Article Per Year (5 Year)
p-Index From 2020 - 2025
1.785
P-Index
This Author published in this journals
All Journal Jurnal Rekayasa Sistem Industri PRISMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Conference on Innovation and Application of Science and Technology (CIASTECH) M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika Jusikom: Jurnal Sistem Informasi Ilmu Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Inovasi Penelitian dan Pengabdian Masyarakat Scientific Journal of Informatics
Kusumaningrum, Dwi Sulistya
Unknown Affiliation
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

Published : 13 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 13 Documents
Search

 1   2 
IMPLEMENTASI SISTEM BILIK DISINFEKTAN OTOMATIS BERBASIS IOT DENGAN NODEMCU DAN SENSOR ULTRASONIC Maulana, Ridwan; Fauzi, Ahmad; Kusumaningrum, Dwi Sulistya
Conference on Innovation and Application of Science and Technology (CIASTECH) CIASTECH 2021 "Kesiapan Indonesia Dalam Menghadapi Krisis Energi Global"
Publisher : Universitas Widyagama Malang

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

Abstract

Banyak kota- kota besar di Indonesia yang warganya ter- infeksi sehinngga menjadi zona merah dan beberapa kota menjadi zona hitam. Berbagai cara memutus rantai penularan Covid-19 seperti mencuci tangan dengan sabun di setiap tempat, menggunakan handsinitizer, dan menggunakan masker setiap berpergian ke keluar rumah. Tujuan dari penelitian ini adalah untuk menghasilkan suatu alat penyemprot disinfektan yang ber-operasi otomatis disaat ada yang melewati sensor Ultrasonic dan bisa mengontrol per-hari yang melewati bilik ini, juga bisa memonitoring kekurangan air disinfektan pada bak menggunakan Internet of things (Iot). Pada penelitian ini membantu dalam upaya pencegahan penyebaran virus Covid-19. Bilik disinfektan ini menggunakan NodeMCU, dan sensor Ultrasonic yang akan memberikan informasi melalui website. Hasilnya dapat memonitoring jumlah warga-nya telah di sterilisasi, dan kinerja dapat memonitoring water level disinfektan-nya dengan hasil rata- rata selisih 0.37cm.
PEREKAMAN OTOMATIS BERDASARKAN DETEKSI OBJEK MANUSIA PADA CCTV MENGGUNAKAN METODE YOU ONLY LOOK ONCE V3 (YOLOV3) Hakim, Mirwan Abdurrahman; Rohana, Tatang; Kusumaningrum, Dwi Sulistya
Conference on Innovation and Application of Science and Technology (CIASTECH) CIASTECH 2020 "Peranan Strategis Teknologi Dalam Kehidupan di Era New Normal"
Publisher : Universitas Widyagama Malang

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

Abstract

CCTV selama ini memiliki kekurangan dalam hal penggunaan penyimpan, sementara pengawasan dilakukan penuh selama 1 × 24 jam, dan membuat kamera menulis frame terus menerus. Penyimpanan pun dengan drastis terpakai sehingga cepat penuh. Hal ini pun membuat storage seperti HDD, akan berkerja keras sehingga keawetan storage HDD tidak terjamin lama. Solusi yang bisa dilakukan adalah dengan memanfaatkan pengenalan objek sebagai kondisi. Frame hanya akan ditulis pada penyimpan ketika kamera mendeteksi adanya objek manusia. Metode Object Detection yang digunakan adalah YOLOv3, dataset dilatih dan menjadi model latih lalu diterapkan secara realtime. Model yang dilatih pada penelitian ini memiliki akurasi 100%, dan setiap objek yang terdeteksi berhasil menjadi kondisi kamera menulis frame pada penyimpan dengan ukuran video paling besar 1,6mb dengan durasi waktu 18 detik.
ANALISIS KESULITAN BELAJAR MATEMATIKA DISKRIT MAHASISWA TEKNIK INFORMATIKA Kusumaningrum, Dwi Sulistya; Puspita Lestari, Santi Arum
PRISMA Vol 8, No 2 (2019): Jurnal PRISMA Volume 8, No 2 tahun 2019
Publisher : Universitas Suryakancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/jp.v8i2.717

Abstract

ABSTRACTAsosiasi Perguruan Tinggi Informatika dan Komputer (APTIKOM) states that learning outcomes of Informatics on mathematical topics are discrete mathematics. This study aims to examine the results of students learning discrete mathematics, and examine what factors are causing students difficulty learning discrete mathematics. The method used is a mix method which is qualitative methods and quantitative methods. Data collection as the result of discrete mathematics learning outcomes, and mathematical learning difficulty questionnaire data. The population used is students of Informatics at Buana Perjuangan University Karawang with a sample of 65 students taking discrete mathematics courses in the 2018/2019 school year. The results showed that most students still had difficulty learning discrete mathematics. This is because an average value is 66,4 from the value of a test value is 55. This Test Value is the minimum passing grade. While the factors that cause discrete mathematics learning difficulties are divided into 2 classifications namely 6 influential indicators and 2 quite influential indicators. Keyword: Learning Difficulties, Learning Outcomes, Discrete Mathematics
Application Of Yolo V8 For Product Defect Detection In Manufacturing Companies Jamal, Malikil; Faisal, Sultan; Kusumaningrum, Dwi Sulistya; Rohana, Tatang
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

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

Abstract

One important aspect in the production process is maintaining product quality and avoiding defects that could harm the company. This research aims to improve quality and avoid product defects that are detrimental to the company, especially defects in the form of bubbles in the product, by using YOLOv8. The dataset consists of 100 data which is divided into 80 for training and 20 testing data with an epoch value of 100. To obtain optimal bubble detection results, this research chose the latest version of YOLOv8 and compared several models, namely YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x. The research results show that YOLOv8m achieves the highest accuracy among other models with a mAP value of 0.712, precision of 0.764, recall of 0.659, and F1-score of 0.708. This research highlights the potential of detection models that can detect bubbles precisely and accurately. Keywords: Kecacatan Produk, Deteksi Gelembung, Perusahaan Manufaktur, Model YOLOv8
Mengintegrasikan Prinsip Pembangunan Berkelanjutan dalam Pembelajaran Matematika untuk Merangsang Keterampilan Berkelanjutan pada Generasi Mendatang Lestari, Santi Arum Puspita; Nurapriani, Fitria; Kusumaningrum, Dwi Sulistya
Jurnal Rekayasa Sistem Industri Vol. 13 No. 1 (2024): Jurnal Rekayasa Sistem Industri
Publisher : Universitas Katolik Parahyangan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26593/jrsi.v13i1.7167.1-10

Abstract

This research constitutes a literature review employing a qualitative approach, analyzing scholarly articles, books, and other documents related to sustainable development. This article aims to summarize and analyze previous studies concerning sustainable development in the context of mathematics education, as well as strategies that can be employed to integrate the principles of sustainable education. Integrating the principles of sustainable development into education, including mathematics education, is crucial in fostering a more environmentally responsible society and promoting sustainability across all sectors. However, its implementation remains limited. Educators face various challenges, including a lack of time, resources, and understanding of sustainable education, along with a dearth of supportive teaching materials. The principles of sustainable development can serve as a framework for developing curricula and teaching practices that are more sustainable. Educators can select mathematical problems related to environmental or social issues, discuss relevant mathematical concepts in connection with these problems, and help students comprehend the impact of mathematical decisions on the environment and society. Integrating the principles of sustainable development into mathematics education not only aids in producing a generation with sustainable skills but also motivates students to learn mathematics in more engaging and meaningful ways. A learning approach centered around sustainable development can be an effective way to prepare students for a sustainable future. The article also underscores the necessity for curriculum development, training, and professional advancement for educators.
Geometric Patterns in Jaipong Dance: An Ethnomathematics Study Lestari, Santi Arum Puspita; Kusumaningrum, Dwi Sulistya; Nurapriani, Fitria
Mathline : Jurnal Matematika dan Pendidikan Matematika Vol. 9 No. 1 (2024): Mathline: Jurnal Matematika dan Pendidikan Matematika
Publisher : Universitas Wiralodra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31943/mathline.v9i1.556

Abstract

Jaipong dance is a traditional dance deeply rooted in the culture of West Java. However, not everyone is aware that Jaipong dance incorporates mathematical elements into its performance. Therefore, the aim of this research is to analyze mathematical concepts, particularly geometric patterns, within Jaipong dance. The research approach employed is ethnography, with data analysis including domain analysis, taxonomic analysis, and ethnographic analysis. Data was collected through three main methods: interviews, observations, and documentation. The research findings reveal the utilization of mathematical concepts in Jaipong dance. This includes counting from 1 to 8 to maintain the dance's rhythm and the use of geometric shapes in floor patterns. The floor patterns in Jaipong dance reflect the spatial arrangement used in the dance performance. Some of the floor patterns used in Jaipong dance encompass straight lines, diagonals, triangles, quadrilaterals, and pentagons. Thus, Jaipong dance not only blends artistic movements but also integrates mathematical and geometric concepts within its floor patterns. Geometry plays a significant role in creating visual aesthetics and regulating interactions among the dancers during Jaipong dance performances.
Application of Convolutional Neural Network (CNN) Algorithm with ResNet-101 Architecture for Monkey Pox Detection in Human Al Fathir Rizal Januar; Indra, Jamaludin; Kusumaningrum, Dwi Sulistya; Faisal, Sutan
Journal of Applied Informatics and Computing Vol. 9 No. 3 (2025): June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i3.9621

Abstract

Monkeypox is a zoonotic disease that has spread to various countries, including Indonesia. It is transmitted through direct contact with skin lesions, respiratory droplets, or contaminated objects. Early and accurate detection is crucial to reduce the risk of transmission and improve treatment effectiveness. This study aims to detect monkeypox using a Convolutional Neural Network (CNN) with the ResNet-101 architecture. The pre-processing steps include normalization and resizing of images to 224×224 pixels. The model is trained using the Adam optimizer, categorical crossentropy loss function, and an adaptive learning rate reduction. Evaluation results show that the model achieved an accuracy of 94%, with a precision of 0.92, recall of 0.92, and an F1-score of 0.92. The model is capable of classifying images effectively, although some misclassifications still occur. This system is intended to function as an initial image-based screening tool, but its results should be confirmed through clinical diagnosis and laboratory testing to ensure accuracy.
Penentuan Status Gizi Pada Balita Menggunakan Fuzzy Inference System Dengan Metode Fuzzy Tsukamoto Vandelweiss, Dita Aura; Fauzi, Ahmad; Kusumaningrum, Dwi Sulistya; Baihaqi, Kiki Ahmad
TIN: Terapan Informatika Nusantara Vol 5 No 1 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i1.5188

Abstract

Nourishing status in babies is a vital consideration of guaranteeing sound development and improvement. This exploration plans to foster a specialist framework for nourishing status in babies using the fluffy surmising framework strategy with the Tsukamoto fluffy calculation in view of body weight and level. In light of essential information overviews and meetings, the information gathered from coordinated wellbeing, in particular Posyandu West Adiarsa, Adiarsa Pusaka, and Telukjambe Timur in Karawang Regime added up to 181 information on kids under five. Framework configuration incorporates a point of interaction framework consisting of information, yield, data set, information construction and calculation framework plan. Framework execution was done using HTML, PHP, MySQL, and Cup. The testing framework includes a fluffy deduction framework using the Tsukamoto fluffy technique on various review instances of young children with different dietary circumstances, with contribution of 3 factors consisting; old enough, weight, level. The experimental outcomes will be contrasted and the nourishing is not entirely set in stone by a nutritionist. This exploration produces fluffy sets for the factors of weight, level and healthful status, as well as fluffy registering decisions that interface information and results. The test brings about the framework obtained a precision of 96% on the grounds that 181 tests were carried out on each information variable which adapted the factors 'terrible', 'less', 'typical', 'more' and 'weight'.
Integrasi Etnomatematika dalam Pembelajaran Bangun Datar Segi Empat Berbasis Kearifan Lokal untuk Meningkatkan Pemahaman Matematika Lestari, Santi Arum Puspita; Kusumaningrum, Dwi Sulistya; Nurapriani, Fitria
Jurnal Inovasi Penelitian dan Pengabdian Masyarakat Vol. 4 No. 2 (2024): Desember
Publisher : Indonesia Emerging Literacy Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53621/jippmas.v4i2.369

Abstract

Matematika dianggap sebagai pelajaran wajib dari tingkat pendidikan dasar hingga tinggi karena menjadi dasar dan penghubung bagi mata pelajaran lainnya. Namun, masih ada siswa yang mengalami kesulitan dan memandang matematika hanya sebagai perhitungan dasar. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan pemahaman matematika siswa dengan menghubungkan matematika dan kebudayaan lokal melalui etnomatematika yang berfokus pada bangun datar segi empat. Kegiatan PkM menggunakan metode sosial konstruktivisme yang dibagi menjadi 5 tahap yakni identifikasi masalah, kolaborasi, eskplorasi, implementasi, dan evaluasi. Melalui kegiatan pengabdian kepada masyarakat, dilakukan penyuluhan di SMPN 2 Cilebar, memperkenalkan etnomatematika pada bidang segi empat kepada siswa. Hasilnya menunjukkan bahwa 85% siswa (22 dari 25 siswa) mampu mengenali bentuk segi empat pada rumah adat Sunda. Selain itu, kegiatan ini berhasil meningkatkan minat siswa terhadap matematika dengan mengaitkannya secara nyata dengan kebudayaan lokal. Meskipun berhasil, masih ada faktor penghambat, seperti persepsi sulitnya matematika dan pandangan bahwa matematika bersifat abstrak. Dengan demikian, kesimpulan yang diperoleh dari kegiatan ini adalah memberikan kontribusi positif dalam memahamkan siswa mengenai penerapan matematika pada kehidupan sehari-hari melalui pendekatan etnomatematika.
Classification Model of Public Sentiments About Electric Cars Using Machine Learning Romadoni, Nurul; Siregar, Amril Mutoi; Kusumaningrum, Dwi Sulistya; Rohana, Tatang
Scientific Journal of Informatics Vol. 11 No. 2: May 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i2.1309

Abstract

Purpose: This research compared the accuracy level of six algorithms based on the ROC method and the Confusion Matrix evaluation on data regarding public sentiments towards electric cars. Methods: Data collection was conducted for data sourced from TikTok. Next, the data underwent text preprocessing (data cleaning and case folding) and text processing (stemming, tokenizing, stopword removal, word frequency, word relation, TF-IDF, scoring, and labeling). Modeling was then conducted using supervised (labeled) algorithms consisting of the Support Vector Machine (SVM), Decision Tree, Naive Bayes, Random Forest, K-Neighbor, and Logistic Regression. Finally, an evaluation was conducted (confusion matrix and ROC). Result: The results revealed that the Decision Tree algorithm with the Confusion Matrix and ROC evaluation obtained the highest result of 87%. The algorithm with the lowest result is KNN, which has an accuracy of 56%. The classification result for the neutral sentiment has a percentage of 57.1%, followed by negative sentiment at 26.8% and positive sentiment at 16.1%. The KNN algorithm is suitable for large and low-dimensional data, SVM is suitable for data with many features and clear separation between classes, and Naive Bayes is efficient for large datasets with many low-quality features. Additionally, the Random Forest algorithm could overcome overfitting and unbalanced data. Logistic regression is also suitable for linear data without assuming a certain distribution. The Decision Tree algorithm is good for complex data as it provides a visual explanation of predictions. In this study, the Decision Tree algorithm obtained high results because it has the best characteristics and is a linear technique. Novelty: This study found that based on the ROC method and the Confusion Matrix evaluation conducted, the Decision Tree algorithm is more accurate than the other algorithms studied.
Co-Authors Al Fathir Rizal Januar Baihaqi, Kiki Ahmad Dwi Sulistya Faisal, Sultan Faisal, Sutan Fauzi Ahmad Muda Hakim, Mirwan Abdurrahman Indra, Jamaludin Jamal, Malikil Lestari, Santi Arum Puspita Nurapriani, Fitria Rahmat Rahmat Ridwan Maulana, Ridwan Rohana, Tatang Romadoni, Nurul Siregar, Amril Mutoi Syahril, Ade Vandelweiss, Dita Aura Yana Cahyana