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All Journal J@TI (TEKNIK INDUSTRI) Jurnal Algoritma Jurnal Kalibrasi STRATEGIC JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) MANAJERIAL JMM (Jurnal Masyarakat Mandiri) Indonesian Journal of English Language Teaching and Applied Linguistics Business Innovation and Entrepreneurship Journal Scope: Journal of English Language Teaching Jurnal Wacana Ekonomi Elsya : Journal of English Language Studies Jurnal Teknik Informatika (JUTIF) Didaktika: Jurnal Kependidikan Khazanah Akademia Indonesian Journal of EFL and Linguistics Jurnal PkM MIFTEK Jurnal Algoritma Jurnal Kalibrasi Bandung Conference Series: Economics Studies Engineering Science Letter Jurnal Mitra Teknik Industri Indonesian Journal of English Language Teaching and Applied Linguistics
Hilmi Aulawi
Institut Teknologi Garut
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Social Sciences Other

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Perancangan Strategi Pemasaran Digital Produk Olahan Kentang di Taman Teknologi Pertanian Cikajang Ali Kamaludin; Hilmi Aulawi; Risa Aisyah
Jurnal Kalibrasi Vol 24 No 1 (2026): Jurnal Kalibrasi
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/kalibrasi/v.24-1.2954

Abstract

This study aims to design a digital marketing strategy for processed potato products at the Cikajang Agricultural Technology Park (TTP) by utilizing the SOSTAC framework and the Analytical Hierarchy Process (AHP) method. The main problem faced is the suboptimal use of digital channels, resulting in sales being limited to nearby shops and direct purchases. Data were collected through interviews and questionnaires and then analyzed using Super Decisions software. The results show that the most influential criterion is the impact on sales (0.4412), while the priority strategies are TikTok Live and Interactive Content (0.3323). Other strategies such as Free Shipping, Giveaways and Local Events, and Instagram Marketing can be implemented as supporting strategies. Therefore, TTP Cikajang needs to focus on interactive social media strategies, particularly TikTok Live, to increase consumer engagement and expand the digital market.
RMSProp Optimizer and KAN Method-Based CNN on Rupiah Banknote Classification for Visually Impaired Dede Kurniadi; Murni Lestari Rahmi; Benedicto B. Balilo Jr; Hilmi Aulawi
Engineering Science Letter Vol. 4 No. 02 (2025): Engineering Science Letter
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/IISTR.esl.00936

Abstract

The visually impaired refers to individuals who experience a loss of visual function. Approximately 4 million people, or about 1.5% of Indonesia's total population, are visually impaired. They rely on their sense of touch to recognize banknote denominations in financial transactions. However, damaged banknotes often hinder identification and increase the risk of fraud. Therefore, this study aims to develop a rupiah banknote denomination classification model to assist them in conducting independent transactions. The researchers developed a CNN-KAN model with the RMSProp optimizer using a private dataset comprising 800 images of Rupiah banknotes with denominations of IDR 1,000, IDR 2,000, IDR 5,000, IDR 10,000, IDR 20,000, IDR 50,000, IDR 75,000, and IDR 100,000 from the 2016, 2020, and 2022 emission years. The dataset encompasses variations in image perspectives, lighting conditions, and the physical state of banknotes, including both intact and damaged ones, with up to 30% of the samples comprising damaged banknotes. Data augmentation techniques were implemented to improve data diversity. The dataset was then utilized for training and testing with different split ratios: 50:50, 60:40, 70:30, 80:20, and 90:10. Performance evaluation was conducted using loss, accuracy, precision, recall, and AUC-ROC metrics. Experimental results indicate that the CNN-KAN model with the RMSProp optimizer achieved optimal performance. In the 90:10 data split scenario, the model achieved 100% accuracy, precision, and recall, with an AUC-ROC of 1 and a loss of 0.008. Therefore, the CNN-KAN model with the RMSProp optimizer has been proven effective for implementing Rupiah banknote denomination detection for the visually impaired in an automated system.
Benchmarking YOLOv8 Variants with Transfer Learning for Real-Time Detection and Classification of Road Cracks and Potholes Dede Kurniadi; A. Abdul Latif; Asri Mulyani; Hilmi Aulawi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6710

Abstract

Road damage, including potholes and cracks, is a significant issue frequently encountered in road infrastructure in many regions. Such conditions accelerate road degradation, increase the risk of traffic accidents, and significantly increase the maintenance and repair costs. Although several deep learning models have been proposed for road damage detection, few studies have systematically compared the performance of lightweight YOLOv8 variants using a consistent dataset. To address this gap, this study proposes a road defect detection and classification model based on the YOLOv8 series, which is enhanced using transfer learning to improve performance and efficiency. The dataset, obtained from Roboflow, comprises 3,846 images categorized into training, validation, and testing sets. Three YOLOv8 variants—YOLOv8n, YOLOv8s, and YOLOv8m—were benchmarked for performance. A performance evaluation was performed using the metrics of precision, recall, and mean Average Precision (mAP). Results show that YOLOv8m achieved the highest precision (99.00%), recall (98.40%), and mAP (99.50%). In the pothole category, precision reached 98.70% and recall 99.30%; in the crack category, precision was 99.30% and recall 97.60%. The findings demonstrate that YOLOv8, particularly the YOLOv8m variant, is highly effective for real-time road damage detection and classification, offering a viable solution for intelligent transportation systems and automated infrastructure monitoring. This research has the potential to revolutionize infrastructure monitoring by enabling scalable, real-time, and cost-effective assessments of road conditions. It minimizes reliance on manual inspections, reduces human errors, and contributes to the development of intelligent transportation systems and predictive maintenance strategies.
Co-Authors A. Abdul Latif Abdu Syobir Abdusy Syakur Amin Ade Sutedi Agi Ferdiansyah Sunarya Ahmad Dzulfikar, Bilal Aisyah, Risa Al Faujan, Septian Kiki Al Fisimar, Farhan Ali Kamaludin Alpin Nurzaman Andri Ikhwana Andriyas Kurniawan, Wahyu Angga Syaeful Azhar Anjas Ninda Hantari Ariyan Hendriatama Putra Saridi Asri Mulyani Aulia Malik Ayu Latifah Bajuri, Ahmad Balilo Jr, Benedicto B. Benedicto B. Balilo Jr Dahman, Muhamad Dede Kurniadi Deni Sahroni Dewi Rahmawati DEWI RAHMAWATI Dian Kusma Noria Dini Destiani Siti Fatimah Dini Riska Anggraeni Eko Walujodjati Faujani, Zidan Ahmad Fikar Raysona, Mochamad Firmansyah, Ara Fitriyadi Salam Gilang Nur Akbar Hamdani, Nizar Alam Hatta Jayawardhana Holisoh, Iis Iman Sudirman Imat Sutarman Iqbal Try Maulana Kadarsah Suryadi Kustian Arisandi Fajar Misbah Syahbudin, Muhammad Khoirul Muhamad Faisal Muhammad Syauqi Mubarok, Muhammad Syauqi Murni Lestari Rahmi Nabhani, Irfan Neng Rita Nurjanah Novie Susanti Suseno Nur Lela Nurhaliza, Nabila Putri Nursa'diah, Rifania Sapta R Tita Rospita S Rachel Sifa Rajesri Govindaraju Ramadhani, Reski Rani Andriani, Rani Reski Ramadhani Revy Ardiansyah Ridwan Jauhari Ridwan Setiawan Ridwan Setiawan Ridwan Setiawan Rina Kurniawati Rina Kurniawati Rinda Cahyana Rinrin Rubianti Risa Aisyah Robiyatul Adawiyah Isni Putri Ruari, Elgi Muhamad Rustandi Rustandi, Rustandi Sabila Rismawati Saepul Jamil, Alwis Santoso, Bambang Tri Sheila Nur Sheilawati Sopian Sopian Sri Rahayu Sukonoya, Muhammad Fajar Sunarya, Agi Ferdiansyah Suseno, Novie Susanti Taofik Slamet Taptajani, Dedi Sa'dudin Ulfa, Risma Liyana Vizay Vicky Pratama Wahyu Andreas Kurniawan Wahyu Andriyas Kurniawan Yadi Ahmad Fauzi Yanti Yogi Permana Yogi Teguh Herdiansyah Yusep Senjani