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All Journal Edsence: Jurnal Pendidikan Multimedia Specta Journal of Technology Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) LOSARI: Jurnal Pengabdian Kepada Masyarakat JUSTIN (Jurnal Sistem dan Teknologi Informasi) Edukasi: Jurnal Pendidikan Dasar Equiva
Syamsul Mujahidin, Syamsul
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Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Transportation Other

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Efektifitas Penerapan Project Based Teaching Module dalam Mengangkat Tingkat Kreativitas Belajar Siswa Ratnaya, I Gede; Dewi, Putu Yulia Angga; Diarini, I Gusti Ayu Agung Sinta; Mujahidin, Syamsul
Edukasi: Jurnal Pendidikan Dasar Vol 4, No 2 (2023)
Publisher : STAHN Mpu Kuturan Singaraja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55115/edukasi.v4i2.3871

Abstract

The aim of this research is to see the level of effectiveness of implementing the project based teaching module on the topic of Culinary Basics. The uniqueness of this research lies in the responses of students who use the module. The module content is very interesting and varied so that it can increase student interest and stimulate creativity. Students become interested in reading because usually students only use books that are still rigid. The examples given in the module are very up to date. The method used in this research is a quasi experimental design research method with a control group and a random research sample. Data analysis techniques were carried out qualitatively (input criticism, suggestions) and quantitative (respondent assessments in the form of numbers on the questionnaire and observation sheet provided). The data collection technique used Pretest - Posttest Control Group Design which was analyzed using analysis prerequisite tests through normality tests and inferential statistics through t-tests (independent sample T-tests) to see differences in the average group learning outcomes. The population of this class is 40 people. The samples used were 30 with random sampling. Testing the effectiveness of using project based teaching module products in increasing the creativity of Dwi Tunggal Tourism Vocational School students was carried out using a two-tailed t-test. The tcount = 2.133 while the ttable value = 2.000, this shows that tcount is greater than ttable with a significance level of 0.05. So, the creativity of Dwi Tunggal Tourism Vocational School students who take part in learning using project based teaching modules is higher than the creativity of Dwi Tunggal Tourism Vocational School students who take conventional learning.
Forecasting Demand for Motorbikes at Astra Motor Balikpapan Using Support Vector Regressor Rizki, Rifaldho Muhammad; Mujahidin, Syamsul; Paninggalih, Ramadhan
Jurnal Pendidikan Multimedia (Edsence) Volume 6 No 1 (June 2024)
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/edsence.v6i1.65882

Abstract

Forecasting requests for motorbikes is a critical aspect of Astra Motor Balikpapan's operations. The Support Vector Regression (SVR) model, a method commonly used in forecasting, is particularly useful when dealing with complex data that may contain outliers and when the data is limited. This research evaluates the performance of the SVR model in estimating requested motorbikes at Astra Motor Balikpapan for 3, 6, 9, and 12 months, and analyzes the impact of parameter changes in the model evaluation. The request data for Astra Motor Balikpapan motorbikes used for five years or 60 months, which are divided into two parts: training and test data. The SVR model was built with three Kernel types: linear, polynomial, and RBF kernels. The evaluation results demonstrate the SVR model's ability to predict request motorbike with Sufficient accuracy, with minor mark errors, including an average MAE of about 0.49, RMSE of about 0.58, and R² score of about 0.99. Parameter changes also affect model evaluation, as in the case of ADV motorbike with RBF kernel; adjustment of parameter C from 0.01 to 10 results in significant accuracy, decreasing MAE from 0.36 to 0.004. This study concludes that the SVR model is an effective method for predicting motorcycle requests, with practical implications for Astra Motor Balikpapan's operations.
Penggunaan Snort dan Fail2ban sebagai IDS untuk Mengatasi Brute Force Attack dengan Notifikasi Telegram: Studi Kasus pada Institusi XYZ Abdullah, Riska Kurniyanto; Fudhail, Muhammad Thariq; Mujahidin, Syamsul
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 12, No 3 (2024)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v12i3.79617

Abstract

Dengan kebutuhan ketergantungan pada jaringan komputer meningkat, hal ini tentu menuntut sistem yang lebih aman dari segi teknologi informasi. Ancaman utama seperti Brute Force Attack bisa diatasi menggunakan firewall, tetapi firewall sering kali sulit dikonfigurasi, mahal, dan terbatas dalam pencegahan. Penelitian ini mengusulkan penggunaan Intrusion Detection System (IDS) seperti Snort dan Fail2Ban yang dikombinasikan dengan honeypot untuk meningkatkan keamanan. Melalui simulasi berbasis SPDLC dan pengujian serangan, terungkap bahwa kombinasi alat ini, jika ditempatkan dengan benar, dapat mendeteksi 100% serangan dengan waktu respons yang cepat. Walaupun demikian, konfigurasi yang salah dapat mengurangi efektivitas dan meningkatkan kemungkinan tidak ada alarm hingga 60%, dan juga dengan kejadian false alarm. Hasil menunjukkan bahwa IDS bisa menjadi solusi efektif, terutama ketika firewall yang baik tidak tersedia.
Pengembangan Deteksi Objek Dalam Rumah Bagi Tunanetra Berbasis Optimasi YOLOv8 Menggunakan Metode Ghost Module dan Attention Mechanism Mujahidin, Syamsul; Insan Kamil, Muhammad; Abdullah, Riska Kurniyanto
JURNAL FASILKOM Vol. 14 No. 3 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i3.8179

Abstract

Penyandang tunanetra sering menghadapi kesulitan dalam mobilitas sehari-hari karena keterbatasan alat bantu yang tersedia saat ini. Meskipun tongkat khusus dapat membantu dalam berjalan, namun masih sulit bagi mereka untuk mendeteksi objek secara real-time. Kemajuan dalam pengenalan objek berbasis citra, terutama dengan penggunaan machine learning, menawarkan solusi yang menjanjikan. Untuk mewujudkan sistem pendeteksi objek yang efektif, diperlukan menjalankan deteksi objek pada perangkat kecil seperti Raspberry Pi 4. Perangkat tersebut ringan dan kompatibel untuk kebutuhan mobilitas tinggi sehingga memberikan kenyamanan bagi penyandang tunanetra ketika melakukan aktivitas sehari-hari. Namun, keterbatasan kemampuan komputasi Raspberry Pi 4 menjadi tantangan, mengingat deteksi objek membutuhkan daya komputasi besar. Penelitian terbaru menunjukkan bahwa meskipun telah dilakukan optimasi pada model deteksi objek seperti YOLOv8, namun beban komputasinya masih cukup besar untuk diimplementasikan pada Raspberry Pi 4. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan model YOLOv8 versi nano dengan beban komputasi yang lebih ringan. Metode yang diusulkan melibatkan penggunaan ghost module, downsampling, dan attention mechanism. Hasil penelitian menunjukkan bahwa penggunaan ghost module dan downsampling efektif mengurangi GFLOPS model YOLOv8n dari 8.09 GFLOPS menjadi 1.77 GFLOPS, menurunkan waktu inference model hingga 57,6%, dari 401,56 ms menjadi 170,33 ms pada perangkat keras Raspberry Pi 4, tanpa mengorbankan performa deteksi. Selain itu, integrasi attention mechanism melalui attention max pooling meningkatkan akurasi model dengan peningkatan mAP sebesar 1,3% dibandingkan max pooling standar. Model ini berhasil memberikan deteksi yang lebih akurat dan efisien, menjadikannya solusi yang potensial dalam membangun sistem benam untuk membantu penyandang tunanetra dalam mendeteksi objek secara real-time.
Implementation of the Elliptic Curve Cryptography Method in Digital Image Security in Medical Images Yanuar Bhakti Wira Tama; mujahidin, syamsul
SPECTA Journal of Technology Vol. 8 No. 3 (2024): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v8i3.1253

Abstract

Digital security become increasingly important particularly in medical field as impact of patient privacy and the protection of patient data. This attempt for this research will be made to use elliptic curve cryptography to hide messages in the form of digital images using multiplication matrix modified hill chipper and count entropy and time encryption and decryption. The encryption process, which utilizes matrix multiplication, ensures that the images achieve near-ideal entropy values, close to 8, indicating a high degree of randomness and security. The result is entropy for encrypted image near 8 it means that randomness of image is quite random. Meanwhile for computational time encrypted and decrypted image for one block is around 400000 nano second for encrypt image and 1500000000 nano second for decrypt image.
Analisis Sentimen Media Sosial Twitter pada Kasus Pemberlakuan Pembatasan Kegiatan Masyarakat dengan menggunakan Metode Naïve Bayes Classifier Utomo, Muchammad Chandra Cahyo; Taukhid, Mukhamad; Mujahidin, Syamsul
Equiva Journal Vol 1 No 1 (2023)
Publisher : Jurusan Matematika dan Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/equiva.v1i1.815

Abstract

Social media is a medium used by users to introduce themselves, interact, collaborate, and share information with other users using the internet. One of the popular social media platforms in Indonesia is Twitter. Twitter is a social media that generally functions as a sender of messages which are usually referred to as tweets or tweets. One of the topics that has been widely discussed is the Policy on Enforcement of Restrictions on Community Activities (PPKM), due to the impact of an increase in cases due to the emergence of a new variant of COVID, namely the Omicron. One of the aims of this study is to find out the results of sentiment analysis regarding public opinion on the imposition of restrictions on community activities using the Naive Bayes method. There techniques machine learning for sentiment analysis, one of which is the Naive Bayes classifier, which is a machine learning technique based on probabilistic. NBC is a simple but very accurate and effective text classification method whose classification is heavily influenced by the training data process. The data used is taken via Twitter with 1594 tweets. The data set will be divided into training data and testing data by comparing 90% training and 10% testing. So, the details of the distribution of the data used in this study are 1594 tweets as training data and 160 tweets as test data. The NBC process crawling data pre-processing, data sharing, data labelling Bayes model naive classification, training data classification. The results of the analysis of public opinion sentiment regarding the imposition of restrictions on community activities using the Naive Bayes obtained a sentiment value of 71% sentiment negatif and 29% sentiment positif, accuracy value of 0.84, F1-Score 0.84, precision is 0.85, and recall is 0,84 ​.
Pengembangan Sistem Informasi Manajemen Inkubator Bisnis Teknologi di Institut Teknologi Kalimantan berbasis Website menggunakan Metode Extreme Programming Aditya, Andhika; Utomo, Muchammad Chandra Cahyo; Mujahidin, Syamsul
Equiva Journal Vol 1 No 2 (2023)
Publisher : Jurusan Matematika dan Teknologi Informasi

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

Abstract

The Kalimantan Institute of Technology has several organizations, one of which is a technology business incubator (IBT). The technology business incubator at ITK does not yet have an information system that can disseminate information regarding registration, selection and training information. IBT ITK requires media to be able to fulfill the need for information publication related to technology business incubators in ITK. Based on the previous problems, it is necessary to build a website-based management information system to facilitate the dissemination of information. The management information system that was built requires a systematic and structured method for its development, so the Extreme Programming method is used with the Laravel framework and MySQL as the database. The Extreme Programming method consists of several stages, namely observation, planning, iteration initialization, design, implementation (unit testing, code, refactor), system testing, retrospective. The results of the research show that the Extreme Programming method is capable of producing an information system that can meet the needs of stakeholders as shown from the test results.
Analisis Sentimen Isu Vaksinasi Covid-19 pada Twitter dengan Metode Naive Bayes dan Pembobotan TF-IDF Tokenisasi 1-2 Gram Hapsari, Yashmine; Mujahidin, Syamsul; Fadhliana, Nisa
SPECTA Journal of Technology Vol. 7 No. 2 (2023): SPECTA Journal of Technology
Publisher : LPPM ITK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35718/specta.v7i2.812

Abstract

The COVID-19 vaccination has been implemented to cut down the spread of the virus in society, but the status of the vaccine, which has been in the development stage, is one of the factors causing people to hesitate to vaccinate. Therefore, a sentiment analysis was carried out on the issue of COVID-19 vaccination with processes and parameters that could increase the model’s accuracy. In this study, sentiment classification was performed using the Naive Bayes method and a dataset of 5,000 tweets related to the vaccination of COVID-19. The weighting stage was applied using the TF-IDF method in which a comparison was made of the effect of using unigram, bigram and 1-2 gram tokenization on model accuracy. The results of one of the experiments with the Gaussian classifier and the ratio train: test is 7:3, the model accuracy is 67.4% for the unigram parameter, 65.5% for the bigram parameter, and 70% for the 1-2 gram parameter, where the model with the combined token is 1 -2 grams has a higher accuracy when compared to using only 1 type of token. Based on these results, it can be concluded that the combination of unigram and bigram tokenization types can provide added value to the model for classifying data, thereby increasing accuracy in analysis related to public sentiment.
Optimasi Branding Produk UMKM dan Peningkatan Popularitas Hutan Telagasari Sebagai Destinasi Wisata Lebah Madu di Kota Balikpapan Rifqiandi, Muhammad; Harli Andrika Lomo; Muhammad Noor Ihsan Fadhilah; Amalia Kartika; Rangga Hermawa; Paulus Anthony Zejlstra; Desilya Lau; Mujahidin, Syamsul; Tama, Yanuar Bhakti Wira
LOSARI: Jurnal Pengabdian Kepada Masyarakat Vol. 7 No. 1 (2025): Juni 2025
Publisher : LOSARI DIGITAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53860/losari.v7i1.410

Abstract

Telagasari Urban Forest, as a unique kerangas forest ecosystem in Kalimantan, holds significant potential in economic, ecological, and social aspects through sustainable management and honey bee cultivation. However, limited digital promotion constrains the utilization of this potential. A community engagement program in RT 45, Telagasari, Balikpapan, aimed to enhance the digital marketing skills of local MSMEs and develop the educational tourism site "Karamunting Honey Bee Tourism." Activities included training in copywriting, content strategy, and digital marketing, followed by hands-on practice, as well as promoting educational tourism for students. Results indicated that digital marketing training effectively improved participants' skills, with a satisfaction level of 87% post-program. Additionally, the development of the honey bee tourism site was supported by an informational website and QR codes on vegetation, enhancing information accessibility and tourism appeal. This program demonstrates that synergy between natural resource utilization and digital strategies can support local product branding while raising environmental conservation awareness.
Co-Authors Aditya, Andhika Amalia Kartika Desilya Lau Diarini, I Gusti Ayu Agung Sinta Fadhliana, Nisa Fudhail, Muhammad Thariq Hapsari, Yashmine Harli Andrika Lomo I Gede Ratnaya Insan Kamil, Muhammad Muhammad Noor Ihsan Fadhilah Paninggalih, Ramadhan Paulus Anthony Zejlstra Putu Yulia Angga Dewi Rangga Hermawa Rifqiandi, Muhammad Riska Kurniyanto Abdullah Rizki, Rifaldho Muhammad Taukhid, Mukhamad Utomo, Muchammad Chandra Cahyo Yanuar Bhakti Wira Tama