Abstract:This study aims to create and implement a physics learning visualization tool that can be used to determine sound intensity. This teaching aid is designed to help students understand physics concepts related to sound waves…
es and their measurements in a more interactive and practical way. The research method used was a review of 20 articles. The results of literature studies can help students better understand the concept of sound intensity. They have the ability to directly see changes in sound intensity through interactive teaching aids. Based on the research results, it was concluded that this physics learning aid not only helps in learning the concept of sound intensity, but also increases students' motivation and interest in learning. The use of teaching aids/visualization is recommended in physics education at the upper secondary education level or equivalent, as an innovative and efficient learning medium.
Abstract:Abstract : Excessive use of the internet can interfere with health so that it will be classified as internet addiction (internet addiction) which can have an impact on the health of users and their social life. A solution…
n is needed for the increasing growth rate of internet users every year, especially in Indonesia. Until now, there are no findings or an application for diagnosing internet addiction that can be used in general so that it can reduce the intensity of surfing in cyberspace. Therefore, for the initial stage it is necessary to have an application that can diagnose the initial internet addiction. By utilizing computer programming algorithms such as PHP and supported by inference engines such as Case Based Reasoning (CBR) so that it can replace an expert to be able to diagnose early symptoms by utilizing a knowledge base such as symptoms or facts about a disease, especially internet addiction. Based on the test results, the system designed can provide predictive values about internet addiction, then the machine will perform a search and issue the results of the diagnosis and the best possible solution.
Keywords: Expert System; Case Based Reasoning; Internet Addiction.
Abstrak : Penggunaan internet yang berlebihan dapat mengganggu kesehatan sehingga akan tergolong dalam internet addiction (kecanduan internet) yang dapat berdampak pada kesehatan pengguna dan kehidupan sosial mereka. Diperlukan suatu solusi atas meningkatnya angka pertumbuhan pengguna internet setiap tahunnya khususnya di Indonesia. Hingga saat ini belum adanya temuan atau sebuah aplikasi untuk mendiagnosa kecanduan internet yang dapat digunakan secara umum sehingga dapat mengurangi intensitas berselancar di dunia maya. Oleh karena itu untuk tahap awal perlu adanya suatu aplikasi yang dapat mendiagnosa awal kecanduan internet tersebut. Dengan memanfaatkan algoritma pemrograman komputer seperti PHP serta didukung oleh inferensi engine seperti Case Based Reasoning (CBR) sehingga dapat menggantikan seorang pakar untuk dapat mendiagnosa gejala awal dengan memanfaatkan basis pengetahuan seperti gejala-gejala atau fakta mengenai suatu penyakit khususnya penyakit kecanduan internet. Berdasarkan hasil pengujian sistem yang dirancang dapat memberikan nilai prediksi tentang penyakit kecanduan internet, kemudian mesin akan melakukan penelusuran serta mengeluarkan hasil diagnosa dan kemungkinan solusi terbaik.
Kata Kunci : Sistem Pakar; Case Based Reasoning; Kecanduan Internet.
Abstract:The design of a lighting automation system for dragon fruit plants uses an LDR sensor as a light intensity detector. This system is supported by a solar module with a capacity of 10-20 watts to supply power to a 12V battery…
ery which is paralleled to 24V. This voltage was then changed by the inverter to 220VAC to light 10 lights as research samples. Tests show that the LDR sensor works optimally at 5VDC voltage. If the voltage supplied is less or more than 5VDC, the sensor cannot function properly. Analysis of the conversion of ADC values to output voltage shows consistent results according to the test table. In addition, using 12VDC voltage directly on the LDR causes the sensor to not function because the LDR is designed for low voltage (≤5V). Without a suitable resistor, excessive current can damage sensor components. The system design is able to minimize the use of electricity sources from PLN and is an energy-saving solution for lighting dragon fruit plants in the field.
Keywords: agriculture sustainable; dragon fruit trees; photosynthesis; renewable energy;solar cells
Abstrak: Rancangan sistem otomatisasi lampu pada tanaman buah naga menggunakan sensor LDR sebagai pendeteksi intensitas cahaya. Sistem ini didukung oleh modul surya berkapasitas 10-20 watt untuk menyuplai daya ke baterai 12V yang diparalel menjadi 24V. Tegangan ini kemudian diubah oleh inverter menjadi 220VAC untuk menyalakan 10 lampu sebagai sampel penelitian. Pengujian menunjukkan bahwa sensor LDR bekerja optimal pada tegangan 5VDC. Jika tegangan yang diberikan kurang atau lebih dari 5VDC, sensor tidak dapat berfungsi dengan baik. Analisis konversi nilai ADC ke tegangan output menunjukkan hasil yang konsisten sesuai tabel pengujian. Selain itu, penggunaan tegangan 12VDC langsung pada LDR menyebabkan sensor tidak berfungsi karena LDR dirancang untuk tegangan rendah (≤5V). Tanpa resistor yang sesuai, arus yang berlebih dapat merusak komponen sensor. Rancangan sistem mampu meminimalisir penggunaan sumber listrik dari PLN dan menjadi solusi hemat energi untuk penerangan tanaman buah naga di lapangan.
Kata kunci: energi terbarukan; fotosintesis; pertanian berkelanjutan; pohon buah naga; solarcell
Abstract:Abstract: The advancement of smart agriculture has become a promising solution to increase food productivity and land use efficiency in urban environments. This research aims to develop an Artificial Intelligence (AI)-based…
sed vertical hydroponic farming system integrated with LED grow light technology and catfish aquaponics. The proposed system combines vertical hydroponics and aquaponics to optimize plant growth and water utilization. Internet of Things technology enables real-time environmental monitoring through an Arduino Uno microcontroller integrated with LDR, soil moisture, pH, and NPK sensors. The obtained sensor data is processed using the Mamdani Fuzzy Logic algorithm, which performs fuzzification, rule inference, aggregation, and defuzzification to generate adaptive control decisions for irrigation, nutrient circulation, and LED grow light intensity. This research uses the Research and Development (R&D) method through prototype development and performance evaluation for 30 days using spinach (Amaranthus spp.) and mustard greens (Brassica juncea) as test plants. Experimental results showed that the developed system successfully maintained stable environmental conditions, with soil moisture ranging between 69–72%, a pH value between 6.4 and 6.6, and optimal nutrient availability. Plant growth increased significantly. The integration of IoT, AI and aquaponics improves cultivation efficiency, enabling environmental control as a smart and sustainable solution for urban agriculture.
Keywords: artificial intelligence; aquaponic; hydroponic; LED grow light; vertical farming
Abstract: Kemajuan pertanian cerdas telah menjadi solusi yang menjanjikan untuk meningkatkan produktivitas pangan dan efisiensi penggunaan lahan di lingkungan perkotaan. Penelitian ini bertujuan untuk mengembangkan sistem pertanian hidroponik vertikal berbasis Kecerdasan Buatan (AI) yang terintegrasi dengan teknologi lampu tumbuh LED dan aquaponik ikan lele. Sistem yang diusulkan menggabungkan hidroponik vertikal dan aquaponik untuk mengoptimalkan pertumbuhan tanaman dan pemanfaatan air. Teknologi Internet of Things memungkinkan pemantauan lingkungan secara real-time melalui mikrokontroler arduino uno yang terintegrasi dengan sensor LDR, kelembaban tanah, pH, dan NPK. Data sensor yang diperoleh diproses menggunakan algoritma Logika Fuzzy Mamdani, yang melakukan fuzzifikasi, inferensi aturan, agregasi, dan defuzzifikasi untuk menghasilkan keputusan kontrol adaptif untuk irigasi, sirkulasi nutrisi, dan intensitas lampu tumbuh LED. Penelitian ini menggunakan metode Pengembangan (R&D) melalui pengembangan prototipe dan evaluasi kinerja selama 30 hari menggunakan bayam (Amaranthus spp.) dan sawi hijau (Brassica juncea) sebagai tanaman uji. Hasil eksperimen menunjukkan bahwa sistem yang dikembangkan berhasil mempertahankan kondisi lingkungan yang stabil, dengan kelembaban tanah berkisar antara 69–72%, nilai pH antara 6,4 dan 6,6, dan ketersediaan nutrisi yang optimal. Pertumbuhan tanaman meningkat secara signifikan. Integrasi IoT, AI dan aquaponik meningkatkan efisiensi budidaya, untuk pengendalian lingkungan sebagai solusi cerdas dan berkelanjutan untuk pertanian perkotaan.
Keywords: aquaponik; kecerdasan buatan; hidroponik; lampu tumbuh LED; pertanian vertikal
Abstract:Abstract: The growing intensity of cyber attacks, marked by rapid, large-scale, automated, and adaptive execution, requires analytical methods that represent the diversity of network environments, including variations in…
target platforms such as IoT, traditional networks, and hybrid infrastructures. This study compares machine learning models for cyber attack classification under heterogeneous environmental conditions and formulates a conceptual optimization framework based on model performance. Four publicly available benchmark datasets were used, namely UNB CIC IoT 2023, UNB CIC IDS-2018, UNSW-NB15, and a Kaggle cyber security attacks dataset, comprising approximately 40,000 to over 3.6 million records and 25 to 80 features across IoT, conventional, and mixed network environments. Random Forest, XGBoost, Multilayer Perceptron, and Transformer were implemented within a unified pipeline involving preprocessing, feature selection, and Bayesian Optimization-based hyperparameter tuning. All models achieved F1-score and Cohen's Kappa above 96%, with XGBoost performing best (97.80%, 97.26%), followed by Random Forest (97.78%, 96.96%) and Transformer (97.44%, 96.82%), while MLP scored lowest (96.74%, 96.00%), a gap below one percentage point. Confusion matrix analysis revealed persistent misclassification in minority and overlapping attack classes, informing a proposed adaptive cyber attack simulation optimization framework.
Keywords: cyber attacks; optimization; machine learning; environmental variability.
Abstrak: Meningkatnya intensitas serangan siber yang berlangsung cepat, masif, otomatis, dan adaptif menuntut pendekatan analitis yang merepresentasikan keragaman lingkungan jaringan, termasuk perbedaan karakteristik platform sasaran seperti Internet of Things (IoT), jaringan konvensional, dan infrastruktur hibrida. Penelitian ini membandingkan model machine learning untuk klasifikasi serangan siber pada kondisi lingkungan heterogen, sekaligus menyusun kerangka optimasi konseptual berdasarkan performa model. Empat dataset benchmark publik digunakan, yaitu UNB CIC IoT 2023, UNB CIC IDS-2018, UNSW-NB15, serta dataset Kaggle cyber security attacks, dengan jumlah data berkisar 40.000 hingga lebih dari 3,6 juta rekaman dan 25 sampai 80 fitur, mewakili lingkungan IoT, konvensional, dan campuran. Random Forest, XGBoost, Multilayer Perceptron, dan Transformer diimplementasikan melalui pipeline terpadu mencakup pra-pemrosesan, seleksi fitur, dan optimasi hyperparameter berbasis Bayesian Optimization. Seluruh model mencapai F1-score dan Cohen's Kappa di atas 96%, dengan XGBoost menunjukkan performa terbaik (97,80%, 97,26%), diikuti Random Forest (97,78%, 96,96%) dan Transformer (97,44%, 96,82%), sementara MLP mencatat skor terendah (96,74%, 96,00%), dengan selisih kurang dari satu poin persentase. Analisis confusion matrix mengungkap misklasifikasi yang konsisten pada kelas minoritas dan serangan dengan karakteristik serupa, yang menjadi dasar kerangka optimasi simulasi serangan siber adaptif yang diusulkan.
Kata kunci: serangan siber; optimasi; machine learning; variabilitas lingkungan
Abstract:Abstract: Conventional semiconductor chip counting at PT Elektronik Indonesia relies on manual weighing, which is prone to human error and inefficiency. This study proposes a desktop-based counting system using a digital…
scanner and image processing. The novelty lies in integrating horizontal-vertical projection with probabilistic Hough transform to robustly detect grid lines, form square cells, and enable accurate unit estimation via average intensity analysis, eliminating the need for reference weighing. Experiments on 15 actual chip images yielded an error rate of 0.009519% and up to 73.674%time efficiency gains compared to the manual method. The system reduces operator dependency, minimizes errors, and accelerates counting, providing a practical machine vision solution for semiconductor production.
Keywords: chip counting; image processing; probabilistic hough transform; grid line detection; time effeciency.
Abstrak: Penghitungan chip semikonduktor konvensional di PT Elektronik Indonesia bergantung pada penimbangan manual, yang rentan terhadap kesalahan manusia dan kurang efisien. Penelitian ini mengusulkan sistem penghitungan berbasis desktop menggunakan scanner digital dan pengolahan citra. Kebaruan terletak pada integrasi proyeksi horizontal-vertikal dengan probabilistic Hough transform untuk mendeteksi garis grid secara kuat, membentuk sel persegi, serta memungkinkan estimasi unit akurat melalui analisis intensitas rata-rata, sehingga menghilangkan kebutuhan penimbangan referensi. Eksperimen pada 15 citra chip aktual menghasilkan tingkat kesalahan 0,009519% dan peningkatan efisiensi waktu hingga 73,674% dibandingkan metode manual. Sistem ini mengurangi ketergantungan operator, meminimalkan kesalahan, dan mempercepat penghitungan, menyediakan solusi machine vision praktis untuk produksi semikonduktor.
Kata kunci: penghitungan chip; pengolahan citra; probabilistic Hough transform; deteksi garis grid; efisiensi waktu.
Abstract:Face recognition has become a common thing used in the field of surveillance and security in computer technology and image devices. This study aims to identify the usefulness of a person's face on 3 test images. This study…
dy examines the methods of cropping techniques, image enhancement through intensity measurement, and histogram analysis to improve the contrast and distribution of image intensity. In addition, the Viola-Jones algorithm is used to detect key facial features such as eyes, nose, and mouth. The results of the analysis are then applied in the feature evaluation stage, where usually between facial features are applied to measure the ratio of facial proportions. Furthermore, the comparison of proportional ratios of several images was analyzed using bar graphs and line graphs to evaluate the trend and stability of facial proportions. The results showed the best ratio stability with a smaller variation of the on-off ratio of image 2 which is 0.4762 pixels to 0.4983 pixels. Image 2 is the most ideal for face measurement systems based on geometric ratios because it provides more consistent and visible results.
Abstract:Penelitian ini bertujuan mengidentifikasi jenis tumbuhan paku (Pteridophyta) dan tingkat keanekaragamannya di Desa Terentang Baru, Kecamatan Batin XXIV, Jambi. Penelitian dilaksanakan pada Mei 2026 menggunakan metode survei…
vei eksploratif dengan teknik purposive sampling dan metode jelajah. Hasil penelitian menemukan 10 spesies tumbuhan paku yang tergolong dalam 9 genus dan 8 famili. Nilai indeks keanekaragaman Shannon-Wiener (H') sebesar 2,18 (kategori sedang) dan indeks kemerataan (E) sebesar 0,95 (kategori tinggi). Kondisi lingkungan berupa suhu 28°C, kelembapan 82%, pH tanah 6,4, dan intensitas cahaya 1.200 Lux mendukung pertumbuhan tumbuhan paku. Keanekaragaman tumbuhan paku di lokasi penelitian tergolong cukup baik dan berpotensi menjadi data dasar inventarisasi flora lokal serta konservasi keanekaragaman hayati.
This study aimed to identify fern (Pteridophyta) species and determine their diversity level in Terentang Baru Village, Batin XXIV District, Jambi. Conducted in May 2026 using an exploratory survey, purposive sampling, and roaming methods, the study identified 10 fern species belonging to 9 genera and 8 families. The Shannon-Wiener diversity index (H') was 2.18 (moderate), while the evenness index (E) was 0.95 (high). Environmental conditions, including a temperature of 28°C, humidity of 82%, soil pH of 6.4, and light intensity of 1,200 Lux, supported fern growth. The findings indicate relatively good fern diversity and provide baseline data for local flora inventory and biodiversity conservation.
Abstract:Tiakur City, the capital of Southwest Maluku Regency, has undergone significant physical development between 2015 and 2025, driven by population growth and economic activities. This study employs a quantitative approach…
using remote sensing technology with PlanetScope satellite imagery to analyze land cover changes. The analysis reveals an increase in built-up land area from 171.29 hectares (7.31%) in 2015 to 395.66 hectares (16.89%) in 2025, while non-built-up land experienced a decline. These findings indicate a rapid development rate and highlight the importance of sustainable spatial planning. In conclusion, understanding the patterns and intensity of land cover changes in Tiakur City is crucial for evaluating spatial planning policies and improving infrastructure development planning for the future.
Abstract:Tax avoidance represents a strategic maneuver by taxpayers to minimize their tax burden by capitalizing on the intricacies of tax legislation. This complex phenomenon encompasses a range of tactics, including leveraging…
exemptions, deductions, tax incentives, non-taxable income, deferring tax liabilities, and, regrettably, engaging in unethical practices such as bribery and forgery. This study seeks to unravel the intricate relationships between profitability, solvency, capital intensity, and company size regarding tax avoidance within the manufacturing sector, specifically targeting food and beverage firms listed on the Indonesia Stock Exchange from 2017 to 2022. Employing the Cash Effective Tax Rate (CETR) as a proxy for tax avoidance, we meticulously selected a sample of 70 companies through purposive sampling based on rigorous criteria. Our analysis, conducted via multiple linear regression using SPSS 25, reveals compelling insights: profitability, solvency, and capital intensity significantly bolster tax avoidance strategies, while larger company size appears to dampen these efforts. Collectively, these factors create a multifaceted influence on tax avoidance behaviors, highlighting the intricate dynamics at play within the corporate landscape.