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All Journal TEKNIK Jurnal Pseudocode Journal of Information Systems Engineering and Business Intelligence Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini IT JOURNAL RESEARCH AND DEVELOPMENT JITU : Journal Informatic Technology And Communication TIN: TERAPAN INFORMATIKA NUSANTARA Journal Evaluation in Education (JEE) Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian Harmoni Sosial : Jurnal Pengabdian Dan Solidaritas Masyarakat Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Manfaat: Jurnal Pengabdian Pada Masyarakat Indonesia Ngudi Waluyo Empowerment : Jurnal Pengabdian Kepada Masyarakat
Alifia Revan Prananda
Department Of Information Technology, Faculty Of Engineering, Universitas Tidar
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities 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 Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Sentiment Analysis for Customer Review: Case Study of GO-JEK Expansion Alifia Revan Prananda; Irfandy Thalib
Journal of Information Systems Engineering and Business Intelligence Vol. 6 No. 1 (2020): April
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.6.1.1-8

Abstract

Background: Market prediction is an important thing that needs to be analyzed deeply. Business intelligence becomes an important analysis procedure for analyzing the market demand and satisfaction. Since business intelligence needs a deep analysis, sentiment analysis becomes a powerful algorithm for analyzing customer review regarding to the business intelligence analysis.Objective: In this study, we perform a sentiment analysis for identifying the business intelligence analysis in GO-JEK.Methods: We use Twitter posts collected from the Twint library which consists of 3111 tweets. Since the dataset did not provide a ground truth, we perform Microsoft Text Analytic for determining positive, neutral, and negative sentiment. Before applying Microsoft Text Analytic, we conduct a pre-processing step to remove the unwanted data such as duplicate tweets, image, website address, etc.Results: According to the Microsoft Text Analytic, the results are 666 positive sentiment numbers, 2055 neutral sentiment numbers, and 127 negative sentiment numbers.Conclusion:  According to these results, we conclude that most GO-JEK customers are satisfied with the GO-JEK services. In this research, we also develop classification model to predict the sentiment analysis of new data. We use some classifier algorithms such as Decision Tree, Naïve Bayes, Support Vector Machine and Neural Network. In the result, the system shows      that the decision tree provides the best performance.
Toward Better Analysis of Breast Cancer Diagnosis: Interpretable AI for Breast Cancer Classification Alifia Revan Prananda; Eka Legya Frannita
IT Journal Research and Development Vol. 7 No. 2 (2023)
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/itjrd.2023.11563

Abstract

Recently, some countries have been distressing with the increasing number of breast cancer cases. Those cases were extremely increased in every year. Practicaly, the increasing number of patients was caused by the manual examination. Recently, some researchers have been done in the development of AI method for solving this problem. However, AI itself still has limitation since it worked in the black-box approach which was difficult to be trusted. Thus, to overcome those problems, we proposed a method that was able to classify breast ultrasound images into two classes (benign and malignant) and able to explain how the prediction was made. Our proposed method consisted of four processes i.e., pre-processing step, development of CNN model, interpretable step and evaluation. In this research work, our proposed method performed into 780 breast ultrasound images divided into three classes (133 normal, 210 malignant, and 437 benign). In the training process, our proposed method obtained training accuracy of 0.9795, training loss of 0.0675. The validation process obtained validation accuracy of 0.8000 and validation loss of 0.5096. While, in the testing process, our proposed method achieved accuracy of 0.7923. In the interpretable process using LIME, the LIME result is covered by doctor visualization. It was indicated that LIME was suitable enough in visualizing the important features of breast cancer severity. Regarding to the results, our proposed method has a potensial to be implemented as an early detection method for classifying malignancy of breast cancer in order to help the doctor in the screening process
Toward Adaptive Manufacturing Development: Implementation of Artificial Intelligence for Identifying Leather Defects Alifia Revan Prananda; Eka Legya Frannita
Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) Vol 10 No 2 (2023): List of the Accepted Article for Future Issues
Publisher : Jurusan Teknik Elektro, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/jurnalecotipe.v10i2.4329

Abstract

Artificial intelligence was the powerful approach that was proven to be impactful for solving several problems. In the leather inspection cases, artificial intelligence also contributed some research works that effected for leather inspection process. In this research, we employed NasNet architecture conducted by using fine-tunning transfer learning method to distinguish the types of leather defects. We used 3600 images that was distributed into six classes which are folding marks, grain off, growth marks, loose grains, pinhole and non-defective. Our proposed solution successfully achieved accuracy for training data is 0.9788 with loss of 0.0198. While the maximum accuracy in validation data is 0.8059 with loss of 0.2126. In the testing data, our experiment obtained accuracy of 0.8603 with loss of 0.1603. These results indicated that our proposed solution was suitable to recognize the characteristics of leather defects and suitable to distinguish them.
AR-FootIN 4.0 : Aplikasi Pengenalan Teknologi Industri 4.0 Pada Bidang Alas Kaki Berbasis Mobile Augmented Reality Alifia Revan Prananda; Marwanto Marwanto; Eka Legya Frannita; Anwar Hidayat
TIN: Terapan Informatika Nusantara Vol 4 No 10 (2024): March 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i10.4956

Abstract

Rapid development of technology gave a positive impact on the footwear industry. The emergence of various types of technology as part of the industrial revolution 4.0 has greatly helped various types of work in industry. However, technology also need to be supported by good quality resource. Knowledge regarding how to use and maintain these technologies is needed so that the benefits of these technologies can be utilized. An alternative way is by developing good quality of human resource to being proficient in using technology. Furthermore, cultivating technological literacy is also one of the essential factors. Regarding to this situation, we proposed research that aims to develop the AR-FootIN 4.0 application as a learning media for introducing industry 4.0 in the footwear sector. This learning media is developed by employing mobile augmented reality. The proposed learning media is developed by using the SDLC method. The resulted learning media is then evaluated by conducting two types of evaluation, which are expert evaluation and user evaluation. The results of expert evaluation and user evaluation obtain a percentage of 93.33% and 86% respectively, which means that the feasibility of the application to support the technological literacy process in the footwear industry is very good.
Penerapan Metode CNN (Convolutional Neural Network) untuk Mengklasifikasikan Jenis Cacat pada Kulit Hewan Eka Legya Frannita; Alifia Revan Prananda
TIN: Terapan Informatika Nusantara Vol 5 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v5i2.5390

Abstract

Recently, leather industry was rapidly growth in several countries. In Indonesia, leather industry became one of the government's priority industries since there were quite a lot of leather industries developing in various regions in Indonesia. On the other hand, there were large number of consumer demand for leather products. Regarding to this fact, maintaining the quality of leather was strongly important. An alternative solution for maintaining leather quality is to conduct leather quality inspection process. However, currently the leather inspection process was still carried out manually by identifying directly the types of defects found on the surface of the leather. This manual inspection process certainly has several hurdles such as time consuming, requiring high accuracy, and requiring experienced operators. This research aimed to develop convolutional neural network architecture that can classify types of leather defects. This research was done by conducting four main processes which were literature study and data collection processes, develop CNN architecture, training process, and testing process. This research work used public dataset consisting of 3600 digital leather images distributed into six classes (folding mask, grain off, growth marks, loose grains, pinhole, non-defective). Based on the training and testing process, the model obtained training accuracy of 90.43% and testing accuracy of 88.47%.
A Review on Digital Microscopic Images for Plasmodium Parasite Detection Nisworo, Sapto; Prananda, Alifia Revan
TEKNIK Vol. 44, No. 3 (2023): December 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/teknik.v44i3.53990

Abstract

Indonesia is one of the regions that contribute to the increasing number of malaria cases. In 2019, more than 250 million malaria cases were found in Indonesia. This phenomenon is caused by several factors, including the examination procedure. In Indonesia, the digital microscopic examination has become the gold standard procedure in detecting and diagnosing malaria, whereas this procedure requires considerable expertise. Hence, the rapid examination is difficult to ensure. In order to overcome this problem, several methods of malaria detection have been proposed with a different approach. Image processing and computer vision techniques have become a powerful approach in the development of early detection systems called computer-aided detection (CADe) and computer-aided diagnosis (CADx). Several previous findings reported their contributions in detecting Plasmodium parasites using image processing and computer vision. Recently, artificial intelligence, including machine learning and deep learning, also offered outstanding results in detecting the Plasmodium parasite. This paper aims to present a scientific review of recent image processing and computer vision applications for the development of CADe or CADx in order to assist the doctor in doing rapid detection and diagnosis.
Optimalisasi Kampung Organik sebagai Ketahanan Pangan di Kelurahan Rejowinangun Selatan Alifia Revan Prananda; Cornelius Rangga Surya Kusuma; Dinda Kusumaningrum; Galih Slamet
Pandawa : Pusat Publikasi Hasil Pengabdian Masyarakat Vol. 2 No. 4 (2024): Oktober: Pusat Publikasi Hasil Pengabdian Masyarakat
Publisher : Asosiasi Riset Ilmu Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/pandawa.v2i4.1264

Abstract

Bay leaves are one of the toga plants (family medicinal plants) which can be used to stop excessive defecation. Apart from that, bay leaves can also be used to treat gout, stroke, high cholesterol, improve blood circulation, stomach inflammation, itching and diabetes. Therefore, there is a need for education in the form of counseling regarding the use of bay leaves and how to process them as herbal medicine to help cure diseases. Kaffir lime is a natural ingredient in various food and beverage products in Indonesia and other Asian countries. Kaffir lime plants contain compounds including essential oils which are also rich in benefits such as antioxidants, antimicrobials, antileuchemicals, antitussives, insecticides, illaricides and phenolic compounds such as flavonoids, flavanones, flavones, flavonols and glycerolipids which according to research function as a source of antioxidants, anti-inflammatory , antiviral, anti-allergic, and anti-carcinogenic, anti-aging for the human body. The planting of kitchen spices in the form of bay plants and orange leaves is grown using organic and environmentally friendly materials.
Klasifikasi Jenis Cacat pada Kulit Menggunakan Arsitektur GoogLeNet Prananda, Alifia Revan; Frannita, Eka Legya
Jurnal Pseudocode Vol 11 No 1 (2024): Volume 11 Nomor 1 Februari 2024
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/pseudocode.11.1.15-20

Abstract

Deep learning has been proven to be able to provide significant contributions to several fields, including industry. It has also been proven that it has resulted in an outstanding performance for classification, detection, and even segmentation processes. In the leather industry, it also successfully gave valuable results, especially for the leather defect inspection process. This study aims to develop deep learning architecture for classifying leather defect. We used 3600 leather digital images distributed in six types of leather defects. In this study we employed GoogLeNet for classifying the data. Our experiment successfully achieved accuracy of 0.904 in training process and 0.885 in testing process. This result indicated that GoogLeNet provided powerful performance for classifying the type of leather defects.
Upaya Mewujudkan Kampung Iklim Melalui Program Bank Sampah dengan Partisipasi Aktif Masyarakat di Rejowinangun Selatan Alifia Revan Prananda; Rhema Chandrawati; Dinda Kusumaningrum; Terbit Bagaskara Ahmad; Lidia Faridah
Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian Vol. 1 No. 4 (2024): Oktober : Transformasi Masyarakat : Jurnal Inovasi Sosial dan Pengabdian
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/transformasi.v1i4.686

Abstract

In this modern era, handling environmental issues such as climate change and waste management is becoming increasingly crucial. The Waste Bank Program in South Rejowinagun plays a central role in the Climate Village initiative, aiming to increase community awareness of waste management through sorting and recycling. This initiative relies on active community participation to reduce the amount of waste sent to landfills and lower greenhouse gas emissions, thereby contributing to environmental cleanliness and climate change mitigation. Apart from positive ecological impacts, the Waste Bank also creates economic opportunities for the community by implementing a waste "savings" system, where each separated type has monetary value. The methods used, including lectures, counselling and training, are designed to educate the public, including PAUD children, about the importance of effective waste management. Although this program has shown positive results, challenges like a lack of public understanding remain. To overcome this and increase program effectiveness, a more intensive educational approach and strengthening collaboration networks between communities are needed.
Optimalisasi Program Permaculture Melalui Adaptasi dan Mitigasi Berbasis Kearifan Lokal di Kelurahan Rejowinangun Selatan Alifia Revan Prananda; Mohammad Norman Aulia Mufasir; Nabila Fairuzzahra; Niken Orisa Putri; Anisa Lestari
Harmoni Sosial : Jurnal Pengabdian dan Solidaritas Masyarakat Vol. 1 No. 4 (2024): Harmoni Sosial : Jurnal Pengabdian dan Solidaritas Masyarakat
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62383/harmoni.v1i4.699

Abstract

The southern district of Rejowingan in Magelang faces challenges like large dumpstores, poor water quality, floods, and rising food needs. Villagers are working with the Ormawa DPM KM PPK team to address these issues. The government launched the Climate Village Program to improve the region's climate and resilience to natural disasters. Permaculture principles can be applied to organic waste management through maggot cultivation, which reduces waste volume and supports sustainable agriculture. This combination of permaculture and maggot cultivation can be an effective and environmentally friendly model for addressing organic waste and ecosystem sustainability.
Co-Authors Abdillah, Muhammad Nurkholis Adam, Otmar Shah Aminuyati Anisa Lestari Annisa Istiqomah, Annisa Anwar Hidayat Bagus Fatkhurrozi Cornelius Rangga Surya Kusuma D Jayus Nor Salim Damar Wicaksono Daniel Gunawan Delfiyan Widiyanto Dhanang Suwidagdho Dinda Kusumaningrum Dwi Wulandari Eka Legya Frannita Galih Slamet Hidayat, Anwar Ibrahim Nawawi Imam Adi Nata Irfandy Thalib Lidia Faridah Majidah, Zharifa Nur Mashud Syahroni Mohammad Norman Aulia Mufasir Mujtahidah, Tholibah Nabila Fairuzzahra Niken Orisa Putri Novitasari Novitasari Pramitaningrum, Erlita Purwaningsih , Nunik Putri, Naimah Rahmawati, Atiqa Restu Rakhmawati Rhema Chandrawati Rheza Ari Wibowo Sapto Nisworo Setiawan , Wawan Budi Setya Wijaya, Vania Amelia Suamanda Ika Novichasari Syifa Fauziah Terbit Bagaskara Ahmad Terra Rhebekka Wibowo, Fadhila Syahida