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JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer)
Published by Universitas Merdeka Malang
ISSN : 26565722     EISSN : 2685497X     DOI : -
Core Subject : Science, Education, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mathematics
Sistem Tenaga Generator, Distribusi Daya, Konversi Daya Listrik, Sistem Perlindungan dan Teknologi Bahan elektrik Sinyal, Sistem, dan Elektronik Pemrosesan Sinyal Digital, Pemrosesan Gambar, Sistem Robot, Sistem Kontrol dan Sistem Embeded Sistem komunikasi Telekomunikasi, Komunikasi Nirkabel dan Jaringan Komputer Teknologi Informasi Rekayasa Perangkat Lunak, Penambangan Data Multimedia, Komputasi Bergerak, Komputasi Paralel / Terdistribusi, Inteligensi Buatan, Grafik Komputer dan AR / VR Aplikasi Sains Instrumentasi, Matematika, Fisika, Teknologi Geologi, Kimia, Pendidikan Sains dan Teknologi Kesehatan atau Biomedis.
Arjuna Subject : -
Articles 129 Documents
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Pengenalan Kualitas Tempe Berbasis YOLOv8 untuk Deteksi Dini Kegagalan Fermentasi Isa Mahfudi; Mila Kusumawardania; Moechammad Moechammad Sarosa; Chandrasena Setiadi; Galih Putra Riatma; Farida Arinie Soelistianto; Nabila Izzatul Muslimah; Nadia Yumni Izati
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16091

Abstract

Tempe is a traditional Indonesian food whose fermentation process is highly influenced by temperature, humidity, and soybean quality. Inadequate environmental conditions can lead to fermentation failure, reducing product quality and causing economic losses. Traditionally, quality assessment of tempe has been carried out manually by artisans, which is subjective and inconsistent. This study aims to develop an automatic tempe quality recognition system based on YOLOv8, implemented on a Raspberry Pi 4B with a Logitech C270 camera, monitoring webserver, and buzzer as an early warning system. The YOLOv8 model was trained to detect two main categories, namely good tempe and failed tempe, through real-time visual analysis. Experimental results show system performance with an average accuracy of 93.1%, precision of 93.5%, recall of 91.2%, and mAP@50 of 94.7%. Confidence score analysis indicates that the model is more certain in detecting failed tempe (0.94–0.95) compared to good tempe (0.80–0.86), due to clearer visual differences.
Hybrid Sampling untuk Meningkatkan Akurasi Deteksi Kanker Serviks pada Data Tidak Seimbang: Kajian Komparatif Slamet Widodo; Samudi; Herlambang Brawijaya
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16134

Abstract

Cervical Cancer has a high mortality rate among women, driving the adoption of early detection systems based on machine learning. However, their implementation is hindered by class imbalance issues, as seen in the UCI Cervical Cancer Behavior Risk Dataset, where positive cases constitute only 5.8–7.3% of the data. This study proposes an evaluation of resampling techniques—including SMOTE, ADASYN, Random Undersampling, and Borderline-SMOTE—combined with classification algorithms such as RF, XGBoost, LR, GNB, and k-NN. Using Stratified K-Fold Cross Validation to preserve the original class distribution in each fold and ensuring resampling is applied only to the training data in each iteration, the results demonstrate that Borderline-SMOTE significantly improved model performance. Specifically, the Random Forest model achieved a Recall of 0.87 and an AUC-ROC of 0.94. These findings are expected to provide a foundation for future research focused on optimizing adaptive sampling methods
Analisis Daya Keluaran PLTS–Turbin Angin terhadap Suhu Kotak Pendingin Portable Terintegrasi GPS IoT: Indonesia Mas Ahmad Baihaqi; Hartawan Abdillah Abdillah; Adi Mulyadi; Tamam Asrori Asrori; Alief Muhammad; Ahmad Fauzan; M. Bayu Afandi
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16183

Abstract

The main challenge faced by small-scale fishermen in Probolinggo is the deterioration of fish catches due to limited cooling systems. This study developed a portable cooling box powered by a hybrid solar–wind energy system integrated with GPS–IoT. The system was designed using a 100 Wp solar panel, a 450 W wind turbine, a 100 Ah battery, a 3000 W inverter, and temperature sensors with IoT communication modules for real-time monitoring. Experiments were conducted for 12 hours under three operating modes: solar, wind only, and hybrid. The results show the hybrid mode maintained the cooling box temperature below 8 °C for more than 12 hours, while the solar-only and wind-only modes lasted only 4–7 hours. The GPS–IoT integration enabled simultaneous monitoring of vessel location and energy conditions. Therefore, the proposed system proved to be more reliable in preserving fish quality while enhancing efficiency and safety of small-scale fishermen through renewable energy.
Rancang Bangun Rhodamine Detector menggunakan Metode Fuzzy Tsukamoto berbasis Internet of Things Ulfa Andayani; Eka Ratri Noor Wulandari; Salnan Ratih Asriningtias; Bayu Sutawijaya; Hafrida Rahmah
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16269

Abstract

This study developed a detection device capable of identifying the presence of Rhodamine B in food using an Internet of Things (IoT)-based Fuzzy Tsukamoto method. Rhodamine B is a coloring agent commonly used in the food industry, but its presence poses health risks. The Fuzzy Tsukamoto method was applied for its ability to manage uncertain information, while IoT technology enabled real-time monitoring. The research resulted in a detection tool with high accuracy and fast response time. Based on validation using 28 field samples, the fuzzy Tsukamoto-based detection system achieved a classification accuracy of 96.5%. The integration of these technologies enhanced analytical precision and allowed direct monitoring across various food types. The findings demonstrate that the developed detection device is efficient, reliable, and compliant with food safety standards, making it suitable for use in food monitoring and quality control processes
Perancangan Safety Lock pada Brangkas Uang Berbasis Arduino Uno dengan QR Scanner GM 65 dan Sensor Fingerprint AS608 Alvin Zuhair; Antika Prasetyaningtyas; Muhammad Syukron; Kukuh Trisna Pambudia; Faisal Hafizh Purnomo
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16276

Abstract

As crime rates rise and technology advances, security systems are becoming an essential necessity to protect assets and valuables. Conventional locks, which are easy to break into, lose, and duplicate, are no longer effective in maintaining security. As a solution, digital access systems such as the GM65 QR Code Sensor and AS608 fingerprint sensor are used to secure safes. Both technologies offer more practical, secure, and efficient access compared to conventional locks. The Sensor high performance in reading QR Codes, while the fingerprint sensor provides a permanent level of security, although it has limitations in wet or dusty conditions. The experimental results show that the success of opening the safe is influenced by the clean condition of the fingerprint and the proper distance of the barcode sensor. This research aims to improve the effectiveness of security systems by incorporating digital technology to prevent unauthorized access and protect valuable data.
Optimasi Hyperparameter CatBoost dengan Particle Swarm Optimization untuk Klasifikasi Hipertensi Muhammad Iqbal Al Afgany; Ani Dijah Rahajoe; Henni Endah Wahanani
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16292

Abstract

Hypertension is a cardiovascular disease affecting 11,952,694 residents aged ≥15 years in East Java in 2019, yet only 40.1% received healthcare services. This study aims to analyze the effect of Particle Swarm Optimization (PSO) on CatBoost algorithm performance in hypertension level classification. The research dataset combined data from Puskesmas Kepatihan Gresik (191 data) and Kaggle (12,500 data) divided with an 80:10:10 ratio. PSO was used for CatBoost hyperparameter optimization including iterations, depth, learning_rate, and l2_leaf_reg. Model evaluation utilized accuracy, precision, recall, and F1-score metrics. Results show that CatBoost with PSO optimization achieved 96% accuracy with optimal configuration of iterations=100, depth=3, learning_rate=0.055, and l2_leaf_reg=3, 2% higher than without optimization (94%). This study proves the effectiveness of PSO in optimizing CatBoost hyperparameters for more accurate early hypertension detection
Penentuan Lokasi Optimal Fasilitas Instalasi Gawat Darurat (IGD) di Kota Palembang Menggunakan Metode Weighted Aggregated Sum Product Assessment (WASPAS) Lydia Putri Prasanti; Sisca Octarina; Fitri Maya Puspita
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16297

Abstract

Fast and appropriate accessibility to Emergency Room (IGD) facilities was a crucial factor in handling critical, life-threatening conditions. This study aimed to determine the optimal IGD location by applying the Weighted Aggregated Sum Product Assessment (WASPAS) method. This research utilized data from 23 hospitals equipped with IGD facilities distributed across 13 districts in Palembang City. The evaluation was conducted based on three main criteria, service level, travel distance, and travel time from each district to the hospitals with IGD facilities. The results presented the top three hospital recommendations (ranked 1st, 2nd, and 3rd) for each district, which provided definite priority options for the community. Practically, these recommendations served as a significant strategic foundation for policymakers and the Health Office in planning health service distribution and ensuring more effective, data-driven emergency mitigation in Palembang City.
Rancang Bangun Sistem Deteksi Dini Kebakaran Berbasis Drone dengan Pengolahan Citra Digital pada Raspberry Pi Eka Susanti; Yessy Marniati; Muhammad Hanif Fatin; Cindy Apriliya; Melna Evanti Relointri
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 8 No. 1 (2026): Juni 2026 (forthcoming Issue)
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v8i1.16314

Abstract

Fires are a common disaster that are difficult to detect early. This study designed and built a drone-based early fire detection system using digital image processing on a Raspberry Pi. The system is equipped with a camera as the main sensor to capture images of the environment, which are then analyzed using a real-time fire color detection method. The Raspberry Pi functions as the data processing center, while the ESP32 module is used for data communication and device control. The location of the fire is identified through a GPS module, enabling accurate position monitoring. Detection results are automatically sent via the Telegram application, making it easier for users to respond to incidents. Test results show that the system is capable of detecting potential fires with fast response and high accuracy in various lighting conditions. This system is expected to be an effective solution in supporting efficient and real-time forest fire mitigation efforts
Sistem Pemantauan Gas Gunungapi Berbasis IoT dan Energi Surya untuk Mitigasi Bencana di Gunung Bromo Hartawan Abdillah; Wahyu Andrian Kusuma; Mas Ahmad Baihaqi; Alief Muhammad; Indah Noor Dwi Kusuma Dewi
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 2 (2025): Desember 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i2.16324

Abstract

This study presents the design of an IoT-based volcanic gas monitoring system powered by solar energy. The system integrates H₂S and CO₂ sensors with an ESP32 microcontroller, transmitting data in real time to a cloud dashboard via MQTT/HTTP protocols. A 100–300 Wp solar panel generated an average of 21 V and 2.1 A (≈529 Wh/day), significantly exceeding the sensor’s energy demand of ≈24 Wh/day. Field testing at Mount Bromo recorded average concentrations of H₂S = 0 ppm and CO₂ = 599 ppm, which are below hazardous thresholds but require continuous observation. The results demonstrate that the system is energy-efficient, stable under variable conditions, and effective in providing early warning alerts, thus supporting volcanic disaster mitigation and aligning with SDGs 9 and 13.

Page 13 of 13 | Total Record : 129

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