JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer)
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.
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<![CDATA[Optimalisasi Mesin Hand Sanitizer Otomatis berbasis Mikrokontroler dengan Sensor Inframerah ]]>
<![CDATA[Subhiyanto Subhiyanto]]>;
<![CDATA[Ista Rahma Nissa]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.11568
<![CDATA[In 2020, the world was hit by the coronavirus pandemic, including Indonesia. According to WHO, millions were infected and thousands died. The Indonesian government responded with several policies, including learning from home. As vaccination programs progressed, some regions began entering the new normal era. Schools resumed limited face-to-face learning by following protocols set by the Joint Decree of Four Ministries (SKB 4 Kementerian). This study, based on analysis and literature review, uses the System Development Life Cycle (SDLC) method to develop an innovative solution involving infrared sensors, commonly used in automation projects. These sensors are proven to be precise, effective, and efficient in implementing automatic hand sanitizer machines. The machine supports COVID-19 health protocols by reducing physical contact and helping prevent virus transmission.]]>
<![CDATA[Implementasi Modified K-Nearest Neighbor (MKNN) untuk Deteksi Penyakit Anemia ]]>
<![CDATA[Putra Dwi Wira Gardha Yuniahans]]>;
<![CDATA[Anggraini Puspita Sari]]>;
<![CDATA[Yisti Vita Via]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.13425
<![CDATA[Anemia is a condition where the hemoglobin level in the human body drops below the normal threshold. It can cause several negative effects, such as delayed psychomotor development, a higher risk of infectious diseases, and in women, the possibility of premature birth. Therefore, early detection of anemia is essential to speed up treatment and recovery. One method that can support the diagnostic process is machine learning, particularly the Modified K-Nearest Neighbor (MKNN) algorithm. MKNN is an improved of standard KNN, incorporating additional steps such as validity calculation and weighted voting, which are not present in the original version. In this study, MKNN was applied to detect anemia and achieved an accuracy of 84% using a 75:25 train-test data split and k=5. The dataset was collected from Jemursari Hospital in Surabaya, consisting of 100 patient records. These records were used to evaluate the performance of the MKNN algorithm in anemia detection.]]>
<![CDATA[Sistem Distribusi Air Bersih Berbasis IoT dengan ESP8266 dan RTC untuk Optimalisasi Waktu Pengaliran ]]>
<![CDATA[Rama Noveliandra]]>;
<![CDATA[Rissa Nurfitriana Handayani]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.15264
<![CDATA[Efficient clean water distribution is essential to meet the needs of communities in various regions. This study aims to develop an Internet of Things (IoT)-based clean water distribution system using ESP8266 as the main controller for automatic and scheduled water flow timing. This system is able to regulate the opening and closing of taps on a schedule and allows manual control via mobile phone devices. The method used includes the integration of IoT technology with the Blynk application for real-time monitoring and control. The results of the study show that this system can optimize the use of water resources, reduce waste, and ensure a more regular distribution of clean water. In addition, the flexibility of control via mobile phones makes it easy for users to manage water distribution. This study offers an innovative solution that can be applied to improve the efficiency of clean water distribution in various regions]]>
<![CDATA[Desain dan Pengembangan Aplikasi Mobile Daur Ulang Sampah di Kota Surabaya dengan Metode Design Thinking ]]>
<![CDATA[Maorisha Virginia]]>;
<![CDATA[Made Kamisutara]]>;
<![CDATA[Achmad Zakki Falani]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.15295
<![CDATA[The issue of waste management in Surabaya City remains a challenge that requires innovative, technology-based solutions. The aim of this research is to design and develop a mobile application that supports waste recycling in order to enhance community engagement and improve waste management in a more effective and sustainable manner. This study employs the Design Thinking method to formulate problem-solving approaches, understand user needs, and test the effectiveness of the proposed design. The mobile application design and development process involves five stages: empathize, define, ideate, prototype, and test. The research results in a prototype application equipped with key features such as recycling education, location-based waste pick-up and drop-off services, and a loyalty points system to reward users. The presence of this application is expected to increase public awareness of sorting and recycling waste and contribute to environmental sustainability programs in Surabaya City.]]>
<![CDATA[Prediksi Keterlambatan Pembayaran Mahasiswa untuk Mitigasi Risiko Cuti Menggunakan SVM Optimasi PSO ]]>
<![CDATA[Hafis Nurdin]]>;
<![CDATA[Imam Nawawi]]>;
<![CDATA[Anus Wuryanto]]>;
<![CDATA[Dewi Yuliandari]]>;
<![CDATA[Hari Sugiarto]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.15483
<![CDATA[Delayed tuition payments present challenges for higher education institutions, impacting both financial stability and students’ academic progress. This study proposes a predictive model using Support Vector Machine (SVM) optimized by Particle Swarm Optimization (PSO) to identify students at risk of payment delays. The dataset includes academic and social attributes. A dot kernel SVM was evaluated using 10-fold cross-validation. Results show that PSO optimization significantly improved model performance, particularly in recall, which increased from 36.10% to 65.51%, indicating better identification of delayed payment cases. The analysis also reveals that social factors, such as employment and academic status, strongly influence prediction outcomes. These findings highlight the potential of the SVM-PSO model as a decision-support tool for early intervention, enabling institutions to mitigate dropout risks and enhance financial planning. By leveraging this approach, universities can better support students while maintaining administrative efficiency and institutional sustainability.]]>
<![CDATA[Optimalisasi Deteksi Wajah Real-Time Menggunakan HAAR Cascade Classifier berbasis OpenCV ]]>
<![CDATA[Alfan Rizaldy Pratama]]>;
<![CDATA[Muhammad Nasrudin]]>;
<![CDATA[Andri Faudzan Adziima]]>;
<![CDATA[Shindi Shella May Wara]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.15485
<![CDATA[Nowadays, the face is one of the features that is widely used in various aspects of life such as security which includes access control and surveillance, biometrics which includes attendance systems, and many others. The obstacles found in implementing this are generally about speed performance when detecting, this is vital because if the process takes a long time, misconceptions and system errors will occur. HAAR Cascade Classifier is one of the most widely used lightweight face detection algorithms. In this research, by analyzing the use of grayscale color compared to RGB, a performance increase of 6.17% is obtained with an average FPS on RGB of 25.63 while on grayscale it is 27.21.]]>
<![CDATA[Prediksi Hasil Produksi Beras di Kabupaten Lamongan Menggunakan Stochastic Frontier Analysis (SFA) ]]>
<![CDATA[Imelda Widya Ningrum]]>;
<![CDATA[Dwi Arman Prasetya]]>;
<![CDATA[Trimono]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.15556
<![CDATA[The agricultural sector plays a crucial role in the Indonesian economy, especially in maintaining food estate and economic stability. This study aims to identify and improve the technical efficiency of rice production in Indonesia using Stochastic Frontier Analysis (SFA). Agricultural data were analyzed through validation, cleaning, feature selection, and modeling with a log-linear Cobb-Douglas production function estimated using Maximum Likelihood Estimation (MLE). Model performance was evaluated on training and test data using Log-likelihood, R-squared, and Mean Absolute Percentage Error (MAPE). The results showed good model prediction performance on test data (R-squared = 0.6658 and MAPE = 14.34%). Technical inefficiency analysis indicated that the level of inefficiency among farmers in Lamongan Regency was relatively low and homogeneous. However, the efficiency frontier analysis identified significant opportunities to increase rice yields through more efficient management of production factors and reduction of inefficiencies]]>
<![CDATA[Analisis Potensi Sampah di Kuantan Singingi untuk Pembangkit Listrik Tenaga Sampah (PLTSa) Landfill Gas (LFG) ]]>
<![CDATA[Boy Ihsan]]>;
<![CDATA[Dicky Pangindra]]>;
<![CDATA[Iswadi Hasyim Rosma]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.15607
<![CDATA[Waste Power Plant (PLTSa) is one of the solutions to overcome waste problems and as electricity supply. This study analyzes the technical and economic feasibility of building a PLTSa at the Muaro Sentajo Landfill, Kuantan Singingi Regency, which uses the sanitary landfill method. The organic waste produces landfill gas (LFG), especially methane, which can be used as fuel for power generation. The estimated LFG content was calculated using the U.S. Environmental Protection Agency model and Landfill Gas Emmisions Model (LandGEM) software. The results show that by the end of the operation period, the landfill can produce 2,966,400 m³ of methane gas capable of operating a power plant with output of 2.39 MW. The analysis shows that the project is financially feasible, with a Net Present Value (NPV) of Rp13.8 billion, Benefit-Cost Ratio (BCR) of 1,1648, Internal Rate of Return (IRR) of 14.2%, and Payback Period of 11 years 8.3 months]]>
<![CDATA[Prediksi Volatilitas Saham KINO dan MRAT menggunakan Model BEKK-MGARCH ]]>
<![CDATA[Renaldy Al Ikhsan]]>;
<![CDATA[Wahyu Syaifullah Jauharis Saputra]]>;
<![CDATA[Kartika Maulida Hindrayani]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.15639
<![CDATA[This study analyzes the volatility prediction of KINO and MRAT stocks using the BEKK-MGARCH model during January 2019 to December 2024. Both stocks exhibit high price fluctuations, with volatility significantly influenced. Persistence effects are more dominant, with asymmetric spillover where KINO's influence on MRAT is stronger. Conditional correlation shows a shift from positive to negative in the 30-day forecast. Model evaluation demonstrates low RMSE values of 2.05×10⁻⁵ (KINO), 3.38×10⁻⁵ (MRAT), and 4.42×10⁻⁵ (covariance), indicating excellent predictive performance and confirming the reliability of the BEKK-MGARCH model with exponential smoothing in forecasting the volatility dynamics and relationship between these two stocks with high precision. However, the Jarque-Bera test rejects residual normality (p < 2.2×10⁻¹⁶), and the Ljung-Box test detects autocorrelation, suggesting the need for more complex models such as Student-t distribution or asymmetric models. These findings provide important insights for investors in managing risk and portfolio diversification strategies in the cosmetics sector.]]>
<![CDATA[Pembuatan Sistem Penjualan Aset 3D Blender berbasis Web menggunakan Metode Waterfall ]]>
<![CDATA[Mahesa Dzikri Kurniawan]]>;
<![CDATA[Bagus Hardika]]>;
<![CDATA[Daffarizqy Prastowiyono]]>;
<![CDATA[Muhammad Adzka]]>;
<![CDATA[Aditya Wicaksono]]>;
<![CDATA[Muhammad Nasir]]>
<![CDATA[ JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025 ]]>
Publisher : <![CDATA[Universitas Merdeka Malang ]]>
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DOI: 10.26905/jasiek.v7i1.15694
<![CDATA[This research developed "3Dify," a web-based 3D Blender asset sales system, employing the Waterfall methodology. Its primary goal is to efficiently facilitate 3D asset acquisition, purchasing, and downloading for creators and users across diverse fields, including education and the creative industry. The development process encompassed needs analysis, UML-based design, implementation using Laravel and MySQL, and functional Black Box testing based on use cases. Implementation results confirm all features operate as expected, from administrator product management to user transactions and downloads. The system significantly enhances the efficiency of 3D asset search and distribution, demonstrating strong potential for future evolution into a digital asset e-commerce platform. Achieving a 90.91% success rate from 44 testing scenarios, this study validates the Waterfall approach's effectiveness in constructing a reliable and structured 3D asset sales system.]]>
