Article Per Year (5 Year)
p-Index From 2020 - 2025
2.267
P-Index
This Author published in this journals
All Journal Inersia : Jurnal Teknik Sipil dan Arsitektur Jurnal Fisika FLUX Jurnal Teras Fisika : Teori, Modeling, dan Aplikasi Fisika IJIIS: International Journal of Informatics and Information Systems JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Jurnal Pendidikan dan Teknologi Indonesia Indonesian Community Journal Perwira Journal of Science and Engineering (PJSE) IJCOSIN : Indonesian Journal of Community Service and Innovation Jurnal Ilmu Fisika dan Terapannya (JIFTA) PEDAMAS (Pengabdian Kepada Masyarakat) Perwira Journal of Community Development (PJCD) Journal of Industrial and Mechanical Engineering
Ika Maulita
Universitas Jenderal Soedirman
Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Edukasi Kesiapsiagaan Bencana Alam di Desa Karangbanjar, Kecamatan Bojongsari, Kabupaten Purbalingga Ika Maulita; Destin Alfianika Maharani; Siti Nasiroh; Melia Dwi Renovriska; Ayu Sitanini
I-Com: Indonesian Community Journal Vol 4 No 1 (2024): I-Com: Indonesian Community Journal (Maret 2024)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v4i1.4024

Abstract

Disaster preparedness training in Karangbanjar Village faces the challenge of increasing community understanding and awareness of disasters. The purpose of this activity is to strengthen the adaptive capacity and preparedness of the community through education and practical simulations. Implementation methods include counseling, practical training, and disaster simulation. The results of the activity showed a significant increase in participants' understanding, as evidenced by the pre-test and post-test results which showed a statistically significant increase in understanding. Evaluation of participants' progress, as measured through the pre-test and post-test, revealed a substantial increase in understanding with the average score increasing from 5.9 to 7.1. This improvement, which represents an overall increase in understanding of 34.61%, was statistically validated through a paired t-test, where the results showed a statistically significant difference between the pretest and post-test scores with a test statistic of -2.708 and a p-value of 0.0112. The program successfully increased community awareness and proactivity in facing disasters, proving the importance of disaster preparedness education in building resilient communities.
Penentuan momen inersia bola pejal menggunakan sensor gyroscope MPU6050 dan sensor photodioda Pratiwi, Umi; Maulita, Ika; Adi, Efita Pratiwi; Luthfia, Adilla
Jurnal Teras Fisika: Teori, Modeling, dan Aplikasi Fisika Vol 7 No 1 (2024): Jurnal Teras Fisika: Teori, Modeling, dan Aplikasi Fisika
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jtf.2024.7.1.12006

Abstract

Pengukuran momen inersia sebagai konsep penting dalam sistem kerja mesin yang memerlukan gerak rotasi, namun pengukuran secara manual belum menghasilkan hasil maksimal. Diperlukan perancangan sistem peraga penentuan Momen Inersia Bola Pejal Menggunakan sensor Mpu6050 Gyroscope Angle dan sensor photodioda untuk penentuan momen kelembaman bola pejal menggunakan berbasis sensor. Metode yang dilakukan dengan merancang sisten pengukuran momen inersia bola pejal, membuat flowchart prinsip kerja sistem, membuat flowchart sistem, dan perhitungan ketelitian. Variabel yang diperoleh berupa waktu tempuh bola pejal, panjang lintasan, dan sudut lintasan bidang miring. Data yang diperoleh berupavariasi panjang lintasan 2
Prediksi Magnitudo Gempa Menggunakan Random Forest, Support Vector Regression, XGBoost, LightGBM, dan Multi-Layer Perceptron Berdasarkan Data Kedalaman dan Geolokasi Maulita, Ika; Wahid, Arif Mu'amar
Jurnal Pendidikan dan Teknologi Indonesia Vol 4 No 5 (2024): JPTI - Mei 2024
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.470

Abstract

Penelitian ini bertujuan membandingkan kinerja lima algoritma pembelajaran mesin, yaitu Random Forest, Support Vector Regression, XGBoost, LightGBM, dan Multi-Layer Perceptron dalam memprediksi magnitudo gempa berdasarkan data kedalaman dan geolokasi. Masalah yang diangkat adalah pentingnya prediksi magnitudo gempa yang lebih akurat untuk meningkatkan efektivitas mitigasi risiko bencana, terutama di daerah rawan gempa. Data yang digunakan mencakup informasi kedalaman, lintang, dan bujur dari peristiwa gempa selama periode tertentu. Metode penelitian melibatkan pembagian data pelatihan dan pengujian, serta evaluasi kinerja model menggunakan metrik Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), dan R². Hasil penelitian menunjukkan bahwa LightGBM memberikan performa terbaik dengan nilai MAE sebesar 0,4688, RMSE sebesar 0,6284, dan R² sebesar 0,2458. Random Forest mengikuti dengan nilai MAE sebesar 0,4750, RMSE sebesar 0,6312, dan R² sebesar 0,2391. XGBoost menunjukkan performa yang kompetitif dengan MAE sebesar 0,4932, RMSE sebesar 0,6471, dan R² sebesar 0,2003. Sebaliknya, Support Vector Regression mencatatkan nilai MAE sebesar 0,5136, RMSE sebesar 0,6987, dan R² sebesar 0,0677, sementara Multi-Layer Perceptron memberikan kinerja terendah dengan MAE sebesar 0,5190, RMSE sebesar 0,7152, dan R² sebesar 0,0231. Dampak penelitian ini sangat penting bagi pengembangan sistem peringatan dini gempa dan peningkatan akurasi prediksi magnitudo gempa. Penelitian ini menegaskan bahwa pemilihan model yang tepat dapat berkontribusi pada mitigasi risiko bencana, dengan memberikan informasi yang lebih akurat mengenai kekuatan gempa yang dapat terjadi. Temuan ini juga menunjukkan bahwa algoritma pembelajaran mesin, terutama LightGBM dan Random Forest, dapat menjadi alat yang efektif dalam analisis seismologi dan aplikasi prediksi gempa.
Analisis Komparatif Linear Regression, Random Forest, dan Gradient Boosting untuk Prediksi Banjir Maulita, Ika; Widiawati, Chyntia Raras Ajeng; Wahid, Arif Mu'amar
Jurnal Pendidikan dan Teknologi Indonesia Vol 4 No 8 (2024): JPTI - Agustus 2024
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.599

Abstract

Penelitian ini mengevaluasi tiga model machine learning—Linear Regression, Random Forest Regressor, dan Gradient Boosting Regressor—untuk memprediksi probabilitas banjir di India, dengan tujuan meningkatkan akurasi prediksi dan mendukung strategi mitigasi risiko banjir. Kinerja model dievaluasi menggunakan metrik Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), dan ????2. Hasil penelitian menunjukkan bahwa Linear Regression dan Gradient Boosting Regressor memiliki kinerja yang hampir setara, dengan MAE dan RMSE yang kompetitif. Namun, Linear Regression sedikit unggul dalam menjelaskan variabilitas probabilitas banjir berdasarkan nilai ????2. Sebaliknya, Random Forest Regressor menunjukkan kinerja yang lebih rendah, yang kemungkinan disebabkan oleh overfitting atau kurang optimalnya penyetelan parameter. Penelitian ini memberikan kontribusi penting terhadap peningkatan akurasi sistem peringatan dini dan pengelolaan risiko banjir berbasis data. Dengan menganalisis faktor-faktor utama yang memengaruhi probabilitas banjir, penelitian ini menawarkan wawasan yang dapat mendukung perencanaan intervensi yang lebih efektif, seperti pengelolaan sungai yang lebih baik dan perencanaan tata ruang perkotaan yang adaptif. Saran untuk penelitian mendatang meliputi eksplorasi algoritma tambahan, termasuk pendekatan pembelajaran mendalam, penerapan rekayasa fitur lanjutan, serta optimalisasi model menggunakan alat Automated Machine Learning (AutoML). Temuan ini berkontribusi pada pengembangan metode prediksi banjir yang lebih akurat dan efisien, serta memperkuat upaya mitigasi risiko banjir di masa depan.
ANALISIS SECOND VERTICAL DERIVATIVE DATA GRAVITASI UNTUK MENGINTERPRETASIKAN STRUKTUR BAWAH PERMUKAAN DAERAH LEMBANG Maulita, Ika; Prasetyaningsih, Nirmala Ratri; Pratiwi, Umi; Azimi, Ali
Jurnal Ilmu Fisika dan Terapannya Vol 11, No 2 (2024): Jurnal Ilmu Fisika dan Terapannya (JIFTA)
Publisher : Prodi Fisika, Departemen Pendidikan Fisika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/fisika - s1.v11i2.22239

Abstract

Analisis data gravitasi Topex dengan metode Second Vertical Derivative (SVD) bertujuan untuk menentukan struktur bawah permukaan di wilayah Lembang Jawa Barat. Data gravitasi yang diunduh dari website Topex, dilakukan koreksi sehingga dapat diketahui pola persebaran kenampakan Anomali Bouguer Sederhana (ABS) berdasarkan interpretasi data gravitasi, dan mengetahui kontur hasil SVD Filter Elkins (1951) dalam penentuan jenis struktur bawah permukaan di Lembang, Jawa Barat. Data yang digunakan adalah data sekunder yang meliputi data gravitasi yang sudah terkoreksi hingga Free Airy Anomaly (FAA) dan topografi yang diambil dari website satelit Topex dengan koordinat 107˚32’ E – 107˚46’ E dan 6˚45’ S – 6˚52’ S. Penelitian ini menggunakan Microsoft Excel 2013, Software Surfer 17, Notepad ++, dan Google Earth Pro. Metode yang digunakan dalam penelitian ini adalah metode gravitasi dan metode Second Vertical Derivatif (SVD) Filter Elkins. Hasil yang diperoleh dari penelitian ini menunjukkan hasil koreksi data gravitasi menghasilkan 120 data nilai ABS, 3 pola sebaran ABS meliputi: anomali tinggi, anomali sedang, dan anomali rendah serta hasil analisa grafik slicing masing-masing line menunjukkan struktur bawah permukaan di Lembang merupakan jenis patahan normal.
Spatiotemporal Analysis of B-Value at Mount Slamet (2014–2023) Maulita, Ika; Sugito, Sugito; Boli, Lusia Silfia Pulo
Jurnal Fisika Flux: Jurnal Ilmiah Fisika FMIPA Universitas Lambung Mangkurat Vol 21, No 3 (2024): Jurnal Fisika Flux: Jurnal Ilmiah Fisika FMIPA Universitas Lambung Mangkurat
Publisher : Lambung Mangkurat University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/flux.v21i3.20718

Abstract

This study investigates the spatial and temporal distribution of b-values at Mount Slamet, one of Indonesia’s most active volcanoes, during its eruption activities from 2014 to 2023. The primary objective is to explore how variations in b-values correlate with stress conditions and volcanic activity, providing insights into eruption forecasting. Seismic data were sourced from USGS, BMKG, and local networks and analyzed using ZMAP and MATLAB to calculate b-values, assess magnitude completeness, and perform spatial and temporal analyses. Results reveal notable spatial variability: higher b-values in the northern and northeastern regions indicate lower stress levels, while lower b-values in the southwestern region suggest elevated stress concentrations. These spatial patterns align with geological features, highlighting zones of intense tectonic and magmatic interactions. Temporally, b-values consistently declined before major eruptions in 2017 and 2020, reflecting increased stress and larger seismic events. Post-eruption, b-values rose, indicating stress reduction and stabilization of the volcanic system. These findings underscore the value of b-value monitoring as an effective tool for eruption forecasting. The observed spatial and temporal trends offer critical insights into Mount Slamet’s evolving stress conditions, aiding disaster preparedness and risk mitigation strategies for local communities. The study highlights the importance of continuous seismic monitoring combined with advanced analytical techniques to enhance the predictive capabilities of volcanic hazard assessments. Future research should integrate additional geophysical parameters, refine predictive models, and extend analyses to similar volcanic settings to improve global understanding of volcanic processes and enhance early warning systems.
Sosialisasi Pemanfaatan Aplikasi Marketplace untuk meningkatkan pemasaran produk UMKM di Desa Meri Kabupaten Purbalingga Sitanini, Ayu; Alfianika, Destin; Nasiroh, Siti; Renovriska, Melia Dwi; Maulita, Ika
Indonesian Journal of Community Service and Innovation (IJCOSIN) Vol 5 No 1 (2025): Januari 2025
Publisher : LPPM IT Telkom Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/ijcosin.v5i1.1659

Abstract

A strategic step to improve the marketing of small and medium enterprise (MSME) products in Meri Village, Purbalingga Regency is to integrate marketplace applications. The development of digital technology has given small business owners new opportunities to grow their business through online platforms such as Shopee, Tokopedia, and TikTok Shop. The objective of this community service program is to provide MSME participants with knowledge about the advantages, working methods, and marketing tactics in the marketplace. Activities are conducted through lectures, tutorials, discussions, and hands-on guidance in creating accounts and managing online stores. The results show that participants better understand digital marketing, are more interested in adopting marketplaces, and are better able to reach a wider range of consumers. It is hoped that MSMEs in Meri Village can increase competitiveness, profits, and the welfare of local communities with continued support.
Earthquake Hazard Analysis of National Vital Objects by Probabilistic Seismic Hazard Analysis Method in West Java Prayogo, Arif Zidan; Rorosanto, Zahrawani Ifada; Syahbana, Arifan Jaya; Maulita, Ika
INERSIA lnformasi dan Ekspose Hasil Riset Teknik Sipil dan Arsitektur Vol. 21 No. 1 (2025): May
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/inersia.v21i1.72915

Abstract

The Probabilistic Seismic Hazard Analysis (PSHA) method was used to analyze the level of earthquake hazard in West Java Province, Indonesia, which is located between two active tectonic plates. This research integrates literature study, earthquake data collection, and data processing to explore the influence of megathrust, background, fault, and combine earthquake sources on local and national vital objects in the region, such as Pusdik Kopassus, Presidential Palace, Cirebon PLTU, Geothermal Power Plant, Peacekeeping Mission Center (PMPP TNI), PT. PINDAD, PT DAHANA SUBANG, PLM GUNUNG SAWAL, Walahar Dam, PT Indonesia Power UJP Jabar 2 Pelabuhan Ratu, which have important roles in critical infrastructure, defense, and national resilience. The analysis shows variations in maximum ground acceleration between 0.40 g to 1.00 g for background earthquake sources, and 0.00 g to 1.00 g for fault earthquake sources. The research also underscores the importance of mitigation efforts and proper planning to reduce the potential impact of earthquakes in West Java, taking into account the crucial role of national vital objects in maintaining the stability and sustainability of the region. The implications of these findings reinforce the urgency to improve coordination between stakeholders in building earthquake resilience at the local and national levels, and highlight the importance of hazard curve analysis on national vital objects to inform the future of the region.
Empirical Analysis of Social Media Interaction Metrics and Their Impact on Startup Engagement Wahid, Arif Mu'amar; Maulita, Ika
International Journal of Informatics and Information Systems Vol 8, No 3: September 2025
Publisher : International Journal of Informatics and Information Systems

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v8i3.272

Abstract

In the digital economy, social media serves as a crucial platform for startups to build relationships with audiences and strengthen brand presence. However, the specific effects of different types of user interactions—likes, comments, and shares—on startup engagement remain insufficiently quantified. This study provides an empirical analysis of how social media interaction metrics influence engagement using secondary data from the publicly available Social Media Engagement Metrics dataset on Kaggle. Employing a quantitative design, the study integrates descriptive statistics, Pearson correlation, Random Forest, and multiple linear regression to examine both linear and non-linear relationships. Results show that likes, comments, and shares collectively affect engagement rates, with Random Forest identifying likes as the most influential feature. However, regression results indicate that shares exert a statistically significant but negative effect on engagement, suggesting complex behavioral patterns behind user interactions. Visual analyses—including histograms, boxplots, and heatmaps—support data normality and highlight variation in post performance. The findings emphasize the importance of visually engaging content and interactive captions to enhance user engagement. This study contributes to digital marketing research by combining methodological rigor with actionable insights, offering data-driven recommendations for startups aiming to optimize their social media strategies.
Waterwheel performance parameters and influencing factors Sampurno, Carolus Borromeus Krishna; Maulita, Ika; Febiyani, Anastasia; Rokhim, Yunus Ari; Margono, Herlian Seto; Darmawan, Almas Rifqi; Pangestu, Retno
Journal of Industrial and Mechanical Engineering Vol 1 No 1 (2023): Journal of Industrial and Mechanical Engineering
Publisher : Department of Industrial Engineering, Universitas Jenderal Soedirman.

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

Abstract

Renewable energy is the cleanest source available on the planet. Water energy is one of the renewable energy sources that are widely available around us. Hydropower is energy obtained from flowing water or falling water. One of the utilization of hydropower by using a waterwheel. Since the 18th century waterwheels have been widely used both for grain milling, textile industry, and other uses. In the 20th century waterwheels began to be used for power generation. However, due to its low efficiency, the waterwheel began to be abandoned as a power plant. There have been many studies conducted to improve the performance of waterwheels, but the information is widely spread, so this article was made with the aim of collecting this information so that it can be known what parameters affect the performance of a waterwheel. The design of the right overshot waterwheel can achieve an efficiency of about 85%, the undershot waterwheel can reach 25% making these two wheels suitable for exploiting from varied and most frequently used flows. The performance of the waterwheel is made based on water discharge data, head differences, and how to use it so that it can be said that the waterwheel has different performance characteristics so that certain parameters are needed. Parameters that affect the performance of the waterwheel include the design of the blades, the amount of water collected on the overshot mill blades, the ratio of the sinking blades on the undershot waterwheel, and the angle used on the breastshot mill blades so that the waterwheel can work optimally to release the potential of water power with a low head.
Co-Authors Adi, Efita Pratiwi Alfianika, Destin Anastasia Febiyani Arif Mu'amar Wahid Arifan Jaya Syahbana Ayu Sitanini Ayu Sitanini Ayu Sitanini Ayu Sitanini Azimi, Ali Boli, Lusia Silfia Pulo Chyntia Raras Ajeng Widiawati Darmawan, Almas Rifqi Destin Alfianika Maharani Ito, Yonathan Luthfia, Adilla Margono, Herlian Seto MELIA DWI RENOVRISKA Melia Dwi Renovriska Nasiroh, Siti obiyasi, aldean Pangestu, Retno Prasetyaningsih, Nirmala Ratri Prayogo, Arif Zidan Renovriska, Melia Dwi Rokhim, Yunus Ari Rorosanto, Zahrawani Ifada Sampurno, Carolus Borromeus Krishna Siti Nasiroh Siti Nasiroh SUGITO Sugito - Tri Setiono, Adhi Umi Pratiwi Umi Pratiwi, Umi Wahid, Arif Mu'amar