Penalaan Pengontrol PID untuk Kecepatan Kecepatan Motor DC pada Robot Pengangkat Anak Timbangan

The rapid development of technology allows human work to be replaced by robot technology. The most frequently used robot in industry is the robot arm. The robot arm can imitate the human arm's characteristics, so it is often used to help humans lift and move goods. With this principle, the robot arm can be used as a weight-lifting robot to aid in calibrating electronic scales. This paper analyzes the control of the DC motor on a weighing-scale lifting robot arm by optimizing the overshoot with PID (Proportional - Integral - Derivative) control. The PID Control test results on the DC motor rotation are stable at 100 rpm with a steady state error of 0%. The system's response to the DC motor has a settling time of 1,26 s and an overshoot of 2%.Perkembangan teknologi yang semakin pesat memungkinkan pekerjaan manusia tergantikan oleh teknologi robot. Robot yang paling sering digunakan dalam industri adalah robot lengan. Robot lengan dapat meniru ciri-ciri lengan manusia sehingga sering digunakan untuk membantu manusia mengangkat dan memindahkan barang. Dengan prinsip tersebut, robot lengan dapat digunakan sebagai robot pengangkat beban untuk membantu kalibrasi timbangan elektronik. Penelitian ini menganalisis pengontrolan motor DC pada bagian alas robot pengangkat anak timbangan dengan melakukan minimisasi overshoot dengan kontrol PID (Proporsional – Integral – Derivatif). Hasil pengujian Kontrol PID pada pengontrolan kecepatan motor DC tunak pada putaran 100 rpm dengan kesalahan tunak sebesar 0%. Respon sistem terhadap motor DC mempunyai settling time sebesar 1,26s, dan overshoot sebesar 2%

Securing IoT-Cloud Applications with AQ-KGMO-DMG Enhanced SVM for Intrusion Detection

In contemporary society, the Internet has evolved into an indispensable facet of daily life, serving myriad functions across various domains. Intrusion detection, as a cornerstone of information security, plays a pivotal role in fortifying networks against potential threats, emphasizing the necessity for robust and reliable methods capable of discerning and mitigating network vulnerabilities effectively. In this work, a pioneering network intrusion detection model is introduced, leveraging Adaptive Quantum-Inspired KGMO with Dynamic Molecular Grouping (AQ-KGMO-DMG) for feature selection and employing Simplified Support Vector Machines (SVM) for the classification of intrusion data. The utilization of the UNSW-NB15 dataset serves as the litmus test for evaluating the efficacy of the developed intrusion detection model. Notably, this approach enhances the accuracy in categorizing classes with minimal instances while concurrently mitigating the false alarm rate (FAR). A notable innovation in this methodology involves the transformation of raw traffic vector data into a visual representation, thereby reducing computational costs significantly. To reduce the computation cost further, the raw traffic vector data is converted into picture format. The experimental findings showed that the proposed model performed better than conventional techniques in terms of FAR, accuracy, and computation cost

Mitigating Flood Peak Discharge with Biopore Absorption Holes (BAH) to Reduce Surface Runoff: Case Study of the Tanralili Sub-watershed

Land use changes in the Tanralili Sub-watershed have profoundly impacted its hydrological dynamics, leading to increased surface runoff and shorter return periods for peak flood discharges. Currently, a significant portion of the area, 75.51%, is dedicated to mixed dryland and wetland agriculture, leaving only 24.49% under forest or grass cover, which has rendered much of the land critical. This research examines the effectiveness of Biopore Absorption Holes (BAH) in mitigating flood risks by enhancing infiltration and reducing runoff. Experiments were conducted on soils with moderate permeability (0.00178 cm/s), utilizing PVC BAH units measuring 10 cm in diameter and 100 cm in length, equipped with biopores of 10 mm. These units were installed in parallel on a 0.23% slope and tested under various rainfall intensities (I2, I5, I10), determined using the Mononobe equation, while peak discharge was estimated with the Nakayasu Synthetic Unit Hydrograph (HSS Nakayasu). The results showed a 58.80% reduction in peak flood discharge and a 62.99% increase in infiltration. These findings underscore the potential of BAH as an eco-friendly solution for flood mitigation. Expanding the use of BAH on open lands is recommended to bolster watershed resilience and tackle the growing risks of flooding. &nbsp

Gaya Bahasa Repetisi Dalam Tindak Tutur Asertif Pada Wacana Debat Keempat Calon Wakil Presiden Indonesia 2024

This study investigates the role of repetition as a linguistic strategy in assertive speech acts within the debate discourse of the fourth vice-presidential candidates leading up to the 2024 election. Specifically, it examines the thematic relationships between repetitive figures of speech and assertive speech acts used by the first, second, and third vice-presidential candidates, utilizing NVivo 12 Plus for data visualization. Adopting a qualitative descriptive method, the study identifies instances of repetition in assertive speech acts, categorizing them into two primary functions: "stating" (three instances) and "explaining" (three instances). A pragmatic analysis reveals that repetition occurs at both the word and phrase levels, primarily serving to reinforce emphasis and strengthen the speaker's stance in political discourse. Moreover, NVivo 12 Plus analysis illustrates a hierarchical structure linking figures of speech, assertive speech acts, and their communicative functions. These findings underscore the strategic role of repetition as a persuasive tool in political debates, demonstrating its effectiveness in reinforcing arguments and enhancing audience recall. The study offers practical insights into political communication strategies, particularly for speechwriters, debate analysts, and politicians seeking to optimize message clarity and impact.Penelitian ini menyelidiki peran repetisi sebagai strategi linguistik dalam tindak tutur asertif dalam wacana debat empat calon wakil presiden menjelang Pemilu 2024. Secara khusus, penelitian ini menganalisis hubungan tematik antara majas repetisi dan tindak tutur asertif yang digunakan oleh calon wakil presiden pertama, kedua, dan ketiga, dengan memanfaatkan NVivo 12 Plus untuk visualisasi data. Dengan menggunakan metode deskriptif kualitatif, penelitian ini mengidentifikasi kemunculan repetisi dalam tindak tutur asertif yang dikategorikan ke dalam dua fungsi utama: "menyatakan" (tiga kali kemunculan) dan "menjelaskan" (tiga kali kemunculan). Analisis pragmatik menunjukkan bahwa repetisi terjadi pada tingkat kata dan frasa, terutama berfungsi untuk memperkuat penekanan dan mempertegas sikap penutur dalam wacana politik. Selain itu, analisis menggunakan NVivo 12 Plus mengungkapkan adanya struktur hierarkis yang menghubungkan majas repetisi, tindak tutur asertif, dan fungsi komunikatifnya. Temuan ini menegaskan peran strategis repetisi sebagai alat persuasif dalam debat politik, yang menunjukkan efektivitasnya dalam memperkuat argumen dan meningkatkan daya ingat audiens. Studi ini memberikan wawasan praktis tentang strategi komunikasi politik, khususnya bagi penulis pidato, analis debat, dan politisi yang ingin mengoptimalkan kejelasan serta dampak pesan mereka

Does the Occurrence of a High-Impact Temporary Incident Disrupt the SERVQUAL Model? Evidence from the Indian Hospitality Industry

The occurrence of COVID-19 made the authors seek to find out if the SERVQUAL model holds good during high-impact temporary incidents or if adding new dimensions can improve the satisfaction prediction. The motive of this research is to observe how the five dimensions of the SERVQUAL Model play out during an unusual high-impact temporary event like the COVID-19 pandemic to measure customer satisfaction, and if the COVID protocol measures adopted by the hospitality industry have any impact on the relative importance of the SERVQUAL dimensions on the overall satisfaction of the customers. This study conducted an online survey to gather relevant information. The researchers identified a select group of respondents using the non-probability sampling technique. This work used the Partial Least Squares (PLS) modeling technique to measure customer satisfaction. Adoption of COVID protocols significantly impacts customer satisfaction. Even when the hotel strictly follows the COVID protocols, the empathy and responsiveness shown by the hotel staff and the assurance guaranteed by the hotel about the safety and well-being of the customers have significantly contributed to improving customer satisfaction. The authors found that SERVQUAL as a model stood firm even during a high-impact temporary incident with a negligible increase in R2 value when the hotel industry adopted a new dimension specific to COVID-19 precautions

Prediksi Model Zonifikasi Wilayah Peri-urban Kota Bandung Bagian Timur

Urbanization pressure has driven the expansion of Bandung's urban area to the East, especially in Cileunyi, Rancaekek, and Jatinangor Districts. As a peri-urban area of Bandung City, which is a transition zone between urban and rural areas, the challenges of its development are increasingly complex, especially since the area has physical limitations but does not hinder land conversion. This study aims to predict land cover changes and zonification models in the Eastern peri-urban area of Bandung City using the Cellular Automata Markov model. The results indicated that urban growth in the peri-urban area of Bandung City, especially in Cileunyi District, occurred significantly, forming an urban-rural frame zone (zobikodes). This pattern indicates strong competition between development interests and environmental conservationefforts. This transformation indicates that urbanization in the peri-urban area is not only triggered by population growth but also by economic dynamics, accessibility, and spatial planning policies that have not been fully able to control urban sprawl. The conclusion of this study confirms that without stricter and evidence-based policy interventions, uncontrolled urban expansion risks accelerating environmental degradation, reducing ecological resilience, and threatening the sustainability of agricultural land. Therefore, the resulting zonification models can be the basis for formulating a more adaptive and sustainable spatial planning strategy to balance economic growth with environmental preservation in the peri-urban areas of Eastern Bandung City.Tekanan urbanisasi telah mendorong ekspansi wilayah perkotaan Bandung ke wilayah Timur, terutama di Kecamatan Cileunyi, Rancaekek, dan Jatinangor. Sebagai wilayah peri-urban Kota Bandung yang menjadi zona peralihan antara kawasan perkotaan dan perdesaan, tantangan pengembangannya semakin kompleks, wilayah tersebut memiliki keterbatasan secara fisik namun tidak menghambat terjadinya perubahan tata gunalahan. Penelitian ini bertujuan untuk memprediksi perubahan tutupan lahan dan pola zonifikasi di wilayah peri-urban Kota Bandung bagian Timur dengan menggunakan model Cellular Automata Markov. Hasil penelitian menunjukkan pertumbuhan perkotaan di wilayah peri-urban Kota Bandung, khususnya di Kecamatan Cileunyi, terjadi secara signifikan membentuk zona bingkai kota-desa (zobikodes). Hal ini mengindikasi adanya persaingan kuat antara kepentingan pembangunan dengan upaya pelestarian lingkungan. Model zonifikasi yang dihasilkan dapat menjadi dasar bagi perumusan kebijakan tata ruang yang lebih efektif untuk mengendalikan urban sprawl dan menjaga keseimbangan ekologis di wilayah peri urban

Negotiating the Waves and Tides of Life: Challenges, Opportunities, and Coping of Skimboarders in Dahican, Mindanao, Philippines

Employing qualitative methods, particularly phenomenological research designs, this study explored the lived experiences and coping strategies of skimboarders in Dahican, Mindanao.  Studies have shown varying effects of ecotourism on locals.  In this study, the result shows the existence of affirmative and negative effects of tourism. Skimboarders faced physical struggles in learning the sport due to its technical difficulty, high temperatures, and exhaustion.  On the emotional and psychological struggles, dealing with unforgiving tourist who treats them as mere commodities or human beings being paid to serve at their disposal.  The wanton abuse of the environment, where tourists are inconsiderate of leaving trash anywhere along the coastlines.  On the other hand, the result also showed an affirmative effect on skimboarders.  Among these were livelihood chances. The tourism industry provides income for skimboarders through tutorials, and these fees are used for their daily expenses.  Further, improved interpersonal relations also appeared.  By dealing with tourists, skimboarders developed their skills in customer relations. Lastly, they improved their advocacy for the environment through marine life protection.  Coastal clean-ups and the development of turtle hatcheries increase their love for the environment, especially the sea.  The result of this study greatly contributes to the growing knowledge and literature on the lives of skimboarders by understanding their opportunities and challenges.

Implementasi Convolutional Neural Network Berbasis Model untuk Klasifikasi Kelayakan Citra Permen Jahe pada Perangkat Android

Ginger is one of the primary ingredients for ginger candy. The manual process of evaluating the feasibility of ginger candy at the Tasacika Company is still prone to errors and is less efficient. This research aims to develop a Convolutional Neural Network model for classifying the feasibility of ginger candy and create an Android-based application that facilitates this process. The research method uses an Experimental approach. Model development is carried out with a Convolutional Neural Network with the MobileNetV2 architecture, using the Cross Industry Standard Process for Data Mining methods. Software development is done using the Prototyping method. This research used a dataset of images taken directly from the Tasacika Company's ginger candy factory. The model is trained and tested using Google Colab with the Python programming language and the TensorFlow and Keras libraries. Implementation is carried out using Kotlin and XML. It can be concluded that the research has succeeded in developing a ginger candy feasibility classification model. The test results show that the developed model is effective in minimizing human error in the process of checking the feasibility of ginger candy. This research also succeeded in developing an Android-based ginger candy feasibility classification applicationJahe merupakan salah satu bahan dasar pembuatan permen jahe. Proses evaluasi kelayakan permen jahe di Perusahaan Tasacika yang masih dilakukan secara manual, masih rawan terjadi kesalahan dan kurang efisien. Penelitian ini bertujuan untuk mengembangkan model Convolutional Neural Network untuk klasifikasi kelayakan permen jahe dan membuat aplikasi berbasis android yang memudahkan proses tersebut. Metode penelitian menggunakan pendekatan eksperimental. Pengembangan model dilakukan dengan Convolutional Neural Network dengan arsitektur MobileNetV2, dan menggunakan metode Cross Industry Standard Process for Data Mining. Pengembangan perangkat lunak dilakukan dengan metode Prototyping. Penelitian ini menggunakan dataset berupa gambar yang diambil langsung dari pabrik permen jahe milik Perusahaan Tasacika. Model dilatih dan diuji menggunakan Google Colab dengan bahasa pemrograman Python, serta library TensorFlow dan Keras. Implementasi dilakukan menggunakan Kotlin dan XML. Dapat disimpulkan bahwa penelitian ini telah berhasil mengembangkan model klasifikasi kelayakan permen jahe. Hasil pengujian menunjukkan bahwa model yang dikembangkan efektif dalam meminimalisir human error pada proses pengecekan kelayakan permen jahe. Penelitian ini juga berhasil mengembangkan aplikasi klasifikasi kelayakan permen jahe berbasis Android

Striking a Balance Between Nature and Development: Investigating Private Green Spaces using ENVI-met

This research investigated the significant effects of private green spaces on air temperatures in Bekasi City. Previous analyses suggested that green spaces could lower air temperatures. Meanwhile, private green spaces, consisting of front and back yards, are a significant part of the concept. Software simulation (ENVI-met) was used to compare several housing scenarios for the tropical monsoon climate of Bekasi City. The scenarios consisted of housing configurations with the same unit size and number in an area of (49 x 49) m2. The results showed that the average air temperature reduction was mostly insignificant. On December 21, the scenarios with the highest and lowest average air temperatures differed by 0.42 ℃ at noon. In this context, the scenario with the most area of green space did not possess the lowest air temperature, due to the increase in building and pavement areas. Wind, sun position, surface area, and type of exposed area affected the outdoor air temperature. Further research could be conducted on innovations, especially regarding building and pavement materials to mitigate air temperature increases

Penyesuaian Konsep Identitas Sosial pada Korpus Ujaran Kebencian, Pendekatan Komputasional Linguistik

The identification of hate speech must be accompanied by the identification of social identity concepts. This study aims to provide an alternative corpus with text metadata and social identity based on relevant laws that are designed to be implemented in machine learning. Two key questions are addressed: what social identity semantic domains are realized in the corpus, and what are the accuracy measurement results from the corpus? To achieve these aims, the study adopts a mixed-methods approach: qualitative for the first question and quantitative for the second. This research falls under the broader umbrella of computational linguistics, utilizing semantic domain theory and natural language processing. The first approach shows that the corpus only contributes five out of nine formulated domains, dominated by negative (uncategorized), religion, and ethnicity. The second approach indicates suboptimal conditions in the annotation distribution of the corpus, despite an average accuracy rate of over 80%. This condition limits the model’s ability to generalize beyond the information within the corpus, especially regarding social identity categories that are not fully represented. This study differs from previous ones by focusing on data categorization based on more up-to-date legal sources. Future research could elaborate on this work by incorporating new language use concepts aligned with the corpus's original goal to detect hate speech.Identifikasi ujaran kebencian harus dibarengi dengan identifikasi konsep identitas sosial. Penelitian ini berupaya memberikan korpus alternatif dengan metadata teks dan identitas sosial berdasarkan hukum terkait. Untuk itu terdapat dua pertanyaan yang perlu di jawab, yaitu apa saja domain semantik identitas sosial yang terealisasi dalam korpus serta bagaimana hasil pengujian dari korpus tersebut. Dengan tujuan tersebut, penelitian ini mengadopsi metode penelitian campuran, yaitu kualitatif untuk pertanyaan pertama dan kuantitatif untuk pertanyaan kedua. Payung besar penelitian ini adalah Linguistik Komputasional yang memanfaatkan teori Domain Semantik dan perhitungan algoritma pembelajaran mesin. Teori tersebut digunakan untuk memproses data korpus ujaran kebencian sebagai luaran dari penelitian sebelumnya yang tersedia secara open-source. Hasil analisis memproyeksikan adanya kondisi yang kurang layak dari segi distribusi anotasi pada korpus, walaupun luaran pengujian akurasi memunculkan angka rata-rata di atas 80%. Kondisi ini mengakibatkan model mesin memiliki kemampuan terbatas hanya pada informasi di dalam korpus saja, sedangkan terdapat kategori identitas sosial yang pengetahuannya tidak termuat dalam korpus. Penelitian ini membedakan dengan penelitian sebelumnya dengan berfokus pada kategorisasi data berdasarkan sumber hukum terkait yang lebih mutakhir. Luaran penelitian dapat dilanjutkan dengan penambahan konsep penggunaan bahasa baru yang sesuai dengan tujuan awal korpus, yaitu mendeteksi ujaran kebencia