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All Journal Jurnal Manajemen Bisnis PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnas Nasional Teknologi dan Sistem Informasi Jurnal ULTIMA InfoSys JURNAL PENDIDIKAN TAMBUSAI EDUKATIF : JURNAL ILMU PENDIDIKAN JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran Jurnal Manajemen Informatika Jayakarta Journal of Students‘ Research in Computer Science (JSRCS) International Journal of Regional Innovation Brilliance: Research of Artificial Intelligence Jurnal Pendidikan Vokasi Raflesia Jurnal Desain Komunikasi Visual Nirmana Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Digital Transformation Technology (Digitech) International Journal of Information Technology and Computer Science Applications (IJITCSA) Jurnal Guru Komputer Journal of Computer Science Contributions (Jucosco) Jurnal PETISI (Pendidikan Teknologi Informasi) Orbit : Jurnal Ilmu Multidisiplin Nusantara Jurnal Komtika (Komputasi dan Informatika)
Rasim, Rasim
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Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Social Sciences Other

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SISTEM PAKAR BERBASIS WEB DIAGNOSIS KERUSAKAN PRINTER MENGGUNAKAN ALGORITMA NAIVE BAYES Rasim, Rasim; Handayani, Dwipa; Lubis, Hendarman; Rawinto, Irsyad
Jurnal Manajamen Informatika Jayakarta Vol 5 No 3 (2025): Jurnal Manajemen Informatika Jayakarta ( JMI Jayakarta)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v5i3.2090

Abstract

Penelitian ini dilatarbelakangi oleh proses diagnosa kerusakan printer yang masih manual di WW Print Solution, sebuah pusat layanan perbaikan printer, yang menyebabkan potensi ketidakakuratan dan keterlambatan perbaikan. Untuk mengatasi permasalahan tersebut, penelitian ini bertujuan merancang dan mengimplementasikan sistem pakar berbasis web yang mampu mendiagnosa kerusakan printer menggunakan algoritma Naive Bayes. Metode pengembangan Waterfall diterapkan secara terstruktur, mencakup analisis kebutuhan, perancangan sistem menggunakan Unified Modeling Language (UML), serta desain basis data. Implementasi dilakukan dengan bahasa pemrograman PHP dan MySQL, dan pengujian sistem menggunakan metode Black Box Testing untuk memvalidasi fungsionalitasnya. Hasil penelitian menunjukkan bahwa sistem pakar yang dibangun berhasil mendiagnosa kerusakan printer secara otomatis sesuai dengan perhitungan probabilitas Naive Bayes. Aplikasi ini terbukti mampu mempercepat proses identifikasi masalah, mengurangi ketergantungan pada pengalaman teknisi, dan meningkatkan efisiensi operasional. Dengan demikian, sistem ini memberikan solusi efektif untuk diagnosa kerusakan printer yang lebih cepat dan akurat, serta meningkatkan kualitas layanan di WW Print Solution. Kata kunci: Sistem Pakar, Diagnosa Printer, Naive Bayes, Web, Waterfall
How Microlearning Can Benefit Education: A Study of Factors and Trends in the Use of Microlearning Ranggana, Alfaza; Rasim, Rasim; Megasari, Rani
EDUKATIF : JURNAL ILMU PENDIDIKAN Vol 7, No 5 (2025): Oktober
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/edukatif.v7i5.8558

Abstract

Microlearning has become one of the approaches that has become increasingly in demand in the last two decades along with the increasing need for flexible and digital technology-based learning. This research aims to define the concept of microlearning and identify research trends and factors that drive its implementation. The method used is a bibliometric analysis of microlearning-themed publications obtained from the ScienceDirect database from the initial appearance of the term until 2024. The analysis was carried out based on three main aspects, namely the frequency of publications, the number of citations, and the network of co-emergence and co-authorship. The results of the study show a significant increase in the number of microlearning-related publications over the past two decades. The publications with the highest citations were mostly from the pre-COVID-19 pandemic period, while 99% of documents did not show a strong pattern of authorship collaboration. In addition, microlearning is defined through three main factors, namely mobile device use, social connectedness, and time constraints. These findings confirm that research on microlearning remains relevant and has the potential to be an important foundation for the development of digital learning strategies in the future
ANALISIS KOMPARATIF ALGORITMA MACHINE LEARNING UNTUK MENDETEKSI MALICIOUS URL BERBASIS FITUR GANDA Alexander, Allan Desi; Warta, Joni; Lubis, Hendarman; Mahbub, Asep Ramdhani; Rasim, Rasim
Jurnal Manajamen Informatika Jayakarta Vol 5 No 3 (2025): Jurnal Manajemen Informatika Jayakarta ( JMI Jayakarta)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jmijayakarta.v5i3.2101

Abstract

Malicious URL Detection (MUD) merupakan komponen esensial dalam pertahanan siber, mengingat kerugian finansial global yang disebabkan oleh phishing, penyebaran malware, dan serangan botnet IoT. Pendekatan tradisional seperti blacklisting terbukti tidak efektif melawan URL yang baru dibuat atau polymorphic. Penelitian ini menyajikan analisis komparatif ekstensif dari tiga kelas algoritma utama: Ensemble Learning (Random Forest/RF), Kernel Methods (Support Vector Machine/SVM), dan Deep Learning (DL), dalam mengklasifikasikan URL yang berpotensi berbahaya. Data yang digunakan bersumber dari repositori publik URLhaus, yang sangat fokus pada malware download, khususnya kampanye botnet Mozi dan Mirai. Metodologi studi ini menekankan pada rekayasa fitur multi-modal, yang menggabungkan fitur leksikal, berbasis host/domain, dan fitur berbasis metadata (tag malware). Kinerja model dievaluasi menggunakan metrik yang sensitif terhadap keamanan siber, yaitu Presisi, Recall, dan F1-Score, untuk meminimalisir False Negatives. Hasil analisis memperlihatkan bahwa meskipun model DL mencapai akurasi tertinggi, Random Forest menawarkan keseimbangan optimal antara kinerja deteksi yang kuat dan efisiensi komputasi, menjadikannya ideal untuk implementasi real-time dalam sistem deteksi ancaman. Malicious URL Detection (MUD) is an essential component of cyber defense, given the global financial losses caused by phishing, malware distribution, and IoT botnet attacks. Traditional approaches such as blacklisting have proven ineffective against newly created or polymorphic URLs. This study presents an extensive comparative analysis of three main classes of algorithms: Ensemble Learning (Random Forest/RF), Kernel Methods (Support Vector Machine/SVM), and Deep Learning (DL), in classifying potentially malicious URLs. The data used is sourced from the public repository URLhaus, which focuses heavily on download malware, specifically the Mozi and Mirai botnet campaigns. The study's methodology emphasizes multi-modal feature engineering, combining lexical, host/domain-based, and metadata-based features (malware tags). Model performance is evaluated using cybersecurity-sensitive metrics, namely Precision, Recall, and F1-Score, to minimize False Negatives. The analysis results show that although the DL model achieves the highest accuracy, Random Forest offers an optimal balance between strong detection performance and computational efficiency, making it ideal for real-time implementation in threat detection systems.
Sentiment Analysis of Indonesian Presidential Candidate Before and After the Election Sofyan, Muhammad Hilmy Rasyad; Zulkifli, Akmal; Rasim, Rasim
ULTIMA InfoSys Vol 15 No 2 (2024): Ultima Infosys: Jurnal Ilmu Sistem Informasi
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/si.v15i2.3689

Abstract

As one of the world's democratic countries, Indonesia has just held a general election to choose its next president. The development of the times encourages presidential candidates to make a new breakthrough, such as the use of social media as campaign media. Currently, X is a popular social media used as a campaign medium. On X, users are given the freedom to share their opinions. Various opinions related to one of the presidential candidates were used by the researchers to collect data using the data crawling method. The results of the data crawling are first processed with different methods in the pre-process to make the data ready for use. Some of the steps that need to be taken in the pre-process are such as cleaning, normalisation, stopword, tokenisation, stemming and translation processes. All the processes carried out in the pre-process stage will produce mature or usable data. The mature data is then classified into positive, negative and neutral using the Naí¯ve Bayes classification method. Once the classification is complete, the results are evaluated in terms of sentiment towards one of the presidential candidates. The results of a total of 2117 data collected from 01 February 2024 to 20 May 2024, there are 390 data used for the pre-presidential election sentiment analysis and 1618 data used for the post-presidential election sentiment analysis. Both before and after the presidential election was held, this presidential candidate had more positive sentiments than the negative and neutral sentiments he received from the public.
Pelatihan CorelDraw Pada Santri Yayasan Yatim Piatu dan Dhuafa Al-Ikhlas Bekasi Khaerudin, Muhammad; Rasim, Rasim
Journal Of Computer Science Contributions (JUCOSCO) Vol. 2 No. 1 (2022): Januari 2022
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/n7acjz74

Abstract

The pandemic condition opens up opportunities for teenagers to do business. In this condition, it is expected that teenagers can use their time positively and productively. Mental readiness and skills need to be prepared before someone enters the world of work. Meanwhile applications in the field of information technology have a major impact in various fields of life, one of which is in the creative industries such as advertising, billboards, graphic design and digital image processing. One of the support skills for the younger generation. The method of community service carried out by a team of Bhayangkara Jakarta Raya University lecturers this time is in the form of graphic design skills training using computers and using CorelDraw and Photoshop software. This activity aims to improve the knowledge and skills of youth in improving the quality of their ability to create attractive graphic designs so that participants can compete to meet the demand for job opportunities and also towards entrepreneurship. Mareri given to participants include making and completing product designs for advertising or printing needs. The results of the graphic design skills training activity show that participants can design logos, business cards, invitations, flyers, banners, banners and other forms of advertising.
Energy Management of a Low-Cost Power Meter using ESP8266 and PZEM-016 Syafri Syamsudin, Muhammad; Septem Riza, Lala; Rasim, Rasim
International Journal of Regional Innovation Vol. 4 No. 1 (2024): International Journal of Regional Innovation
Publisher : Inovbook Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52000/ijori.v4i1.97

Abstract

The burgeoning significance of the Internet of Things (IoT) lies in its capacity to configure interconnected environments and facilitate human-object interactions through collaborative services. This study proposes an efficient energy management approach leveraging cost-effective technologies like the ESP8266 microcontroller and the PZEM-016 Modbus RTU energy monitoring module. Tailored towards wireless connectivity, this solution is purposefully crafted for diverse sectors operating within constrained budgets, obviating the need for intricate infrastructure. A systematic deployment of the forward engineering research methodology is undertaken to discern the requisites and hurdles inherent in energy management. The amalgamation of ESP8266, PZEM-016, and the MQTT protocol, with RabbitMQ serving as a message broker, forges an efficacious framework for inter-device information exchange. The solution's instantiation entails the interconnection of power meter devices using the MQTT protocol, transmitting data in JSON format. The PZEM-016 sensor constitutes the crux, adeptly measuring voltage, current, frequency, and power with precision. Furthermore, the solution encompasses a prototype Smart Meter fortified with Wi-Fi connectivity to the internet, thus extending network coverage ubiquitously. Economic scrutiny reveals that the resultant power meter device costs less than 100 USD, competitively positioning it against analogous market offerings. This economically optimized design advocates for widespread adoption across multifarious sectors constrained by budgetary limitations, assuaging the complexities inherent in energy management through a trifecta of efficiency, reliability, and affordability.
Analisis Perubahan Sentimen Publik di Media Sosial X terhadap Konflik Palestina-Israel Menggunakan Model IndoBERT Al-Kadzim, Muhammad Ghiyats; Rasim, Rasim; Herbert, Herbert
Digital Transformation Technology Vol. 4 No. 2 (2024): Periode September 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i2.5312

Abstract

Media sosial, khususnya X (sebelumnya Twitter), telah menjadi platform utama bagi masyarakat Indonesia untuk mengekspresikan pendapat mereka mengenai berbagai isu global, termasuk konflik Palestina-Israel yang kembali memanas. Tantangan yang dihadapi adalah melihat perubahan sentimen yang terjadi pada masyarakat Indonesia dan penyebab perubahan sentimen itu bisa terjadi. Meningkatnya perdebatan yang terjadi di X telah menggerakkan masyarakat Indonesia untuk terlibat dalam diskusi-diskusi mengenai konflik ini. Untuk mengatasi tantangan ini, penelitian ini mengadopsi pendekatan analisis sentimen menggunakan Natural Language Processing (NLP) dengan memanfaatkan model pre-trained IndoBERT, yang telah disesuaikan untuk memahami bahasa Indonesia.  Model IndoBERT yang telah di pre-train akan masuk ke dalam fase fine-tuning. Model ini digunakan untuk mengklasifikasikan sentimen ke dalam kategori positif, negatif, atau netral. Model ini menghasilkan nilai terbaik weighted avg pada batch size 16 dan epoch 5 dengan nilai accuracy 0.73, precision 0.73, recall 0.73, dan f1-score 0.73. Model yang telah di fine-tune digunakan untuk prediksi tweet yang belum dilabeli. Hasil prediksi divisualisasikan untuk melihat perubahan sentimen yang terjadi di setiap bulannya dan di analisis sehingga mendapatkan kesimpulan bahwa lonjakan dan fluktuasi sentimen publik terhadap konflik Palestina dan Israel sangat terkait dengan intensitas kekerasan seperti penyerangan dan banyaknya korban jiwa serta keputusan politik yang menjadi perhatian bagi masyarakat Indonesia.
Analisis Sentimen Mengenai Gangguan Bipolar Pada Twitter Menggunakan Algoritma Naïve Bayes Silaen, Oriza Sativa Dinauni; Herlawati, Herlawati; Rasim, Rasim
Jurnal Komtika (Komputasi dan Informatika) Vol 6 No 2 (2022)
Publisher : Universitas Muhammadiyah Magelang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31603/komtika.v6i2.8198

Abstract

Bipolar disorder is one of the world's most common mental health disorders. To find out public sentiment regarding bipolar disorder, sentiment analysis is carried out through social media to analyze positive or negative sentiments with the aim of maintaining positive sentiment towards the problem of bipolar disorder. Twitter is a social media that is often used to exchange information, discuss, and even express emotions. The emotions of Twitter users can be called sentiment. Sentiment analysis is also carried out to see opinions or tendencies towards an opinion. Opinion tendencies can be in the form of positive or negative sentiments. The data used in this study uses the bipolar keyword. There are 2177 tweets data that were successfully obtained in the crawling process using API key access from Twitter developers, after which the data will be processed using preprocessing. The comparison of the presentations obtained is 70.92% expressing a negative opinion and 29.08% expressing a favorable opinion. The analysis results in this study using the nave Bayes algorithm is with an accuracy value of 92.110092%.
Implementasi Algoritma Apriori pada Sistem Informasi Penjualan Web Pujiono, Krisna Dimas; Mugiarso; Handayani, Dwipa; Rasim, Rasim
Journal of Students‘ Research in Computer Science Vol. 6 No. 2 (2025): November 2025
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/kjhjrc12

Abstract

This study focuses to implementing a web-based sales information system leveraging the Apriori algorithm to analyze consumer purchasing patterns at PT. Mura Mitra Sejati. Adopting the Waterfall development methodology, the project progressed systematically through the analysis, design, implementation, testing, and maintenance stages.The system was developed using a native PHP architecture based on the MVC pattern, supported by a MySQL database and Bootstrap for the front-end. Key functionalities of the system include sales transaction recording, real-time inventory management, and powerful association rule mining. Comprehensive black-box testing across all modules—Login, Stock Management, Transactions, Apriori Analysis, and Reporting—confirmed the intended performance of every system function, achieving a 100% success rate.The Apriori algorithm effectively identified strong association rules from 10 transaction datasets, notably revealing the frequent co-purchase of White Paint and 1-inch Brushes, with 40% support and 80% confidence, respectively. Ultimately, the resulting system delivers an efficient, well-structured, and data-driven solution that significantly improves sales management and supports strategic decision-making.
RANCANG BANGUN SISTEM INFORMASI MONITORING DAN ANALISIS KINERJA PENJUALAN MENGGUNAKAN METODE RAPID APPLICATION DEVELOPMENT ( RAD ) Rasim, Rasim; Mugiarso, Mugiarso; Handayani, Dwipa; Lubis, Hendarman
Journal of Information System, Informatics and Computing Vol 9 No 2 (2025): JISICOM (December 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v9i2.2078

Abstract

The sales achievement monitoring process at CV Pakar Prima Buana, which relies on Microsoft Excel, has led to issues such as data duplication and inconsistency due to the manual filtering and target distribution performed by team leaders in a company with over 500 employees. This study aims to develop a web-based information system designed to simplify, accelerate, and streamline the monitoring of each salesperson’s achievement performance. The Rapid Application Development (RAD) methodology was adopted for its fast and adaptive development cycle, consisting of three main phases: Requirements Planning, Design Workshop, and Implementation. The system was developed using PHP, the CodeIgniter framework, and a MySQL database. The black-box testing results demonstrate that all system functions operate as expected. The resulting system successfully automates the calculation and reporting of sales achievements, eliminates data duplication, and provides structured, accurate, and timely information to support managerial decision-making. Keywords: Information System, Sales Achievement, Rapid Application Development, CodeIgniter, Black-box Testing
Co-Authors ACHMAD FAUZI Agus Hidayat Al-Kadzim, Muhammad Ghiyats Alexander, Allan D Anisyah, Ani Baszliah Nursabrina Bayu Wicaksono Dwipa Handayani Eka Fitrajaya Rahman Enjang Ali Nurdin Erlangga Erlangga Fajar Ramadhan Fauzi, Indah Resti Fazira, Ira Fried Sinlae Ghaitsa Zahira Shaffa Hambali, Yudi Ahmad Herbert Siregar Herlawati Herlawati Isya, Nadhief Athallah Joniwarta Judie, Rizky Rachman Juliano, Aryo Julianti, Sukma Junaeti, Enjun Khaairi, Mochamad Lavianti, Desi Lubis, Hendarman Mahbub, Asep Ramdhani Mahphoth, Mohd Halim bin Mugiarso Mugiarso, Mugiarso Muhamad Firdaus Muhammad Khaerudin Muhammad Yasir Munir Munir, Munir Nailah Nurul Qalbina Natasya Regita Gandawidjaya Nursalman, Muhammad Nusratullo, Samialloi Piantari, Erna Prima Dina Atika Pujiono, Krisna Dimas Puspo Dewi Dirgantari Putro, Budi Laksono Ranggana, Alfaza Rani Megasari Rawinto, Irsyad Robertus Suraji Rosa, Elisa Rozi, Muhammad Fahru Sari, Fitra Bona Septem Riza, Lala Shafarin, Anti Nuraulia Silaen, Oriza Sativa Dinauni Siregar, Herbert SITI SETIAWATI Sofyan, Muhammad Hilmy Rasyad Sugiyatno Sugiyatno Sumitra, Desfasa Ilham Syafri Syamsudin, Muhammad Ully, Rona Wawan Setiawan Wihardi, Yaya Wijati, Damar Zulkifli, Akmal