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APLIKASI KRIPTOGRAFI DALAM MENGAMANKAN PESAN TEKS DENGAN METODE ALGORITMA RC4 BERBASIS ANDROID Ratna Dewi; Johan Johan; Imam Muslem
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 3 No. 1 (2020): Jutikomp Volume 3 Nomor 1 April 2020
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v%vi%i.1332

Perkembangan teknologi telekomunikasi pada saat ini semakin canggih sehingga dapat membantu kegiatan sehari-hari. Salah satu contoh media komunikasi short service message (SMS), yang dapat melakukan berbagai teknik pengambilan informasi baik legal maupun illegal. Berbagai teknik perlindungan informasi yang dirahasiakan dari yang tidak berhak telah dikembangkan untuk melindungi informasi. Kriptongrafi adalah teknik penulisan pesan rahasia agar oarang tidak dapat mengetahui. Algoritma RC4 adalah salah satu teknik yang digunakan untuk membuat pesan rahasia dengan teknik enkripsi dan dekripsi pesan.Penelitian ini bertujuan utuk merancang suatu aplikasi kriptongrafi dalam pengamanan pesan teks, yang diimplementasikan pada perangkat mobile berbasis android. Aplikasi ini dikembangkan dengan aplikasi eclipsedan teknik kriptongrafinya dikembangkan dengan algoritma Rivest Code 4 (RC4).

Sistem Pendeteksi Kebocoran Gas Rumah Tangga Menggunakan Mq-2 Sensor Dan Mikrokontroler Imam Muslem R
Jurnal Tika Vol 6 No 02 (2021): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Program konversi gas bertujuan untuk melakukan kampanye penggunaan gas LPG sebagai pengganti minyak tanah sebagai bahan bakar kebutuhan dapur rumah tangga. Program Pemerintah Indonesia yang dimulai sejak tahun 2007 berjalan dengan lancar hingga saat ini. Namun dalam praktiknya, tidak sedikit masyarakat yang enggan untuk menggunakan gas LPG dikarenakan sering terjadi insiden kebocoran gas yang menyebabkan ledakan dan kebakaran yang berujung kepada kematian. Berdasarkan kondisi dan permasalahan tersebut, dalam penelitian ini penulis mencoba mengembangkan suatu prototype yang mampu mendeteksi potensi kebocoran gas. Tujuan dari prototype ini yaitu untuk memberikan notifikasi kepada user saat terjadi kebocoran gas, sehingga langkah preventif seperti tidak menghirupkan lampu dan perangkat elektronik lain, tidak memantik api, membuka pintu dan jendela ruangan dapat dilakukan demi mengantisipasi terhirupnya gas dan terjadi ledakan serta kebakaran. Prototype sistem pendeteksi kebocoran gas ini dikembangkan dengan menggunakan metode pengembangan prototype. Sistem ini menggunakan sensor MQ-2 berbahan utama Sn02 untuk mengumpulkan data kondisi konsentrasi gas di udara. Prototype ini juga menggunakan arduino sebagai alat pemroses data serta menggunakan display LCD 16x02 dan modul suara sebagai aktuator yang berfungsi untuk memberikan notofikasi kebocoran gas kepada pengguna. Berdasarkan hasil implementasi, didapatkan bahwa sistem yang dikembangkan berjalan dengan baik dengan fungsi sesuai dengan yang diinginkan. Untuk pengembangan kedepan, disarankan menggunakan notifikasi berbasis Internet of Things, seperti notifikasi yang dikirim ke ponsel cerdas pengguna sehingga pengguna tau bahwa sedang terjadi kebocoran gas meskipun pengguna tidak berada di tempat

Penetapan Klaster Siswa Unggul Dengan Menggunakan Algoritma Roc-Smarter Dedy Armiady; Imam Muslem R.
Jurnal Tika Vol 7 No 2 (2022): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

The development of the IT world today has penetrated into all sectors of human life, one of which is the education sector. However, the implementation that occurs in the field has not been fully maximized, considering that there are still educational institutions that still seem half-hearted in implementing information technology. This happens due to various problems, such as lack of funds for IT development, IT infrastructure that is still minimal, especially for educational institutions located far from urban areas, human resources that are still lacking in skills and knowledge and various factors. Many efforts can be taken to improve this, one of which is as carried out in this study. The focus of this research is to develop an application by applying the ROC-SMARTER method so that it can be used by MTsN 2 Bireuen in determining the superior student cluster. From the implementation of the research using the ADDIE approach (Analyze, Design, Development, Implementation, and Evaluation) it was found that the case of determining the cluster of superior students at MTsN 2 Bireuen could be solved effectively and efficiently where previously it was done using manual and traditional methods

Sistem Informasi Kalkulasi Zakat Pada Kantor Baitul Mal Kabupaten Bireuen Berbasis Android Sri Winar; Erifki Rizki Putra; Imam Muslem R.
Jurnal Tika Vol 7 No 3 (2022): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

The technology that is currently developing at its fastest pace is information and telecommunications technology, which presents a wide selection of forms and literature from various sources by searching for data to add insight in the development of applications that are made. The calculation of zakat basically has provisions and formulas that have been determined based on the hadith and Al-Qur'an, so to improve services and make it easier for the community in terms of determining and calculating zakat it is necessary to develop a calculation system so that people can easily determine the amount of zakat that must be issued by each individual zakat payer. In this research, the development of the Zakat Calculation Information System uses the php programming language which has been bundled in the Eclipse application. The resulting application will be able to help society in general and especially Android-based smartphone users in terms of calculating zakat including zakat fitrah to zakat mal. Zakat is wealth that must be issued if it meets the conditions determined by religion, and is distributed to people who have been determined as well, namely the eight groups who are entitled to receive zakat. In this study the method that will be used to help analyze problems and deal with problems is field research and literature review. This application has complete zakat calculations which include Zakat Fitrah and Zakat Maal (Zakat Treasure) and this application can assist users in calculating zakat independently and knowing the function of each zakat

E-Absensi Mahasiswa Fakultas Ilmu Komputer Universitas Almuslim Berbasis Web Fitriani Fitriani; Imam Muslem R
Jurnal Tika Vol 5 No 3 (2020): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

E-Absensi merupakan hal yang wajib dilakukan untuk mahasiswa. Dalam melakukan absensi masih menggunakan cara manual. Oleh karena itu, diperlukan suatu sistem absensi mahasiswa yang dapat melakukan pendataan dan pengelolaan data agar dapat dilakukan secara cepat, efisien, dan akurat. Pembuatan sistem absensi mahasiswa ini dilakukan dengan cara pengumpulan data, analisa sistem, perancangan sistem, dan implementasi sistem. Sistem ini dibuat dengan menggunakan bahasa pemrograman PHP dan MySQL untuk pengelolaan database. Sebagai hasil dari Skripsi ini adalah dibuatnya aplikasi berbasis web Sistem Informasi Absensi Mahasiswa Berbasis PHP Menggunakan web yang memiliki fasilitas seperti: manajemen data mahasiswa, manajemen data dosen, manajemen data mata kuliah, manajemen data absensi, dan laporan rekap absensi mahasiswa. Dengan adanya aplikasi ini, diharapkan proses absensi akan lebih efisien dan dapat dipantau dengan mudah oleh dosen dan oleh Ka.Prodi

Klasifikasi Citra Ikan Menggunakan Algoritma Convolutional Neural Network dengan Arsitektur VGG-16 Imam Muslem R; Teuku Muhammad Johan; Luthfi
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1209

The development of technology in the field of image processing has inspired this research which aims to overcome challenges in classifying fish images using a Convolutional Neural Network (CNN) based approach. In this research, we utilize the VGG-16 architecture, a CNN model that has been proven capable of retrieving important features from images with significant depth. The dataset consists of 1088 fish images divided into four classes: Bangus, Glass Perchlet, Gold Fish, and Gourami. The initial process involves feature extraction via image embedding using the VGG-16 architecture. Next, a classification model is built using the Orange Data Mining tool. The experimental results show that this approach is able to provide good classification performance with significant accuracy in recognizing different fish species. The use of VGG-16 enables powerful and complex feature extraction, and experimental results show that this approach achieves a training accuracy of 96.2%. Furthermore, when the classification process uses data testing, this method produces an accuracy of 99.5%. This finding shows the great potential of the Convolutional Neural Network in overcoming the challenge of classifying fish images with very satisfactory results, which can be applied in various fields including marine science and remote sensing.

Image Classification pada Kasus American Sign Language Menggunakan Support Vector Machine Zulkifli; Imam Muslem R
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1242

This study aims to develop and test a hand drawing classification model using the Support Vector Machine (SVM) algorithm to identify digits in American Sign Language (ASL). This method utilizes image processing techniques for extracting relevant features from hand images and SVM's ability to separate complex patterns. The training and test data consists of hand images representing the digits 0 through 9 in ASL. Tests are performed using test data that the model has never seen during training, to measure the performance and validity of the model in real-world situations. The results showed that the developed classification model was able to recognize digits in ASL with satisfactory accuracy, where the accuracy of the developed model was 99.8% with a loss of 0.018. Error analysis provides insight into situations that confuse the model and the potential for further improvement. The use of SVM in this ASL classification opens up new opportunities in strengthening communication accessibility for the hand sign language community. In conclusion, this model has the potential to make a positive contribution in facilitating communication and inclusion for deaf communities.

Klasifikasi Kualitas Buah Pisang Berdasarkan Citra Buah Menggunakan Stochastic Gradient Descent Dedy Armiady; Imam Muslem R
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 2 (2023): Oktober 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i2.1243

Banana fruit quality is an important factor in meeting consumer demand and maintaining product quality in the supply chain. The development of automatic methods for classifying the quality of bananas is becoming increasingly important as the worldwide consumption of bananas grows. In this study, we propose a classification method for banana fruit quality using the Stochastic Gradient Descent (SGD) algorithm. This study aims to evaluate the performance of SGD in classifying the quality of bananas and to analyze the effect of selecting hyperparameters on the classification results. The dataset collected is a dataset containing pictures of bananas with various levels of ripeness and conditions. This dataset is used to train and test a classification model using SGD. During the experiment, hyperparameter tuning processes such as learning rate, momentum, and batch size were carried out to understand how these parameters affect the performance of SGD in classification. We report the results of evaluating the classification based on accuracy and analyze changes in performance with variations in hyperparameters. The results of this study indicate that SGD has the potential to classify the quality of bananas, where the optimal SGD model obtained a classification accuracy of 99.9%, compared to the standard SGD model which only obtained a classification accuracy of 94.7%.

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