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All Journal Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JPM (Jurnal Pemberdayaan Masyarakat) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL PENGABDI JMM (Jurnal Masyarakat Mandiri) JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Teknologi Informasi dan Multimedia Jurnal SASAK : Desain Visual dan Komunikasi Jurnal Bumigora Information Technology (BITe) REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Soft Computing Exploration Jurnal Pengabdian Masyarakat Indonesia Media Jurnal Informatika Jurnal Aplikasi Teknologi Informasi dan Manajemen (JATIM) ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Interaktif: Warta Pengabdian Pendidikan (JIWPP) Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) MATRIX : JURNAL MANAJEMEN TEKNOLOGI DAN INFORMATIKA Paradigma Journal of Engineering, Technology and Computing (JETCom) INCOME: Indonesian Journal of Community Service and Engagement Insand Comtech : Information Science and Computer Technology Journal Journal of Artificial Intelligence and Digital Business Bakti Sekawan : Jurnal Pengabdian Masyarakat Journal Of Artificial Intelligence And Software Engineering Prosiding Seminar Nasional CORISINDO
Hammad, Rifqi
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Using a Partition System to Improve the Performance of the Apriori Algorithm in Speeding Up Itemset Frequency Search Process Syahrir, Moch; Hammad, Rifqi; Abd. Latif, Kurniadin; Rosanensi, Melati
Sistemasi: Jurnal Sistem Informasi Vol 13, No 1 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i1.3610

Abstract

The apriori algorithm uses minimum support and minimum confidence to determine appropriate itemset rules for decision making. The problem faced in this research is how to improve the performance of the a priori algorithm in the process of searching for itemset frequencies using data partition techniques, and be able to produce optimal and consistent rules. To overcome this problem, the author implemented the a priori method and partition system to improve the performance of the a priori algorithm for the itemset frequency search process by taking public data in the form of supermarket transaction data. In this research, the performance of the a priori algorithm was tested with and without a partition system. The data used in this research consists of 350 transaction data from 1784 records with a 4-itemset pattern, minimum support value of 20% and minimum confidence of 0.5 with the best standard rules for determining minimum confidence of 0.8. Based on this research carried out, the research results obtained are that for comparison of time and memory usage the apriori algorithm with a partition system is much faster than the apriori algorithm without a partition system, while memory usage is relatively less for the apriori algorithm with the system than the apriori algorithm without a partition system.
Klasterisasi Pemain PUBG Mobile dengan Algoritma K-Modes Clustering pada Mayoung Universe Harisandi, Lalu Ilham; Sujaka, Tomi Tri; Hammad, Rifqi
CORISINDO 2025 Vol. 1 (2025): Prosiding Seminar Nasional CORISINDO 2025
Publisher : CORISINDO 2025

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/corisindo.v1.5520

Abstract

Mayoung Universe merupakan penyelenggara turnamen Esport dan Leader komunitas yang aktif mengadakan turnamen PUBG Mobile di wilayah Nusa Tenggara Barat. Dari sekian banyak turnamen yang telah di selenggarakan akan tetapi Mayoung Universe mengalami kesulitan dalam menentukan pola penyelenggaraan turnamen PUBG Mobile untuk kedepannya, Selain itu, Terdapat data pendaftaran pemain berjumlah 401 data, serta didominasi oleh atribut yang bertipe kategorik Oleh sebab itu, menerapkan algoritma K-Modes Clustering sangatlah cocok di terapkan untuk mengatasi permasalahan serta untuk menangani data kategorik. Algoritma K-Modes merupakan pengembangan dari K-Means yang dirancang untuk mengelompokkan data kategorikal Hasil evaluasi dari Elbow Method terdapat jumlah k optimal yakni 4,6 dan 8, Hasil evaluasi dari Silhouette Coefficient jumlah k terbaik sebanyak k=6, dengan skor=0,249. Sedangkan evaluasi dari Dunn index dan DBI, k terbaik terdapat pada k=3, skor dari Dunn index yaitu 0,643, dan skor DBI yakni skor 2,395. Hasil dari visualisasi jumlah k=6 dan 3, terdapat jumlah objek terbanyak pada cluster 1 sebanyak 197 untuk k=6, dan 231 untuk k=3. Untuk mengatasi permasalahan bagaimana menentukan pola turnamen PUBG Mobile di Nusa Tenggara Barat, pihak Mayoung Universe hendaknya memperhatikan cluster 1 dari 3 dan 6 jumlah k terbaik dengan segala bentuk karakteristiknya. Sebagai gambaran, dalam menyelenggarakan turnamen PUBG Mobile kedepannya. 
Perbandingan Algoritma XGBoost dan Random Forest dalam Klasifikasi Surat Masuk Pemerintahan Hidayat, Fadila Ananda Kartika; Sulistianingsih, Neny; Hammad, Rifqi
RIGGS: Journal of Artificial Intelligence and Digital Business Vol. 4 No. 4 (2026): November - January
Publisher : Prodi Bisnis Digital Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/riggs.v4i4.5044

Abstract

Pengelolaan surat masuk pada lingkungan pemerintahan daerah berperan penting dalam mendukung efektivitas administrasi dan pengambilan keputusan oleh pimpinan daerah. Surat masuk merupakan salah satu bentuk komunikasi resmi yang harus dikelola secara sistematis agar informasi yang terkandung di dalamnya dapat segera ditindaklanjuti sesuai dengan bidang administrasi terkait. Volume surat yang tinggi sering menimbulkan berbagai kendala, terutama dalam proses identifikasi isi surat dan pengelompokan berdasarkan bidang administrasi yang berwenang. Kondisi tersebut berpotensi menyebabkan keterlambatan disposisi, kesalahan pengelompokan surat, serta menurunnya kualitas pelayanan administrasi apabila masih dilakukan secara manual. Penelitian ini bertujuan untuk membandingkan kinerja dua algoritma machine learning, yaitu Extreme Gradient Boosting (XGBoost) dan Random Forest, dalam melakukan klasifikasi surat masuk kepala daerah secara otomatis dan terstruktur. Data yang digunakan dalam penelitian ini meliputi arsip surat masuk pemerintah daerah periode 2021–2022 serta hasil ekstraksi dokumen surat berbentuk PDF yang diperoleh dari aplikasi persuratan SRIKANDI menggunakan pustaka pdfplumber untuk menghasilkan data teks yang dapat diolah.. Tahapan penelitian mencakup proses pra-pemprosesan data, pembagian data menjadi data latih dan data uji, pelatihan model, serta evaluasi kinerja model menggunakan indikator accuracy, precision, recall, dan F1-score. Berdasarkan hasil pengujian, algoritma XGBoost menunjukkan performa yang lebih unggul dengan nilai akurasi sebesar 81,87% dan F1-score 82,00%, dibandingkan Random Forest yang hanya mencapai akurasi 76,00% dan F1-score 76,03%. Dengan demikian, XGBoost dinilai lebih efektif untuk mendukung proses klasifikasi surat dalam implementasi e-government di lingkungan pemerintahan daerah.
Optimalisasi Pemanfaatan Platform Digital dalam Merancang Identitas Produk dan Pemasaran Digital Madu Trigona Lebah Prawira Desa Sokong Lombok Utara Tri Sujaka, Tomi; Abd Latif, Kurniadin; Syahrir, Moch; Hammad, Rifqi; Bukran
INCOME: Indonesian Journal of Community Service and Engagement Vol 4 No 4 (2025)
Publisher : EDUPEDIA Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56855/income.v4i4.1907

Abstract

Kelompok Ternak Madu Trigona Lebah Prawira merupakan kelompok ternak yang ada pada wilayah Desa Sokong Kecamatan Tanjung Kabupaten Lombok Utara. Permasalahan utama yang dihadapi mitra meliputi rendahnya pemanfaatan media digital, belum terbentuknya identitas merek yang kuat, serta keterbatasan pengetahuan dan keterampilan dalam pemasaran digital. Kegiatan ini bertujuan untuk mengoptimalkan pemanfaatan platform digital dalam mendukung branding dan pemasaran produk madu trigona. Metode Pelaksanaan kegiatan meliputi sosialisasi, pelatihan digital branding dan pemasaran digital, penerapan solusi pemasaran digital, dan pendampingan serta evaluasi. Hasil kegiatan menunjukkan adanya peningkatan pemahaman dan keterampilan mitra dalam membangun identitas merek, menghasilkan konten promosi yang lebih menarik dan konsisten, serta memanfaatkan media sosial dan marketplace untuk memperluas jangkauan pemasaran. Pembahasan menunjukkan bahwa penerapan strategi branding dan pemasaran digital mampu meningkatkan visibilitas produk, interaksi dengan konsumen, serta potensi peningkatan nilai jual madu trigona. Optimalisasi pemanfaatan platform digital melalui pendekatan pelatihan dan pendampingan terbukti efektif dalam meningkatkan daya saing dan keberlanjutan usaha madu trigona di era digital.
Rice Leaf Disease Classification Based on ResNet50 and MobileNetV3 Feature Extraction Using Random Forest Pratama, Gede Yogi; Husaini, Rahayun Amrullah; Nasri, Muhammad Haris; Hammad, Rifqi
Media Jurnal Informatika Vol 17, No 2 (2025): Media Jurnal Informatika
Publisher : Teknik Informatika Universitas Suryakancana Cianjur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/mji.v17i2.5939

Abstract

Diseases in rice plants are one of the main factors contributing to decreased agricultural productivity. Early and accurate disease identification is crucial to support effective decision-making in plant disease management. This study aims to compare the performance of deep learning models based on Convolutional Neural Networks (CNN), namely ResNet50 and MobileNetV3, as well as their integration with the Random Forest (RF) algorithm for rice leaf disease classification. The dataset used consists of rice leaf images categorized into several disease classes. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics with a macro-average approach. The results show that the standalone ResNet50 and MobileNetV3 models achieved accuracies of 62.5% and 65.7%, respectively, with macro F1-scores below 0.65, indicating moderate classification performance. However, combining CNN models with Random Forest significantly improved classification performance. The ResNet50 + RF model achieved an accuracy of 99.6%, while the MobileNetV3 + RF model attained the highest accuracy of 99.8%, along with equally high macro-averaged precision, recall, and F1-score values. These findings demonstrate that integrating CNN-extracted features with the Random Forest algorithm enhances the model’s ability to distinguish disease classes more accurately and consistently. Therefore, the hybrid CNN–Random Forest approach shows strong potential as an effective solution for image-based rice plant disease detection systems.
Intervensi Edukasi Digital Marketing untuk Peningkatan Pengetahuan Siswa Siswi Madrasah Aliyah Nasri, Muhammad Haris; Hammad, Rifqi; Husaini, Rahayun Amrullah; Roodhi, Mohammad Najid; Pratama, Gede Yogi
Bakti Sekawan : Jurnal Pengabdian Masyarakat Vol. 6 No. 1 (2026): Juni
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/bakwan.v6i1.913

Abstract

Advances in digital technology require young people to possess adequate digital literacy skills, particularly in digital marketing, which is now a crucial skill in education, the workplace, and entrepreneurship. However, observations indicate that Madrasah Aliyah (MA) students still lack a grasp of digital marketing concepts and practices. This community service activity aims to improve MA students' knowledge and understanding of basic digital marketing concepts, social media promotion strategies, digital branding principles, and consumer behavior in the digital world. The activity is divided into three stages: preparation, implementation, and evaluation. The preparation phase includes initial discussions with schools and the development of training materials. During the implementation phase, materials are delivered through interactive lectures and discussions, followed by simple practices using digital platforms. Assessments were conducted using pre- and post-tests to measure student knowledge gains. The results showed significant improvement, with an average pre-test score of 42.7 rising to 82.4 in the post-test. This 39.7-point increase indicates that the training successfully strengthened students' understanding of digital marketing concepts. This activity is effective in improving MA students' digital literacy and is relevant to continue with mentoring to better prepare them to face the challenges of the digital era
Pengenalan Bahasa Isyarat Hijaiyah: Augmentasi Data dengan EfficientnetB7 Tanwir, Tanwir; Husain, Husain; Hammad, Rifqi; Anas, Andi Sofyan; Azwar, Muhammad
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 4 (2025): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i4.728

Abstract

Sign language plays an important role as the primary means of communication for individuals with hearing impairments. This study aims to improve the accuracy of hijaiyah sign language detection through the application of the EfficientNetB7 architecture and data augmentation tech-niques. The method used, namely the EfficientNetB7 algorithm, was chosen as the base model be-cause of its ability to balance high accuracy with optimal resource utilization by performing data augmentation with rescale, shear, zoom, rotation, and flip horizontal techniques applied to enrich the variation of the original dataset of 6,811 images to 105,615 images. The experimental results show that the combination of EfficientNetB7 and data augmentation produces 99% accuracy on the test data, with consistent performance seen from the confusion matrix and accuracy loss graph for 50 epochs. This study proves that this approach not only improves model generalization but also reduces the risk of overfitting, thus potentially supporting social inclusion through efficient and reliable technology.
Pengembangan Platform Intervensi Status Gizi Ibu Hamil Berbasis Integrasi Case-Based Reasoning dan Teori Dempster–Shafer Nasri, Muhammad Haris; Hammad, Rifqi; Pratama, Gede Yogi
Jurnal Teknologi Informasi dan Multimedia Vol. 8 No. 1 (2026): February
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v8i1.905

Abstract

Nutritional problems among toddlers and pregnant women remain a major public health issue in Indonesia, necessitating a decision-support system capable of providing rapid and accurate nu-tritional diagnosis and intervention. This study develops an expert system integrating Case-Based Reasoning (CBR) and the Dempster–Shafer theory to diagnose the nutritional status of toddlers and pregnant women. The CBR method is employed to identify solutions for new cases based on similarity to previous cases, while the Dempster–Shafer theory is utilized to handle un-certainty and combine multiple forms of evidence derived from anthropometric, clinical, and health history parameters. The system was tested using 20 cases involving variables such as body weight, height, mid-upper arm circumference (MUAC), hemoglobin level (Hb), gestational age, and dietary intake. The results indicate that the system achieved an accuracy of 90%, an average confidence level of 82.7%, and a diagnostic precision of 88% when compared to expert nutrition-ists’ assessments. Diagnostic discrepancies occurred in only two cases (10%), both of which ex-hibited parameter values near the classification thresholds. These findings demonstrate that the integration of CBR and the Dempster–Shafer theory enhances the reliability of expert systems in generating accurate and measurable nutritional diagnoses despite data uncertainty, and shows strong potential as a decision-support tool for nutritionists in providing faster, more objective, and evidence-based nutritional interventions.
PEMBERDAYAAN KELOMPOK WANITA TANI MELALUI DIVERSIFIKASI PRODUK OLAHAN SINGKONG Muhid, Abdul; Yudiarini, Nyoman; Susanti, Ida Ayu Made Dwi; Javandira, Cokorda; Hammad, Rifqi; Zulfikri, Muhammad
JMM (Jurnal Masyarakat Mandiri) Vol 10, No 1 (2026): Februari
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v10i1.36560

Abstract

Abstrak: Singkong merupakan komoditas pangan lokal yang melimpah di Lombok Utara, namun pemanfaatannya masih terbatas dan bernilai tambah rendah. Keterbatasan keterampilan dan inovasi pengolahan menyebabkan potensi singkong belum dimanfaatkan secara optimal Kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kapasitas Kelompok Wanita Tani (KWT) ITB Asri di, Lombok Utara dalam mengembangkan diversifikasi produk olahan singkong sebagai upaya peningkatan kemandirian dan ekonomi lokal. Metode pelaksanaan menggunakan pendekatan Participatory Community Empowerment melalui tahap perencanaan, edukasi, praktik produksi, pendampingan, dan evaluasi. Hasil kegiatan menunjukkan adanya peningkatan pengetahuan yang signifikan, dengan kenaikan pre-test dan post-test hingga 46% pada aspek produksi serta 26% pada aspek digital marketing. Beberapa produk unggulan seperti tepung mocaf, keripik singkong, dan brownies singkong berhasil dikembangkan dan diproduksi secara mandiri oleh KWT, didukung oleh pendampingan dalam pengemasan, branding, dan pemanfaatan pemasaran digital. Secara keseluruhan, kegiatan ini berhasil meningkatkan keterampilan, motivasi kewirausahaan, dan kapasitas ekonomi KWT, sehingga memberikan dampak positif terhadap pemanfaatan potensi lokal dan penguatan usaha berbasis pangan.Abstract: Cassava is a local food commodity abundant in North Lombok, but its utilization is still limited and has low added value. Limited skills and processing innovations mean that cassava's potential has not been optimally utilized. This community service activity aims to increase the capacity of the ITB Asri Women's Farmers Group (KWT) in Berangan Hamlet, Kayangan Village, North Lombok in developing diversified cassava processed products as an effort to increase independence and the local economy. The implementation method uses a participatory community empowerment approach through the stages of planning, education, production practice, mentoring, and evaluation. The results of the activity showed a significant increase in knowledge, with a pre-test and post-test increase of up to 46% in the production aspect and 26% in the digital marketing aspect. Several superior products such as mocaf flour, cassava chips, and cassava brownies were successfully developed and produced independently by the KWT, supported by mentoring in packaging, branding, and the use of digital marketing. Overall, this activity succeeded in increasing the skills, entrepreneurial motivation, and economic capacity of the KWT, thus having a positive impact on utilizing local potential and strengthening food-based businesses. 
Design and Implementation of a Music Bot and Its Impact on the Community of the Discord Server Slowly Hariadi, Fadli; Husain, Husain; Hammad, Rifqi
Journal of Engineering, Technology and Computing (JETCom) Vol. 4 No. 3 (2025): Journal of Engineering, Technology and Computing (JETCom)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/jetcom.v4i3.307

Abstract

This study aims to design, implement, and evaluate a music bot integrated into the Discord platform, as well as to analyze its impact on community interactions within the “Slowly” Discord server. The bot was developed using the Python programming language and the discord.py library, and tested through black-box testing to ensure the reliability of its core features such as play, pause, resume, skip, queue, and disconnect. The findings indicate that the bot operates stably and meets user expectations. In terms of usage, the bot contributes to increased interaction within the community. The average number of users in the voice channel increased from 1–3 to 4–7 users per day, while the average session duration grew from 2–3 hours to 3–5 hours. Furthermore, during one week of observation, a total of 58 songs were played, demonstrating that the bot not only serves as an entertainment tool but also strengthens social engagement within the community. This study recommends further development including the addition of comprehensive documentation (help command), performance optimization to reduce delays, periodic evaluation of user needs, and migration to cloud hosting services to ensure system availability. Thus, the Discord music bot has the potential to become an integral part of enhancing social interaction and user experience in online communities
Co-Authors Abdul Muhid, Abdul Abdurahman Abdurrahman Ahmad Ahmad Ahmat Adil Al-Mu’min, Al-Mu’min Amrullah, Ahmad Zuli Andi Sofyan Anas Apriani Apriani Apriani Arfa, Muhammad Astuti, Emi Attaqwa, M.Aswin Syarif Azhar, Raisul Azhari, Anjas Ardiyan Azkari, Adzan Naufal Bukran Cahyablindar, Ayu Cokorda Javandira Fatimatuzahra, Fatimatuzahra Fatimatuzzahra Fatimatuzzahra Fatimatuzzahra Guyup Mahardhian Dwi Putra Habib Ratu Perwira Negara Hairani Hairani Hardita, Veny Cahya Hariadi, Fadli Harisandi, Lalu Ilham Hidayat, Fadila Ananda Kartika Husain Husain Husaini, Rahayun Amrullah Husnita Komalasari I Made Yadi Dharma I Nyoman Switrayana Ida Ayu Made Dwi Susanti Kartarina, Kartarina Kurniadin Abd Latif Kusmayadi, Iwan Lestari, I Desak Ayu Adhia M. Hidayatullah Mardedi, Lalu Zazuli Azhar Melati Rosanensi Miftahul Madani Muhammad Haris Nasri Muhammad Innuddin Muhammad Mujahid Dakwah Neny Sulistianingsih Nyoman Yudiarini Pahrul Irfan Panca Mukti, M Thoric Pratama, Gede Yogi Puspita Dewi, Puspita Putri, Destiana Adinda Qososyi, Sayidina Ahmadal Qulub, Mudawil rodhi, mohammad najib Roodhi, Mohammad Najid Samudra, Nanang Santoso, Heroe Saputra, Ahmad Hakiki Sembiring, Rinawati Sholeha, Eka Wahyu Sirojul Hadi Sujaka, Tomi Tri Sujaka, Tomy Tri Sukmawaty Sukmawaty, Sukmawaty Suprayetno, Djoko Suriyati ., Suriyati Syahrir, Moch. Syarif, M. Aswin Tajuddin, Muhammad Tanwir Tanwir Tri Sujaka, Tomi Wirajaya Kusuma Yuliana Yuliana Zamroni Alpian Muhtarom Zuhrian, Naufal Rifqi Zulfikri, Muhammad