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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) JAIS (Journal of Applied Intelligent System) SISFOTENIKA Journal of Electrical Technology Jurnal Teknologi Informasi MURA Voice Of Informatics Zero : Jurnal Sains, Matematika, dan Terapan JOURNAL OF SCIENCE AND SOCIAL RESEARCH JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) CSRID (Computer Science Research and Its Development Journal) Jurnal Informatika Kaputama (JIK) Jurnal Mantik IT (INFORMATIC TECHNIQUE) JOURNAL ICIT (Innovative Creative and Information Technology) Journal REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Generic JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Journal of Applied Computer Science and Technology (JACOST) DEVICE Syntax: Journal of Software Engineering, Computer Science and Information Technology Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) INFOSYS (INFORMATION SYSTEM) JOURNAL Jurnal IPTEK Bagi Masyarakat Jurnal Ipteks Terapan : research of applied science and education International Journal of Research in Vocational Studies (IJRVOCAS) Jurnal Minfo Polgan (JMP) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) JURNAL ILMIAH INFOKOM Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Jurnal Teknologi Informasi Mura Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) CSRID
Rika Rosnelly
Uiversitas Potensi Utama
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Penerapan Metode POQ dalam Penentuan Persediaan Material Proyek pada PT. Swakarya Putra Berbasis Android Daniel Ginting; Rika Rosnelly
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 2 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No2.pp302-310

Abstract

Material inventory is a crucial factor in the smooth running of construction projects. PT. Swakarya Putra has been facing challenges in managing its inventory, such as delays in stock information, recording errors, and unplanned purchases. The purpose of implementing the POQ method is to control material inventory to minimize inventory costs and ensure timely material availability. The POQ method contributes to determining the optimal order quantity and timing by considering ordering, storage costs, and project material requirements. The system is built on an Android platform so that it can be accessed in real time by relevant parties in the field. The implementation results show that the system is able to calculate material ordering schedules accurately, simplify stock monitoring, and reduce the risk of shortages or excess inventory. Thus, the implementation of the Android-based POQ method can improve the efficiency of controlling project material inventory at PT. Swakarya Putra. This method helps minimize the risk of stockouts and excess stock, as well as improve operational efficiency by ordering quantities at specific time intervals.
OPTIMASI PIPELINE KLASIFIKASI PENYAKIT PADI MENGGUNAKAN STRATEGI AUGMENTASI CITRA INTENSIF DAN TRANSFER LEARNING EFFICIENTNET-B0 Dwi Robiul R; Diyo Mollana F; Nanda S; Johan; Rahmad S; Satriyo W; Rika Rosnelly
INFOKOM (Informatika & Komputer) Vol 13 No 2 (2025): JURNAL INFOKOM DESEMBER 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i2.2355

Abstract

Rice plant diseases represent a significant challenge to global food productivity. This study aims to optimize a rice disease classification pipeline using the EfficientNet-B0 architecture combined with intensive image augmentation strategies and transfer learning. The dataset comprises 10,407 rice leaf images categorized into 10 classes, including healthy conditions and nine types of diseases. Augmentation strategies such as random rotation, color jittering, and random resized cropping were implemented to enhance model robustness against diverse field conditions. Evaluation results demonstrate that the model achieved outstanding performance, with a Top-1 Accuracy of 96.25% and a Top-5 Accuracy of 99.90%. Grad-CAM++ analysis validated that the model accurately focuses feature extraction on pathological leaf areas. t-SNE visualization revealed clear feature cluster separation between classes, further supported by ROC curve AUC values reaching 1.00 for the majority of categories. This research confirms that the proposed pipeline is highly reliable for early rice disease detection and holds significant potential for mobile device implementation to assist farmers.
Practice-Based Digital Marketing and Coding Training to Strengthen Students’ Entrepreneurial Competencies at Bina Satria School Linda Wahyuni; Rika Rosnelly; Soeheri Soeheri; Chairul Rizal; Hardianto Hardianto; Andika Wiratama; Afandi Maulana
Jurnal IPTEK Bagi Masyarakat Vol 6 No 1 (2026)
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/j-ibm.v6i1.1738

Abstract

This community service program implemented practice-based digital marketing and coding training to strengthen students’ digital entrepreneurship competencies at Bina Satria School. The program integrated experiential learning and project-based learning through website development using HTML, PHP, and MySQL, product catalog management, and digital promotion activities. Thirty students participated in six groups. Data were collected through observation, interviews, documentation, identical pre-test and post-test questionnaires, and project assessment. The 12-item questionnaire was reviewed by three experts. Internal consistency testing yielded Cronbach’s α = 0.683 and standardized Cronbach’s α = 0.715. Before the training, 83.3% of participants reported no or limited understanding; after the training, 73.3% reported understanding or high understanding. All six groups completed functional website projects with scores ranging from 88 to 91. The findings indicate an aggregate shift toward higher understanding and support the practical feasibility of integrating coding and digital marketing in contextual entrepreneurship training. Because the evaluation used categorical descriptive data without a comparison group or paired inferential analysis, the findings do not establish the program’s causal effectiveness.
Optimasi Algoritma Genetika pada Perbandingan ANN dan KNN untuk Klasifikasi Penyakit Jantung Andreas Zai; Lima Hartima Rambe; Reza Ananda Putra; Rika Rosnelly; Tamado Simon Sagala; Indra Kelana Jaya
Majalah Ilmiah METHODA Vol. 15 No. 1 (2025): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol15No1.pp10-23

Abstract

A comparative analysis of genetic algorithm optimization methods on the performance of Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) in heart disease classification shows significant results. The research used a heart disease dataset consisting of 303 samples with 14 attributes. Genetic algorithm optimization produced substantial performance improvements in both models. The optimized ANN model achieved 94.85% accuracy, 93.00% precision, 97.00% recall, and 97.00% ROC AUC, demonstrating excellence in positive case identification. Meanwhile, the optimized KNN model achieved 93.30% accuracy, 92.00% precision, 95.00% recall, and 96.77% ROC AUC, yielding more balanced performance. The genetic algorithm optimization method proves its effectiveness in improving heart disease classification accuracy, where ANN is optimal for applications requiring high sensitivity and KNN is more stable for small datasets.
Co-Authors Abwabul Jinan Adil Setiawan Aditia Rangga Afandi Maulana Agung RM Alam Agus F Nduru Agus F.S. Ndruru Agus Fahmi Agus Fs Ndruru Akbar Idaman Alan Prayogi Alesia Lorenza Sinaga Alvinur Naswar Alvinur Naswar Ameliana Sihotang Andika Wiratama Andreas Jorghy Parapat Andreas Rezeki Zai Andreas Zai Andri Armaginda Siregar Annisa Ashari Anton Purnama Arselan Ashraf B. Herawan Hayadi Bambang Suhardi Batubara, Muhammad Akbarri Bill Raj Bob Subhan Riza Bob Subhan Riza Chairul Rizal Cindy Paramitha Cindy Paramitha Damri Mulia Hutabalian Daniel Ginting Dedi Irawan Dedi Irawan Della Syahrani Desi Irfan Dian Maya Sari Diky Wahyudi Diyo Mollana F Dwi Robiul R Edy Victor Haryanto, Edy Victor Eko Setyo Budi Putra Aji Elly Veronika Sihite Elsa Aditya Eri Triwanda Esmawaty Sinaga Fadil Habib Fadil Habib Farhan Sardy Abdillah Finis Hermanto Laia Gilang Harahap Gusti Firanda Hardianto Hardianto Hardianto Hardianto Hartono Hartono Hetty Zahrani Indra Kelana Jaya Iqbal Giffari Ritonga Iswanto Jaka Kusuma Jaka Tirta Samudra Jalaluddin Nasution Jazmi Hadi Matondang Johan Junaidi Junaidi Karuniaman Buulolo Kristine Wau Lima Hartima Rambe Linda Wahyuni Linda Wahyuni Linda Wahyuni Lubis, Cindy Paramitha M Suhada WD M. Agung Oki Prayugo Maradona Jonas Simanullang MARIA BINTANG Masri Wahyuni Mega Christin Lase Mega Christin Morys Lase Mega Marisani Ziraluo Mhd Agung Irnanda Mhd Prasetyo Mimi Chintya Adelina Mira Kartiwi Mubarak - Muhammad Al Adib Muhammad Fachrurrozi Nasution Muhammad Sadikin Muhammad Suhada WD Muhammad Zulkarnain Lubis Mutiara S. Simanjuntak Nanda S Naufal Dhiya Putra Dalimunthe Pebruarianto Hutabarat Pius Deski Manalu Progresif Bulolo Progresif Bulolo5 Puji Sari Ramadhan Rabiatul Adawiyah Hasibuan Rahmad S Rahmat Humala Putra Hasibuan Rahmatika Hizria Rais Affaruq Zunnurain Ramadhani Ritonga Reza Ananda Putra Ricky Irnanda Ridha Maya Faza Lubis Rofiqoh Dewi Rohima, Rohima Romi Antoni Rony, Zahara Tussoleha Roslina, Roslina Rubianto Rubianto Rubianto Sartika Mandasari Sarwadi Sarwadi Sarwadi, Sarwadi Satriyo W Setiawan, Adil Soeheri Soeheri Surya Tri Nowo Susiana Khosasih Syawaluddin Kadafi Parinduri Tamado Simon Sagala Teddy Gunawan Teddy Surya Gunawan Teddy Surya Gunawan Teresa Tamba Tri Andre Anu Triandi, Budi Ubaidullah Hasibuan Wahyuni, Linda Wanayumini Wulandari, Wulandari Yiska Dayanti Zagoto Yuke Manza Yuni Franciska Zakarias Situmorang Zuriati Janin