangkan precision dan recall untuk kelas negatif masing-masing sebesar 0.783 dan 0.856. Temuan ini menunjukkan bahwa Bernoulli Naive Bayes efektif dalam mengidentifikasi sentimen masyarakat secara umum, terutama pada sentimen negatif. Penelitian ini memberikan gambaran persepsi publik terhadap pelantikan kabinet serta menjadi dasar untuk pengambilan keputusan kebijakan komunikasi pemerintah yang lebih baik.
Implementasi Base64, Beaufort Cipher, Vigenere Cipher, Untuk Pengamanan File Source Code Dalam Bahasa Pemrograman Harjo, William Lutfir Rahman; Ikhsan, Muhammad; Rifki, Mhd Ikhsan
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 6, No 1: JUNI 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v6i1.6339

Abstract

Kriptografi adalah teknik digunakan untuk menjaga kerahasiaan suatu data. Suatu data yang dianggap penting dan dirasa sensitif, sebaiknya diberikan suatu pengamanan untuk melindungi kerahasiaannya. Pada penelitian ini mengimplementasikan algoritma Base64, Beaufort Cipher dan Vigenere Cipher guna meningkatkan keamanan pada file source code dalam berbagai ekstensi bahasa pemrograman. Tahapan enkripsi yang dilakukan pada penelitian ini dengan cara merubah teks didalam file source code terlebih dahulu kedalam format Base64, kemudian mengenkripsi menggunakan algoritma Beaufort Cipher dan dilanjutkan menggunakan algoritma Vigenere Cipher untuk menghasilkan file source yang telah terenkripsi. Penelitian ini menghasilkan aplikasi berbasis web. Pengujian avalanche effect, bit error rate, character error rate, entropy dan blackbox pada aplikasi, telah dilakukan agar memastikan bahwa aplikasi bekerja sesuai dengan spesifikasinya dan sudah layak untuk digunakan.
Comparison of Naïve Bayes and Dempster Shafer Algorithms for the Diagnosis of ARI Diseases Haikal, Baginda Fikri; Hasibuan, Muhammad Siddik; Rifki, Mhd Ikhsan
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1161

Abstract

Acute Respiratory Infection (ARI) has a high prevalence in Indonesia, but the manual diagnosis process faces challenges such as limited medical personnel and uncertainty in symptom analysis. This study developed and compared two AI methods, namely Naïve Bayes and Dempster-Shafer, in a web-based expert system to diagnose ARI. Symptom and disease data were collected from literature and experts, then implemented in a PHP and MySQL-based system. Naïve Bayes was used for probability-based classification, while Dempster-Shafer handled uncertainty. Testing was conducted on one case of ARI. Naïve Bayes produced a probability of 21.99% for Pneumonia, while Dempster-Shafer provided a combined probability of 61.6% for five diseases, including Colds, Acute Pharyngitis, and Epiglottitis. The results show that Naïve Bayes is suitable for consistent single diagnoses, while Dempster-Shafer is more appropriate for conditions with overlapping symptoms and uncertain data
Co-Authors Abdul Halim Hasugian Adha Hasibuan, Aidillia Afandi Sahputra Aidil Akbar Simatupang Aidil Halim Lubis Ali Darta Andilala Aulia, M. Arif Bagas F, Muhammad Dwi Prapita Sari Dysa Handira Fadhillah Lubis, Muhammad Arif Fauzi Kurniawan Gibran, M. Khalil Haikal, Baginda Fikri Harjo, William Lutfir Rahman Harun Al Rasyid Hasibuan, Ainun Mardiah Hasibuan, Bunga Lestari Ikhwan, Ali Ilka Zufria Inneke Putri Julianti, Miranda Khairul Azis Khalil Gibran, M. Lubis, Nur Azizah M. Khalil Gibran Mhd Furqan Muhamad - Alda Muhamad Alda Muhammad Ezar Raditya Muhammad Ikhsan Muhammad Ikhsan Muhammad Siddik Hasibuan Muhammad, Faisal Nasution, Fadhilah Ramadhani Ong, Russell Pulungan, Miftahul Rizky Rambe, M. Riski Andika Rini Halila Nasution Salim Salim Siahaan, Ahmad Taufik Al Afkari SIHOMBING, JULIANA SION Suhardi Suhardi Syamia, Nanda Yusuf Ramadhan Nasution