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How to Manage Numerical Abilities in Algebra Material? Munifah, Munifah; Romadhona, Annisa Nurhuda; Ridhona, Ilma; Ramadhani, Rahmi; Umam, Rofiqul; Tortop, Hasan Said
Al-Jabar: Jurnal Pendidikan Matematika Vol 10 No 2 (2019): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v10i2.5325

Abstract

Numerical ability is very help students understand the material, analyze any problems, and apply math concepts in daily life so that numerical abilities of students is a factor that can affect learning outcomes. Determine the effect of learning model Scramble and learning model with SAVI (Somatic, Auditory, Visual, and Intellegence) on the ability of numerical be the purpose of this article. The design of the research used Quasy Experimental Design, with the instrument used for the study in the form of test numerical ability. Data analysis used the T-test. Based on the results of the research concluded that the learning model Scrambler and learning model SAVI has a significant influence on numerical ability. And both of them is a model of learning which is equally effective against numerical abilities in order to improve learning outcomes is more optimal. But model pembelajaran SAVI is more effective than learning models scramble
Analysis of the Effectiveness of Learning in the Use of Learning Modules Against Student Learning Outcomes Rahmawati, Rika; Lestari, Fitria; Umam, Rofiqul
Desimal: Jurnal Matematika Vol. 2 No. 3 (2019): Desimal: Jurnal Matematika
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/djm.v2i3.4557

Abstract

At present there are still students who have difficulty in learning, due to limited learning resources. One effort that can be done is the use of modules in learning. Modules are printed teaching materials designed to be studied independently by learning participants. This study aims to determine the effect of the use of modules on the learning outcomes of students in MTs Hasanuddin Teluk Betung. Through the analysis of diffrences in the average of mathematics learning outcomes between those who used modules and those who did not use modules. The method used in this study is experiments with quantitative exploratory levels. The basic data collection technique uses a test technique that is to determine students learning outcomes. Testing hypotheses by using the t-test statistical formula. Based on the results of hypothesis testing it was concluded that the average mathematics learning outcomes of students using modules were higher than students who did not use the module.
Determining the arm's motion angle using inverse kinematics models and adaptive neuro-fuzzy interface system Palupi, Endah Kinarya; Umam, Rofiqul; Junaidi, Rahmad; Perkasa, Yudha Satya; Sanjaya, W. S. Mada
International Journal of Electronics and Communications Systems Vol. 1 No. 1 (2021): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v1i1.9238

Abstract

Robotics technology is known as a great technology demand to be developed continuesly. One of the important things that need to be considered is the control of the motion of the robot. Movement predictions can be modeled in mathematical equations. Prediction based on learning logic is also very supportive of motion control systems, especially arm motion. In this study, the authors combined the two methods as the main study. The working principle of the arm is to take colored objects detected by the camera. In this study, we made arm four DOFs (Degree of Freedom), but only one DOF is controlled by ANFIS because the other three DOFs only move at two fixed angles. Two methods of determining the arm angle of motion used are inverse kinematics and ANFIS methods. The angle of motion and the position of the red object can be observed in real-time on the monitor with the interface in the MATLAB GUI. The angular output that appears in the MATLAB GUI is sent to Arduino in the form of characters, then, Arduino translates it into servo motion to the coordinates of the object detected by the camera. The results showed that the ANFIS method was more effective than the inverse kinematics model.
Modifying the DC Servo Motor Observed by Particle Swarm Optimization Techniques Saxena, Arti; Panse, Vishal R; Asyhari, Ardian; Umam, Rofiqul; Michalska-Domańska, Marta; Dixit, Aparna
International Journal of Electronics and Communications Systems Vol. 4 No. 2 (2024): International Journal of Electronics and Communications System
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ijecs.v4i2.25071

Abstract

The PID controller's optimized tuning improves the control system's functionality. This work presented the tuning of the PID/FOPID controller by the conventional Ziegler-Nichols (ZN) method and the Particle Swarm Optimization (PSO) algorithm. The PID controller is the most popular in the industry because it is simple to implement, has good computing ability, and provides a robust system. These methods are implemented on the DC servomotor system to optimize the transient responses like rise time (??), settling time (??), and peak overshoot (??) to get a better result. The PID controller tuned by the conventional ZN method gives a longer settling time, a longer rise time, and a higher peak overshoot. The PSO algorithm is utilized to overcome the significant overshoot and considerable settling time obtained in the conventional Ziegler-Nichols method. Analyzing and comparing the MATLAB simulation results, it is observed that PSO algorithms provide a better-optimized response over the ZN method with FOPID controller in respect of less rise time (?? =0.0392 sec.), less settling time (??=0.0605 sec.) and peak overshoot (??=1.92 percent). The results obtained by the proposed controller provide better reliability and better response.
Geochemical Evidence from Major and Trace Elements in Geothermal Waters of Empat Lawang, Southern Sumatra: Clues to Mineralization and Hydrothermal Sources Umam, Rofiqul; Suharno, Suharno; Junaidi, Rahmad
Leuser Journal of Environmental Studies Vol. 3 No. 2 (2025): October 2025
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ljes.v3i2.343

Abstract

This study explores the major and trace element geochemistry of geothermal waters from Empat Lawang, Southern Sumatra, Indonesia, to assess hydrothermal origins and mineral prospecting potential. Five water samples were analyzed using ternary plots, ion correlation diagrams, and geothermometric equations. A strong Na–Cl correlation (R2 = 0.9694) suggests evaporite dissolution or mixing with connate water, while the Ca–SO4 relationship (R2 = 0.9555) indicates gypsum or anhydrite dissolution. The Ca + Mg vs. HCO3 pattern reflects carbonate and silicate weathering influenced by lithological variability. Diagnostic ion plots reveal active ion exchange and halite dissolution across sample sites. Reservoir temperatures estimated using Giggenbach and Fournier Truesdell equations range from 190°C to 404°C, with an outlier of 1593.75°C in PN3, likely due to fluid disequilibrium. Depths span 4.22 to 16.39 km, indicating deep-seated hydrothermal systems with intense fluid–rock interaction. The Cl/Li vs. B plot identifies hydrothermal signatures, with most samples below the Cl/Li < 1000 threshold and elevated boron levels, suggesting active leaching and mineral transport. These findings highlight the potential for borate and metal mineralization. By integrating classical geochemical approaches with modern trace element indicators, this study provides a novel framework for geothermal exploration in Indonesia’s volcanic regions. These findings suggest potential for borate and metal mineralization and offer a geochemical framework for geothermal exploration in Indonesia’s volcanic regions.
Innovative Integrated Disaster Education in Physics Learning: An Effort to Enhance Students’ Disaster Literacy Skills Saregar, Antomi; Putra, Fredi Ganda; Diani, Rahma; Anugrah, Adyt; Misbah, Misbah; Umam, Rofiqul
Jurnal Pendidikan IPA Indonesia Vol. 14 No. 2 (2025): June 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jpii.v14i2.23959

Abstract

Disaster-prone regions require an education system that equips students with both scientific understanding and disaster preparedness. However, integration of disaster mitigation content into subject-specific learning, particularly physics, remains limited. This study aims to develop and evaluate the effectiveness of physics teaching materials integrated with disaster mitigation education to enhance students’ disaster literacy skills. A mixed-method approach with an exploratory sequential design was employed. The development process followed the 4D model (Define, Design, Develop, and Disseminate) to systematically design and implement teaching materials. The study was conducted in two high schools in South Lampung Regency, Lampung, Indonesia involving four classes (two experimental and two control groups) with a total of 128 students, consisting of 63 students in the experimental groups and 65 in the control groups. The T-test results show that the use of disaster mitigation-based teaching materials had a statistically significant effect on students' disaster literacy abilities, with a significance value of 0.000 (p < 0.05).  Furthermore, the results of the effect size analysis (Cohen’s d = 0.62 and 0.66) fall within the moderate category, confirming that this intervention had a significant impact on enhancing students’ disaster literacy skills related to disaster mitigation. The implementation of this teaching material not only enhances students’ understanding of physics concepts but also increases their awareness and preparedness for disasters, particularly around disaster literacy, making it a strategic innovation in disaster education. This research contributes significantly to the development of disaster education curricula in Indonesia, particularly within the context of physics education.
An unsupervised machine learning algorithm approach using K-Means Clustering for optimizing Surface Wave Filtering in seismic reflection data Hartono, Hartono; Anwar, Haerul; Umam, Rofiqul; Takahashi, Hirotaka
Journal of Natural Sciences and Mathematics Research Vol. 10 No. 1 (2024): June
Publisher : Faculty of Science and Technology, Universitas Islam Negeri Walisongo Semarang

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

Abstract

Surface waves often cause significant noise in seismic data, complicating the interpretation of subsurface structures. Traditional filtering methods, such as FK filtering, usually struggle with non-stationary noise and require extensive manual parameter tuning. This study explores the effectiveness of using K-means clustering, incorporating attributes such as amplitude, frequency, and phase to filter surface waves from seismic data. Synthetic seismic data were first generated to test the proposed method, ensuring its robustness before application to real field data. Attributes were extracted from each seismic trace, including instantaneous amplitude, frequency, and phase. These attributes were used as input parameters for the K-means clustering algorithm. The identified clusters corresponding to surface waves were then used to filter these waves from the seismic data. The K-Means clustering effectively differentiated surface waves from reflected waves in both synthetic and real seismic datasets. The method demonstrated that by including phase as an attribute, alongside amplitude and frequency, the accuracy of surface wave detection and filtering significantly improved. The synthetic data showed a clear separation of wave types, validating the method. When applied to real field data, the approach consistently removed surface waves, clarity of seismic reflections crucial for subsurface analysis.
The Characteristics of the First Kind of Chebyshev Polynomials and its Relationship to the Ordinary Polynomials Maulidi, Ikhsan; Wibowo, Bonno Andri; Apriliani, Vina; Umam, Rofiqul
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 5, No 2 (2021): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v5i2.4647

Abstract

In this article, we discuss the Chebyshev Polynomial and its characteristics. The second order difference equation and the process obtaining the explicit solution of the Chebyshev polynomial have been given for each real number. The symmetry and orthogonality of the Chebyshev polynomial has also been demonstrated using the explicit solutions obtained. Furthermore, we have also given how to approx the polynomial function using the Chebyshev polynomials.
Evaluating The Effectiveness of Radon Measurement Techniques in Soil Gas: Impact of Hole Depth and Measurement Time Iqbal, Mochamad; Berlian, Fitra; Al Farishi, Bilal; Ipmawan, Vico Luthfi; Siregar, Rahmat Nawi; Umam, Rofiqul
EKSPLORIUM Vol. 45 No. 2 (2024): NOVEMBER 2024
Publisher : BRIN Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/eksplorium.2024.7134

Abstract

Radon measurement methodologies are critical for accurate risk assessment and resource optimization, yet challenges persist in determining the optimal sampling depth and measurement duration. These factors significantly influence radon concentration readings, and their impact still needs to be explored in systematic evaluations, particularly in balancing efficiency and accuracy. This study evaluates the effectiveness of radon measurement methodologies by experimenting with how sampling hole depth and measurement duration affect radon concentration in soil gas. Radon experiments were conducted at depths of 0.5 m, 1.0 m, and 1.2 m over a 39-day period in soft tuff rock formations at Institut Teknologi Sumatera. Measurements were taken on Days 0, 6, 12, 18, 27, and 39 using the RAD7 Radon Detector, with multiple cycles to ensure stability. The results indicate that radon concentrations varied significantly with both depth and time, with the highest concentrations observed at 1.2 m on Day 18 (1,089 Bq/m³). A noticeable “lag effect” was observed following rainfall events, where radon levels initially decreased due to soil saturation but spiked as the soil dried. The depth of 0.5 m provided the most consistent measurements, with the lowest coefficient of variation (CV = 31%), making it the most reliable and practical depth for routine radon assessments. Overall, this study highlights the importance of considering environmental conditions, such as rainfall and soil moisture, when interpreting radon data and provides insights into optimizing radon measurement practices for accuracy and efficiency.
Relationship between Organizational Learning and Supply Chain Agility on Organizational Performance: A Quantitative Study in Fashion SMEs Parama Kartika Dewa; Irma Nur Afiah; Rofiqul Umam
Jurnal Optimasi Sistem Industri Vol. 23 No. 1 (2024): Published in July 2024
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (715.865 KB) | DOI: 10.25077/josi.v23.n1.p46-60.2024

Abstract

Supply Chain Agility (SCA) is recognized as a crucial component in fostering organizational agility, offering a competitive and expansionary strategy for businesses. However, the impact of SCA on organizational performance, particularly in the fashion industry, remains underexplored. This study aims to investigate how learning and agility within the supply chain affect the performance of fashion SMEs, providing a comprehensive understanding of these dynamics. Employing a quantitative approach, data were collected through a questionnaire from 180 fashion SMEs in the Special Region of Yogyakarta, with responses obtained from managers in the fashion industry sector. This methodological choice ensures that the insights gathered are both relevant and specific to the targeted industry. A Structural Equation Modeling using Partial Least Squares (SEM-PLS) was utilized to test the hypotheses, focusing on both the direct and indirect effects of internal and external learning dimensions on organizational performance. The findings reveal that both learning and supply chain agility significantly enhance the performance of fashion SMEs, underscoring their importance in boosting organizational effectiveness. Specifically, the study highlights that internal learning processes and external knowledge acquisition are both critical in fostering a more agile and responsive supply chain. These results contribute to the understanding of how SMEs in the fashion sector can leverage learning and agility to improve performance, supporting the development of more effective supply chain strategies. Consequently, the study's hypotheses are validated, providing valuable insights for practitioners and researchers in the field. This research underscores the potential for fashion SMEs to enhance their competitive edge and operational efficiency through strategic learning and agile supply chain management.
Co-Authors Abd. Rasyid Syamsuri Abda Abda Abdul Mutolib Abdurahman Abdurrahman Adi, Langit Cahya Adyt Anugrah Ahmad, Faozan Al Farishi, Bilal Al-Hijrah, Al-Hijrah Alhamdy Adytama Ali Rahmat Ali Rahmat Anam, Muhammad Khoirul Andika Eko Prasetiyo Andika Eko Prasetiyo, Andika Eko Andiyan Andriana, Bibin B. Annisa Nurhuda Romadhona Antarnusa, Ganesha Antomi Saregar Ardian Asyhari Ayu Puspa Wirani Azima, Muhammad Firman Bayu A. Sadjab Belista Gunawan Berlian, Fitra Betta Kurniawan, Betta Bumi, Philosofi Setia Desi Nadalia Dewa, Parama Kartika Dewi Lengkana Dixit, Aparna Endah Kinarya Palupi Endah Kinarya Palupi Endah Kinarya Palupi Endah Kinarya Palupi Fajar Ikhwan Harnomo Fajri Mulya Iresha Felga Zulfia Rasdiana Firda Fibrila Fitria Lestari Fredi Ganda Putra Fujiani, Dwi Haerul Anwar Hartati, Niken Sri Hartono Hartono Hasan Said Tortop Hasan Said Tortop Hasan Said Tortop Heriyanto Syafutra Herlina Herlina Hesti Herliantari Hurien Helmi Husna, Ismalia I Putu Tedy Indrayana Ikah N. P. Permanasari Ilma Ridhona Imama, Khoirunnisa Iqbal, Mochamad Irma Nur Afiah Irmansyah . Irwandani Irwandani Irzaman, Irzaman Iskandar Tsani Iskandar Tsani, Iskandar Iwamony, Steven Jermsittiparsert, Kittisak Kasam Kasam Khoirunnisa Imama Khusnul Yakin Kittisak Jermsittiparsert Kurnia, Yogi Laila Puspita Lengkana, Dewi Lusi Anggraini M Ridwan M. Ubaidillah Ridwanulloh M. Yogi Riyantama Isjoni Mada Sanjaya WS Mariana Ngundju Awang Maula, Frida Yassar Maulidi, Ikhsan Mersi Kurniati Michalska-Domańska, Marta Misbah Misbah Mochamad Iqbal Muawanah Muawanah Muhamad Syazali Muhamad Yasin Muhammad Nafian Muliadi Ramli Munifah Munifah Munifah Munifah, Munifah Nanda Ridki Permana Nangkula Utaberta Nurhanurawati Nurhanurawati Nurhanurawati Nurhanurawati Palupi, Endah Kinarya Panse, Vishal R PRAMUDAWARDANI, HANIS Prasetyawati Umar, Emi puspitarum, deska lismawenning Rahma Diani Rahma Diani, Rahma Rahmad Junaidi, Rahmad Rahmi Ramadhani Rashidi Abdull Manap, Mohd Riana, Ulfa Ridhona, Ilma Rika Rahmawati Rika Rahmawati Rizka Dwi Saputri Rizqi Prastowo Rohim, Miftahul Romadhona, Annisa Nurhuda Rudi Heryanto Saiful*, Saiful Santi Widyawati Saxena, Arti Siregar, Rahmat Nawi Sismanto Sismanto Sismanto Sismanto Steven Iwamony Sugeng Sutiarso Sugeng Sutiarso Suharno Suharno Suparman Suparman Suparman Suparman Syamsul Huda Syamsul Huda Syamsul Huda Takahashi, Hirotaka Tita Cardiah Tortop, Hasan Said Tri Wahyu Handayani Triani Triani Usman, Musawwir Vico Luthfi Ipmawan Vina Apriliani Wahyudianto, Benny Wibowo, Bonno Andri Yakin, Khusnul Yasin, Muhamad Yetri Hasan Yudha Satya Perkasa Yudha Satya Perkasa, Yudha Satya Zakir Sabara