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All Journal Jurnal Simetris Bulletin of Electrical Engineering and Informatics SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Dinamisia: Jurnal Pengabdian Kepada Masyarakat Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah Informatik : Jurnal Ilmu Komputer Jurnal Telematika Jurnal Mantik SULUH: Jurnal Abdimas Computer Science and Information Technologies Jurnal Abdimas Bina Bangsa Jurnal Informatika: Jurnal Pengembangan IT ABDIKOM
Ridwan Raafi'udin
Universitas Pembangunan Nasional Veteran Jakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Analisis Nilai Sensor untuk Penilaian Kualitas Aroma Kopi Kolombia Hananto, Bayu; Raafi’udin, Ridwan; Widiyanto, Didit
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 16, No 1 (2025): JURNAL SIMETRIS VOLUME 16 NO 1 TAHUN 2025
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v16i1.13989

Abstract

Penilaian kualitas aroma kopi merupakan aspek krusial dalam industri kopi, terutama untuk produk-produk premium seperti kopi Kolombia. Studi ini bertujuan untuk analisis nilai sensor menggunakan electronic nose dalam mengkategorikan kualitas aroma kopi Kolombia berdasarkan tiga kategori: kualitas tinggi (HQ_Coffee), kualitas sedang (AQ_Coffee), dan kualitas rendah (LQ_Coffee). Metode yang digunakan melibatkan pengambilan data aroma kopi menggunakan electronic nose dengan berbagai jenis sensor, termasuk SP-12A, SP-31, TGS-813, TGS-842, SP-AQ3, TGS-823, ST-31, dan TGS-800, yang masing-masing menunjukkan karakteristik respons yang berbeda. Hasil studi menunjukkan bahwa sensor SP-31 memiliki sensitivitas tertinggi terhadap aroma kopi di semua kategori, menjadikannya sensor yang paling andal untuk deteksi kualitas aroma. Sensor TGS-842 menunjukkan fleksibilitas dengan rentang respons yang luas, sementara sensor SP-AQ3 memiliki sensitivitas terendah, yang mungkin membatasi efektivitasnya dalam mendeteksi variasi aroma yang kompleks. Kesimpulannya, penggunaan kombinasi sensor dalam electronic nose dapat menghasilkan penilaian kualitas aroma kopi yang lebih cepat, konsisten, dan objektif dibandingkan dengan metode manual.
Pengembangan Prototipe untuk Prediksi Tingkat Penyeduhan Kopi Menggunakan Data Spektroskopi dan Deep Learning Prananto, Muhammad Teguh; Raafi'udin, Ridwan; Adrezo, Muhammad; Pradana, Musthofa Galih; Arifuddin, Nurul Afifah
Jurnal Informatika: Jurnal Pengembangan IT Vol 10, No 3 (2025)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v10i3.8710

Abstract

Consistency in coffee flavor is a crucial factor for coffee enthusiasts, thus requiring a method capable of objectively measuring the coffee brewing level in accordance with the standard brewing chart. This study utilizes the AS7265X spectroscopy sensor to capture the characteristics of coffee based on the resulting light spectrum. The spectral data is then used in a deep learning model using the Convolutional Neural Network (CNN) algorithm to classify the coffee brewing level into five distinct classes. A total of 150 data samples were used in the training and testing process. Initial results show that the model achieved a very high average accuracy of approximately 97%. After hyperparameter tuning using the Random Search method, the model's accuracy further improved, reaching a very high accuracy. However, this performance improvement resulted in a trade-off in computational time, with execution time increasing from 15 seconds to 1 minute and 43 seconds. This research is expected to contribute to ensuring consistent coffee brew quality and to open opportunities for further studies that combine sensor technology and artificial intelligence in the food and beverage sector.
Performance comparison of algorithms in the classification of fresh fruit types based on MQ array sensor data Hananto, Bayu; Raafi'udin, Ridwan
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.9070

Abstract

Accurate classification of fresh fruit types is essential in the agricultural sector for ensuring quality control, minimizing waste, and enhancing food safety across the supply chain. This study evaluates the performance of four machine learning algorithms—artificial neural network (ANN), K-nearest neighbors (KNN), logistic regression (LR), and random forest (RF)—in classifying fruit freshness based on data obtained from electronic noses equipped with MQ array sensors. Experiments were conducted using a comprehensive dataset comprising various fruit combinations, and model performance was assessed using accuracy, precision, recall, and F1 score metrics. Results indicate that the RF algorithm achieved the highest accuracy (100%) and precision (1.00), demonstrating superior performance in both classification accuracy and computational efficiency. ANN and KNN also performed well, with accuracies of 96.80% and 97.10%, respectively, while LR yielded a lower but still effective accuracy of 91.16%. Statistical analysis confirms that RF's superior performance is statistically significant when compared to the other algorithms. These findings suggest that RF is the most effective algorithm for fruit freshness classification using electronic nose data, offering fast and reliable results that are well-suited for integration into real-time monitoring systems in agricultural and food retail applications.
Pelatihan Canva dalam Peningkatan Kapasitas Pembuatan Materi Ajar Interaktif pada Guru di TK Islam Al Azkar Dewi, Catur Nugrahaeni Puspita; Raafiudin, Ridwan; Indriana, Intan Hesti; Theresa, Ria Maria
Jurnal Pengabdian kepada Masyarakat Bidang Ilmu Komputer Vol 3 No 2 (2025): Jurnal Pengabdian Kepada Masyarakat Bidang Ilmu Komputer (ABDIKOM)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/abdikom.v3i2.11966

Abstract

Desain materi ajar yang menarik memiliki peran penting dalam meningkatkan efektivitas pembelajaran, khususnya untuk anak usia dini. Salah satu solusi praktis yang dapat digunakan guru adalah platform desain Canva, yang menyediakan berbagai fitur user-friendly untuk menciptakan materi pembelajaran visual yang menarik. Penelitian ini mengevaluasi hasil pelaksanaan pelatihan desain pembelajaran menggunakan Canva melalui data form evaluasi yang dikumpulkan dari peserta pelatihan guru TK Islam Al Azkar. Hasil evaluasi menunjukkan peningkatan signifikan dalam kemampuan peserta menggunakan Canva secara mandiri. Mayoritas peserta memberikan respon positif dan menyatakan bahwa pelatihan ini sangat bermanfaat. Diharapkan pelatihan ini dapat berkelanjutan untuk terus meningkatkan kompetensi guru dalam menciptakan media pembelajaran digital yang menarik dan efektif.
Utilization of Electronic Nose to Detect Quality of Meat in the Beef Ribs section Hananto, Bayu; Widiyanto, Didit; Raafi'udin, Ridwan
SITEKIN: Jurnal Sains, Teknologi dan Industri Vol 21, No 1 (2023): December 2023
Publisher : Fakultas Sains dan Teknologi Universitas Islam Negeri Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24014/sitekin.v21i1.27066

Abstract

This study analyzes the use of Electronic Nose (E-Nose) in detecting the quality of beef on the ribs. This experiment used a variety of gas sensors, and found a significant pattern related to rib meat quality. There are three sensors, namely MQ137, MQ5, and MQ6, which show the value is inversely proportional to the other sensors. An increase in the value of this sensor indicates a decrease in the quality of the ribs. Furthermore, MQ8 gave the highest score in the "Good" and "Excellent" categories, while MQ5 and MQ6 gave the highest score in the "Equal" and "Not Eligible" categories. The analysis revealed that E-Nose has the ability to recognize changes in aroma associated with changes in the quality of rib meat. These results show that E-Nose can provide objective and fast information about the quality of beef in the ribs, which can support the food industry in decision making and product quality control. Further research is needed to optimize the use of sensors and validate this technology in various storage conditions and types of beef.
Kegiatan Training of Trainers (ToT) Pengelolaan Desa Cerdas Digital Bagi Aparatur Pemerintah Desa Rawa Panjang Kabupaten Bogor Solihin, Indra Permana; Triwahyono, Bambang; Wibisono, M. Bayu; Raafi’udin, Ridwan; Wirawan, Rio
Jurnal Pengabdian kepada Masyarakat Bidang Ilmu Komputer Vol 2 No 1 (2023): Jurnal Pengabdian Kepada Masyarakat Bidang Ilmu Komputer (ABDIKOM)
Publisher : Fakultas Ilmu Komputer

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

Abstract

Kemajuan teknologi informasi telah memengaruhi cara layanan masyarakat di daerah pedesaan. Salah satu konsep yang berkembang adalah "Smart Village" (Desa Cerdas), yang menggabungkan teknologi dalam berbagai aspek pembangunan pedesaan. Dalam kerangka Program Peningkatan Pemerintahan dan Pembangunan Desa (P3PD), Kementerian Desa Pembangunan Daerah Tertinggal dan Transmigrasi (Kemendesa PDTT) telah mendorong penggunaan teknologi informasi dan komunikasi sebagai salah satu prioritas dalam alokasi dana desa. Hal ini bertujuan untuk mencapai Sustainable Development Goals (SDGs) di tingkat desa. Training of Trainer (ToT) mengenai pengelolaan desa cerdas ini diberikan kepada aparatur pemerintah desa dengan harapan mereka dapat menjadi instruktur yang melatih pemangku kepentingan di desa. Hasil dari pelatihan ini mencakup kemampuan peserta untuk mengelola proses penyusunan dokumen secara digital, mulai dari tingkat RT hingga tingkat yang lebih tinggi. Hal ini memungkinkan percepatan dan efisiensi dalam penyampaian surat dengan memanfaatkan teknologi tanda tangan digital. Selain itu, hasil pelatihan ini diharapkan akan memungkinkan adopsi layanan digital yang terintegrasi secara daring pada tahun 2024. Sebagai hasilnya, setiap layanan kepada masyarakat akan berfokus pada penerapan konsep "Smart Village" dengan layanan persuratan digital yang terintegrasi secara daring, dengan tujuan memberikan pelayanan yang optimal kepada masyarakat.
Digital Empowerment:Improving Dasawisma's Capabilities in Online Marketing and Sales Through the Marketplace: Digital Empowerment: Peningkatan Kapabilitas Dasawisma Dalam Pemasaran Dan Penjualan Online Melalui Marketplace Raafi’udin*, Ridwan; Rosmawarni, Neny; Dewi, Catur Nugrahaeni Puspita; Edyana, Fajar
Dinamisia : Jurnal Pengabdian Kepada Masyarakat Vol. 8 No. 6 (2024): Dinamisia: Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/dinamisia.v8i6.22099

Abstract

This community service activity aims to improve the capabilities of dasawisma women in RW 10, Ciracas Village, Ciracas District, East Jakarta in digital marketing and online sales through the marketplace platform. Through a series of practical trainings, participants have been given an in-depth understanding of digital marketing concepts, effective online marketing strategies, and the use of various features in the marketplace platform. In addition, legal aspects, online security, and network development are also the focus, providing a strong foundation for participants to run an online business sustainably. With the aim of empowering the local economy, this activity is expected to help dasawisma women take advantage of the potential of the local economy and increase their contribution to local economic development, as well as this activity helps the government technically in relation to the community directly. This activity was attended by 120 participants and as many as 85 have provided feedback from the material and experience that has been given. The training material was delivered in lectures and discussions. For the lecture session, it was delivered by presenting material about digital marketing through the marketplace and comparing it in a conventional way. Broadly speaking, participants are able to accept and understand the use of digital marketing technology through the marketplace. Furthermore, the results of the implementation of community service activities were evaluated using a SWOT analysis with results showing a significant increase in understanding of online security and marketing. With the results of the training that show for the better, the community, especially dasawisma women, is ready to develop businesses both managed independently and business groups managed under the auspices of local residents.
Analisa Trafik Pengunjung Website dalam Pengembangan UI dan UX Raafi'udin, Ridwan; Hananto, Bayu; Nugrahaeni Puspita Dewi, Catur
Informatik : Jurnal Ilmu Komputer Vol 15 No 2 (2019): Agustus 2019
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (313.248 KB) | DOI: 10.52958/iftk.v15i2.1419

Abstract

Perkembangan teknologi informasi dan komunikasi menggiring para pengguna untuk selalu memutakhirkan penerapan teknologinya. Hampir di setiap lapisan masyarakat baik di kalangan industri dalam persaingan bisnisnya maupun di bidang pendidikan untuk meningkatkan layanan pendidikan yang semakin baik. Website portal menjadi salah satu kewajiban yang harus dimiliki oleh universitas dalam rangka penyediaan layanan informasi kepada khalayak umum, yang memerlukan informasi. Dalam rangka peningkatan pelayanan informasi kepada khayalak tersebut diperlukan peningkatan dari berbagai aspek, seperti kecepatan akses, user interface, dan user experience. Pada penelitian ini, peneliti akan mencoba meningkatkan user experience pada website portal yang dimiliki Universitas Pembangunan Nasional Veteran Jakarta. Dengan peningkatan tersebut diharapkan akan meningkatkan kepuasan khayalak terhadap pemenuhan kebutuhan informasi yang bersumber dari kampus UPN Veteran Jakarta.
Effects of Semi-Automated Preprocessing in The Beef Freshness Prediction based on Near Infrared Spectroscopy Raafi'udin, Ridwan; Purwanto, Yohanes Aris; Sitanggang, Imas Sukaesih; Astuti, Dewi Apri
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol. 16 No. 2 (2025): JURNAL SIMETRIS VOLUME 16 NO 2 TAHUN 2025
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v16i2.15142

Abstract

This study investigates the application of near-infrared spectroscopy (NIR) within the wavelength range of 1350–2550 nm to predict key quality parameters of beef, specifically focusing on tenderloin cuts. The quality indicators assessed include drip loss, color, pH, moisture content, storage duration, and total plate count (TPC) as a measure of microbial load. Predictive modeling was conducted using three machine learning algorithms: Partial Least Squares (PLS), Support Vector Regression (SVR), and Random Forest Regressor (RFR). To enhance model accuracy, a semi-automated preprocessing pipeline was employed utilizing the Nippy library. This library integrates several spectral preprocessing techniques including Savitzky-Golay filtering, Standard Normal Variate (SNV), Robust Normal Variate (RNV), Local Standard Normal Variate (LSNV), as well as clipping, resampling, baseline correction, and smoothing.  Among the models developed using raw spectral data, the RFR model exhibited the highest performance, achieving coefficient of determination (R²) values of 0.82 for drip loss, 0.65 for color, 0.67 for pH, 0.61 for moisture content, 0.81 for storage duration, and 0.76 for TPC. Post preprocessing, the predictive accuracy improved significantly with R² values increasing to 0.89, 0.82, 0.87, 0.85, 0.91, and 0.90 respectively for the same parameters. These findings underscore the potential of combining advanced machine learning techniques with robust preprocessing methods to enhance the non-destructive, rapid assessment of beef quality parameters. This approach offers a promising tool for quality control in the meat processing industry, facilitating more efficient and accurate monitoring of product standards.
Co-Authors Ali Khumaidi ali khumaidi, ali Catur Nugrahaeni Puspita Dewi DEWI APRI ASTUTI Didit Widiyanto Edyana, Fajar Fajar Edyana Hananto, Bayu Henki Bayu Seta Imas Sukaesih Sitanggang Indra Permana Solihin Intan Hesti Indriana Jayanta Jayanta Mohamad Bayu Wibisono Muhammad Adrezo Musthofa Galih Pradana Neny Rosmawarni Nugrahaeni Puspita Dewi, Catur Nurul Afifah Arifuddin Prananto, Muhammad Teguh Ria Maria Theresa Tri Rahayu Triwahyono, Bambang Wirawan, Rio