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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) TEKNIK INFORMATIKA Jurnal Informatika Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi AMIKOM ICT AWARD 2010 Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Jurnal Buana Informatika Jurnal Sarjana Teknik Informatika Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Dinamika Informatika Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal technoscientia Jurnal Teknologi Jurnal Pseudocode Jurnal Teknologi Informasi dan Ilmu Komputer Telematika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Techno (Jurnal Fakultas Teknik, Universitas Muhammadiyah Purwokerto) JUITA : Jurnal Informatika Proceedings Konferensi Nasional Sistem dan Informatika (KNS&I) Seminar Nasional Informatika (SEMNASIF) CESS (Journal of Computer Engineering, System and Science) Proceeding SENDI_U Jurnal IPTEK-KOM (Jurnal Ilmu Pengetahuan dan Teknologi Komunikasi) Jurnal Inspiration KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Proceeding of the Electrical Engineering Computer Science and Informatics PROtek : Jurnal Ilmiah Teknik Elektro Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Creative Information Technology Journal AT-Tahdzib: Jurnal Studi Islam dan Muamalah SISFOTENIKA IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Ilmiah Universitas Batanghari Jambi INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Syntax Literate: Jurnal Ilmiah Indonesia CogITo Smart Journal InComTech: Jurnal Telekomunikasi dan Komputer Insect (Informatics and Security) : Jurnal Teknik Informatika Jurnal Eksplora Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Komtika (Komputasi dan Informatika) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Informatika Universitas Pamulang Applied Information System and Management Jurnal Sinergitas PkM & CSR Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah RESEARCH : Computer, Information System & Technology Management INTECOMS: Journal of Information Technology and Computer Science JurTI (JURNAL TEKNOLOGI INFORMASI) Angkasa: Jurnal Ilmiah Bidang Teknologi Jiko (Jurnal Informatika dan komputer) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer CYBERNETICS Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) Journal on Education JURTEKSI Jurnal Informasi dan Komputer Multitek Indonesia : Jurnal Ilmiah Indonesian Journal of Applied Informatics Jurnal Manajemen Informatika Jambura Journal of Informatics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) EXPLORE ComTech: Computer, Mathematics and Engineering Applications CSRID (Computer Science Research and Its Development Journal) Jurnal Ilmiah Sinus Informasi Interaktif Majalah Ilmiah Bahari Jogja CCIT (Creative Communication and Innovative Technology) Journal EDUMATIC: Jurnal Pendidikan Informatika Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming M A T H L I N E : Jurnal Matematika dan Pendidikan Matematika TAFAQQUH: Jurnal Hukum Ekonomi Syariah Dan Ahwal Syahsiyah Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Technologia: Jurnal Ilmiah JURNAL TAHURI SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi Aisyah Journal of Informatics and Electrical Engineering Jurnal Manajemen Informatika dan Sistem Informasi Journal of Information Systems and Informatics TAJDID KURVATEK Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jurnal Tecnoscienza Respati IT (INFORMATIC TECHNIQUE) JOURNAL JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Journal of Intelligent Decision Support System (IDSS) G-Tech : Jurnal Teknologi Terapan SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL International Journal of Advances in Data and Information Systems Jurnal Sistem Komputer dan Informatika (JSON) Journal of Innovation Information Technology and Application (JINITA) Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Bulletin of Computer Science and Electrical Engineering (BCSEE) Infotek : Jurnal Informatika dan Teknologi jurnal syntax admiration Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) TEPIAN Infokes : Jurnal Ilmiah Rekam Medis dan Informasi Kesehatan JURNAL TEKNOLOGI TECHNOSCIENTIA Jurnal Teknik Informatika (JUTIF) Jurnal Teknimedia: Teknologi Informasi dan Multimedia Journal of Electrical Engineering and Computer (JEECOM) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Mitra Mahajana: Jurnal Pengabdian Masyarakat Jurnal Pendidikan dan Teknologi Indonesia International Journal of Computer and Information System (IJCIS) Jurnal Informatika dan Teknologi Komputer ( J-ICOM) International Research on Big-data and Computer Technology (IRobot) Bulletin of Computer Science Research INFOSYS (INFORMATION SYSTEM) JOURNAL J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen International Journal of Informatics, Information System and Computer Engineering (INJIISCOM) International Journal of Research and Applied Technology (INJURATECH) Jurnal Ekonomi dan Teknik Informatika International Journal Artificial Intelligent and Informatics Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Dinamika Informatika (JDI) Jurnal Nasional Teknik Elektro dan Teknologi Informasi sudo Jurnal Teknik Informatika Jurnal Informatika Teknologi dan Sains (Jinteks) Duta.com : Jurnal Ilmiah Teknologi Informasi dan Komunikasi Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram EXPLORE Journal of Comprehensive Science Techno Indonesian Journal Computer Science (ijcs) Jurnal Educative: Journal of Educational Studies Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer JURNAL TEKNIK INDUSTRI Jurnal Pendidikan Indonesia (Japendi) Cerdika: Jurnal Ilmiah Indonesia International Journal of Advanced Science Computing and Engineering Innovative: Journal Of Social Science Research J-Icon : Jurnal Komputer dan Informatika Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) SmartComp Fahma : Jurnal Informatika Komputer, Bisnis dan Manajemen Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Teknomatika: Jurnal Informatika dan Komputer Proceeding of International Conference on Information Science and Technology Innovation (ICoSTEC) Tafaqquh : Jurnal Hukum Ekonomi Syariah dan Ahwal Syahsiyah Explore The Indonesian Journal of Computer Science Scientific Journal of Informatics Jurnal Teknologi KOPEMAS International Journal of Information Engineering and Science At-Tahdzib: Jurnal Studi Islam dan Muamalah semanTIK JESICA Jurnal Sistem Informasi Komputer dan Teknologi Informasi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Journal of Business, Social, Management, and Technology Jurnal Komtika (Komputasi dan Informatika)
Ema Utami
Universitas Amikom Yogyakarta
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Improving Model Capability for Sentiment Trend Analysis in Hotel Visitor Reviews with Bi-LSTM Multistage Approach Yanuargi, Bayu; Utami, Ema; Kusrini, Kusrini; Parikesit, Arli Aditya
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5185

Abstract

This study focuses to improve the sentiment analysis of hotel reviews using Multistage mechanism of two-stage approach based on the Bidirectional Long Short-Term Memory (Bi-LSTM) architecture with 53,000 data from 28 hotels in Yogyakarta that captured from google maps review for hotel in Yogyakarta. Hotel customer reviews often contain mixed sentiment expressions, making it crucial to filter out only sentences with a single dominant sentiment to avoid ambiguity. In the first stage, the model detects sentiment at the token level and counts the number of sentiment expressions in each sentence. Only sentences with a single polarity are passed to the final classification stage. In the second stage, the overall sentiment is classified as positive, negative, or neutral using pooled contextual representations. Experimental results from 30 iterations demonstrate consistently high performance, with precision, recall, and F1-scores above 0.95, and overall accuracy exceeding 96%. The confusion matrix analysis shows strong model performance, although some challenges remain in distinguishing between positive and neutral sentiment. Additionally, sentiment trend analysis of hotel reviews from properties such as Lafayette Boutique Hotel and The Westlake Resort Jogja reveals dynamic shifts in guest perception over time. This multistage mechanism approach proves effectiveness of improving sentiment classification accuracy by avoid the bias on sentiment and also in providing valuable temporal insights for monitoring customer satisfaction.
Performance Comparison of Child Stunting Prediction Support Vector Machine vs Random Forest with Grid Search Optimization Elim, Marthinus Ikun; Utami, Ema
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5285

Abstract

Stunting is a serious global health problem, particularly in developing countries. Its prevalence is high in Indonesia, reaching approximately 24.4% among children under five in 2021. This condition, defined as failure to thrive due to chronic malnutrition, repeated infections, and a lack of psychosocial stimulation, has long-term impacts on an individual's cognitive development and productive capacity. This study aims to conduct a comparative analysis of the Support Vector Machine and Random Forest algorithms in predicting stunting in children, with a focus on evaluating the impact of hyperparameter optimization using Grid Search on model performance. This study used the public stunting dataset from Kaggle and included data preprocessing steps such as handling missing values, duplication, encoding, and scaling. The data was then divided into 80% for training, 10% for testing, and 10% for validation. Comprehensive evaluation metrics such as precision, recall, F1-score, and ROC-AUC were also used to assess model performance.  Grid Search optimization was applied to both models to find the best hyperparameter combination. Experimental results showed that Grid Search optimization significantly improved the accuracy of the SVM model from 94.29% to 98.37%. Meanwhile, the Random Forest model demonstrated very high performance, achieving 99.59% accuracy both before and after Grid Search optimization. These findings underscore the significant potential of machine learning models in supporting stunting prevention efforts for public health intervention policies. This research contributes to the development of machine learning-based decision support systems for public health, particularly in early detection and intervention strategies for stunting. 
Development of Double-Tail Generative Adversarial Network with Adaptive Style Transfer for Anime Background Production with Makoto Shinkai's Stylization Purwanto, Agus; Kusrini, Kusrini; Utami, Ema; Agustriawan, David
Scientific Journal of Informatics Vol. 12 No. 1: February 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i1.20850

Abstract

Purpose: Traditionally, 2D anime production involves the expertise of experienced animators and is labor-intensive and time-consuming. Generative adversarial networks (GANs) have been developed to create high-quality anime over the years. However, the developed GANs still have caveats, such as the presence of artifacts, high-frequency noise, color and semantic structure mismatches, blurring, and texture issues. Additionally, research on AI-generated anime images with a particular style is still lacking. Thus, this study aimed to develop double-tail generative adversarial network (DTGAN) with adaptive style transfer to generate quality anime background images aligning with Makoto Shinkai's anime style. Methods: A dataset of real world and anime images was collected and preprocessed. The training was run, and an inference process was done to generate background images with the anime style of Makoto Shinkai using DTGAN with adaptive style transfer. Evaluations of the images produced were performed using visual comparison and quantitative analysis using Fréchet Inception Distance (FID) and peak signal-to-noise ratio (PSNR). Result: Compared to other methods, the images generated by DTGAN with adaptive style transfer had the lowest FID and highest PSNR values of.38.7 and 19.4 dB, respectively. Visual comparison of the images against other methods and real anime image of Makoto Shinkai demonstrated that images from DTGAN had the best quality that matched Makoto's style, as observed from color, background preservation, photorealistic style, and light contrast. Novelty: These findings suggest that DTGAN with adaptive style transfer using adaptive instance normalization (AdaIN) and linearly adaptive denormalization (LADE) outperforms other methods, highlighting its practical use for 2D anime production.
Perbandingan Algoritma DBSCAN dan K-Means Clustering untuk Pengelompokan Data Gangguan PT. PLN UID Kalselteng Wijaya, Tri Amri; Utami, Ema; Al Fatta, Hanif
Innovative: Journal Of Social Science Research Vol. 4 No. 1 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i1.8920

Abstract

Perusahaan Listrik Negara (PLN) merupakan salah satu perusahaan Badan Usaha Milik Negara, Dalam pendistribusian listrik sering terjadi gangguan yang menyebabkan pasoka listrik sering terdampak diantranya terjadi pemadaman, Bentuk pencegahan gangguan dilakukan dengan cara pengelompokan titik-titik gangguan yang sering terjadi, Untuk mengatasi permasalahan Terdapat berbagai metode yang dapat digunakan dalam pengelompokan data, diantaranya : DBSCAN dan K-Means. Tujuan dari penelitian ini untuk melakukan pengelompokan data gangguan menggunakan metode DBSCAN dan K-Means. Percobaan dilakukan menggunakan dataset sebanyak 2000 data yang terdiri dari 2 atribut: lattitude dan longtitude. Berdasarkan penelitian ini, Setelah melalui beberapa percobaan diperoleh hasil bahwa K-Means lebih unggul daripada DBSCAN dalam mengelompokkan data gangguan. Algoritma K-Means memiliki nilai SI terbaik sebesar 0,581 yang terletak pada percobaan dengan nilai k = 6.
Comparison of Feature Extraction Methods for Conducting Sentiment Classification in Ternate Malay Language using Machine Learning Approaches Surya, Satria Dwi; Utami, Ema; Yaqin, Ainul
PROtek : Jurnal Ilmiah Teknik Elektro Vol 11, No 3 (2024): Protek: Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v11i3.7262

Abstract

Local people in Ternate, North Maluku, often use local languages to communicate on social media. This poses a challenge for newcomers to understand the implied meaning and emotions of the messages conveyed through social media. This research aims to develop a natural language processing (NLP)-based emotion classification method that can be applied to Ternate Malay text datasets. The application of NLP is expected to improve the accuracy of emotion detection and classification in the text. The research was conducted by applying and comparing the performance of several classification models trained using Ternate Malay text datasets. The models used include SVM (Support Vector Machine), K-Nearest Neighbors (KNN) Random Forest, Decision Tree and Logistic Regression. Each model is applied using BoW (Bag-of-Words) and Word2Vec vectorization representations. The evaluation results show that the BoW+SVM model provides the highest performance with 77% accuracy, followed by BoW+Random Forest (75%) and BoW+Logistic Regression (73%). Thus it can be concluded that NLP can be applied to the Ternate Malay language dataset to classify emotions based on text.
Systematic Literature Review of the Development of Financial Information Systems in Churches Wicaksono, Sherif Aji; Wijaksana, Candra Putra; Ngaeni, Nurus Sarifatul; Utami, Ema
International Journal of Computer and Information System (IJCIS) Vol 4, No 4 (2023): IJCIS : Vol 4 - Issue 4 - 2023
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v4i4.143

Abstract

This study was conducted to investigate the factors that influence the development of financial information systems in churches. The study used a systematic literature review with 10 studies that met the inclusion criteria. The findings of this study suggest that user involvement, technology selection, and change management are all important factors that influence the successful development of financial information systems in churches. Churches that are considering developing a financial information system should pay attention to these factors to increase their chances of success.Keywords : Financial information systems.
APPLYING USER-CENTERED DESIGN FOR MOBILE APPLICATIONS INTERFACE DESIGN Farasalsabila, Fidya; Lestari, Verra Budhi; Nugroho, Jangkung Tri; Pramudyantoro, Arvi; Utami, Ema
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 1 (2023): Desember 2023
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i1.2619

Abstract

Abstract: The Healthy Food Supplier App, which introduces groundbreaking innovations to increase public access to and delivery of healthy food, has emerged as a new phenomenon in the food sector. This research intends to examine and describe how the use of healthy food suppliers contributes to improving public health by making healthy food accessible to obtain and deliver it quickly. The development of mobile applications with the aim of providing healthy food and ingredients for the community is the subject of this research. The aim of this app is to provide original responses to issues related to raising awareness of quality of life and the value of nutritious food in everyday life. The User Centered Design (UCD) method needs to be applied to categorize various user information needs and package them into a mobile application design model. The results of the application design showed that the interface design for the pioneer food and health food raw material application was successfully created using the implementation of the UCD method with a number of revisions that have been updated since the evaluation as one of the feature developments in the application. The food recording feature and personalized recommendations implemented in this mobile application provide users with awareness and guidance in adopting healthier eating patterns.            Keywords: Design Interface; Mobile Applications; Requirements Engineering; User-Centered Design  Abstrak: Aplikasi Pemasok Makanan Sehat yang memperkenalkan inovasi terobosan untuk meningkatkan akses publik ke dan pengiriman makanan sehat, telah muncul sebagai fenomena baru di sektor makanan. Penelitian ini bermaksud untuk mengkaji dan mendeskripsikan bagaimana penggunaan pemasok makanan sehat berkontribusi dalam peningkatan kesehatan masyarakat dengan membuat makanan sehat dapat diakses untuk mendapatkan dan mengantarkannya dengan cepat. Pengembangan aplikasi mobile dengan tujuan menyediakan makanan dan bahan makanan sehat bagi masyarakat menjadi pokok bahasan penelitian ini. Tujuan dari aplikasi ini adalah untuk memberikan tanggapan orisinal terhadap masalah yang terkait dengan peningkatan kesadaran kualitas hidup dan nilai makanan bergizi dalam kehidupan sehari-hari. Metode User Centered Design (UCD) perlu diterapkan untuk mengkategorikan berbagai kebutuhan informasi pengguna dan mengemasnya ke dalam model desain aplikasi mobile. Hasil perancangan aplikasi didapatkan bahwa desain antarmuka aplikasi pelopor makanan dan bahan baku makanan kesehatan berhasil dibuat dengan menggunakan implementasi metode UCD dengan sejumlah revisi yang sudah diperbarui sejak evaluasi sebagai salah satu pengembangan fitur pada aplikasi. Fitur pencatatan makanan dan rekomendasi personal yang diterapkan pada aplikasi mobile ini memberikan pengguna kesadaran dan panduan dalam mengadopsi pola makan yang lebih sehat. Kata Kunci: Design Interface; Mobile Applications; Requirements Engineering; User-Centered Design
ANALYSIS OF PUBLIC OPINION ON INDONESIAN TELEVISION SHOWS USING SUPPORT VECTOR MACHINE Farasalsabila, Fidya; Utami, Ema; Hanafi, Muhammad
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 2 (2024): Maret 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i2.2935

Abstract

Abstract: There are a great number of academics that are now conducting research on sentiment analysis by employing supervised and machine learning techniques. The research can be carried out with the assistance of a variety of sources, including reviews of movies, reviews of Twitter, reviews of online products, blogs, discussion forums, and other social networks. With the progress of technology, individuals may now effortlessly utilize social media platforms to access and share information, as well as express their viewpoints to the general public, without any constraints of distance or time. Twitter is a social media network that serves as a repository for opinions. Diverse techniques are employed to provide optimal and realistically precise pressure detection. The analysis and discussion affirm that the Support Vector Machine (SVM) was effectively employed in this study, utilizing public opinion data on television program reviews in Indonesia. An SVM classifier is employed to examine the Twitter data set by utilizing various parameters. The study successfully completed the preprocessing process by collecting a total of 400 data points, consisting of 320 reviews from 4 television shows for training data and 80 reviews for testing. The data was filtered and classified using SVM, with 200 positive and 200 negative data points for comparison. The experiment utilized the SVM method using TF-IDF to achieve the most accurate test results. The test accuracy was 80%, while the training data accuracy reached 100%.            Keywords: Sentiment Analysis; Support Vector Machine; Television Shows Review, TF-IDF,  Abstrak: Saat ini, banyak akademisi sedang menyelidiki analisis sentimen melalui pemanfaatan teknik yang diawasi dan pembelajaran mesin. Kajian dapat dilakukan dengan menggunakan beberapa sumber seperti review film, review Twitter, review produk online, blog, forum diskusi, atau jejaring sosial lainnya. Dengan kemajuan teknologi, masyarakat kini dapat dengan mudah memanfaatkan platform media sosial untuk mengakses dan berbagi informasi, serta menyampaikan pandangan mereka kepada masyarakat umum, tanpa batasan jarak dan waktu. Twitter adalah jaringan media sosial yang berfungsi sebagai gudang opini. Beragam teknik digunakan untuk menghasilkan deteksi tekanan yang optimal dan presisi secara realistis. Analisis dan pembahasan menegaskan bahwa Support Vector Machine (SVM) efektif digunakan dalam penelitian ini, memanfaatkan data opini publik tentang review program televisi di Indonesia. Pengklasifikasi SVM digunakan untuk memeriksa kumpulan data Twitter dengan memanfaatkan berbagai parameter. Penelitian berhasil menyelesaikan proses preprocessing dengan mengumpulkan total 400 titik data yang terdiri dari 320 review dari 4 acara televisi untuk data pelatihan dan 80 review untuk pengujian. Data disaring dan diklasifikasikan menggunakan SVM, dengan 200 titik data positif dan 200 titik data negatif sebagai perbandingan. Percobaan ini menggunakan metode SVM dengan menggunakan TF-IDF untuk mencapai hasil pengujian yang paling akurat. Akurasi pengujiannya mencapai 80%, sedangkan akurasi data pelatihan mencapai 100%. Kata kunci: Analisis Sentimen, Review Tayangan Televisi, TF-IDF,  Support Vector Machine
Deteksi Penyakit Gigi dan Mulut Menggunakan Algoritma Inception-V3 Detection of Dental and Oral Diseases Using Inception-V3 Ghifari, Dloifur Rohman Al; Utami, Ema; Ariatmanto, Dhani
Jurnal Pendidikan Indonesia Vol. 6 No. 4 (2025): Jurnal Pendidikan Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/japendi.v6i4.7649

Abstract

Kesehatan gigi dan mulut sangat penting bagi kesejahteraan umum, namun banyak orang mengabaikan pengobatan karena kurangnya kesadaran atau tantangan diagnostik. Metode diagnostik tradisional sering kali kurang akurat dan efisien. Penelitian ini bertujuan mengembangkan sistem otomatis untuk mengklasifikasikan penyakit gigi dan mulut menggunakan algoritma deep learning Inception-V3 guna meningkatkan akurasi diagnostik. Penelitian menggunakan dataset 8.776 citra oral yang diseimbangkan dengan SMOTE dan diproses dengan teknik augmentasi. Inception-V3 dilatih dan dibandingkan dengan CNN, VGG-16, ResNet50, serta model machine learning tradisional. Model Inception-V3 mencapai akurasi 94%, mengungguli model lain (CNN: 81%, VGG-16: 88.7%, ResNet50: 76.25%) dan menunjukkan stabilitas tanpa overfitting. Studi ini menegaskan potensi Inception-V3 dalam analisis gambar medis, menawarkan alat diagnostik yang andal untuk deteksi dini penyakit gigi dan mulut, sehingga dapat meningkatkan hasil layanan kesehatan.
Design of Automatic Feeder with Adjustable Temperature, PH, and Weather for Catfish Antara, Pebri; Utami, Ema; Kusnawi, Kusnawi
Cerdika: Jurnal Ilmiah Indonesia Vol. 5 No. 4 (2025): Cerdika: Jurnal Ilmiah Indonesia
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/cerdika.v5i4.2473

Abstract

Catfish is a fish that is consumed by many Indonesians and is one of the business opportunities. This can be a good prospect for the future with catfish farming. Even many restaurants and restaurants use this fish as one of the menus. Cultivating catfish is not easy, there are many parameters that need to be considered so that fish life can develop properly. Starting from sufficient water ph or according to the standard of living catfish, up to the air temperature. These factors will affect if catfish farms are ignored. Timely feeding is also a major factor that can have sufficient nutrition. With an automatic fish feed system and water quality monitoring, farmers' problems related to water quality can be monitored using sensors. Feeding can be done via a telegram bot with certain settings as needed.
Co-Authors , Anggit Dwi Hartanto A.A. Ketut Agung Cahyawan W AA Sudharmawan, AA Abdul Malik Zuhdi Abdullah Ardi Abdullah, Riska K Abdulrahmat E Ahmad Abyan Fauzi Widihasani Achmad Yusron Arif Ade Pujianto Adi Surya Adiatma, Biva Candra Lutfi Adipradana, Candra Afif, Muhammad Sholih Afifah Nur Aini Afis Julianto Aflahah Apriliyani Afu Ichsan Pradana Agun Nurul Widiyanto Agung Budi Prasetio Agung Budi Prasetio Agung Budi Prasetio Agung Budi Prasetyo Agung Dwi Cahyanto Agung Susanto Agus Fathurahman Agus Fatkhurohman AGUS PURWANTO Agustin, Tinuk Agustina Srirahayu Agustina, Nova Ahmad Fauzi Ahmad Febri Diansyah Ahmad Fikri Iskandar Ahmad Fikri Iskandar Ahmad Fikri Iskandar Ahmad Hajar Ahsan, Muhammad Rafiqudin Ahsan, Muhammad Rafiqudin Ain, Quratul Ainul Yaqin Ainul Yaqin Ainul Yaqin Aji Said Wahyudi Hidayat Akhmad Dahlan Al Fathir As, Rahmat Saudi Aldy A Kulakat Alfansani, Abdul Rauf Alfin Mahadi Alimuddin Yasin Alin, Octhavia Almi Yulistia Alwanda Alqowiy, Mohd Qorib Alsyaibani, Omar Muhammad Altoumi Alva Hendi Muhammad Alva Hendi Muhammad Alva Hendi Muhammad Alvhinia Meinda Amitaba Alvian Trias Kurniawan Alvian Trias Kurniawan Alvina Felicia Watratan Amir Fatah Sofyan Amir, Fail Amrullah, Ahmad Afief Amrullah, Ahmad Afief Amrullah, Yusuf Amri Andang Wijanarko Andhika Wisnu Widyatama Andhika Wisnu Widyatama Andi Sunyoto Andrie Prajanueri Kristianto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto, Anggit Dwi Anggit Hartanto Anggriandi, Dendi Anip Moniva Anisa Rahmanti Anisya Nursyah Gusman Anjar Setiawan Annisa Rahayu P Antara, Pebri Anwar Sadad Ardi, Abdullah Arfian Hendro Priyono Arham Rahim Ari Rudiyan Arief Setyanto Arief, M.Rudyanto Arif Nur Rohman Arif Rahman Arif Santoso Arif Sutikno Arif, Achmad Yusron Aris Setiyadi aristin chusnul khotimah Arli Aditya Parikesit Armadiyah Amborowaty Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Arvi Pramudyantoro Arya Luthfi Mahadika Asrawi, Hannan Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asrul Abdullah Astica, Yustikamasy Atin Hasanah Aziza Devita Indraswari Bambang Sumantri, R Bagus Bangun Watono Banu Dwi Putranto Basri, Nur Faizal Bayu Setiaji Béjar, Rodrigo Martínez Betri, Tigus Juni Bety Wulan Sari Bima Widianto Bisono, Hadi Hikmadyo Biva Candra Lutfi Adiatma Bonifacius Vicky Indriyono Bonifacius Vicky Indriyono, Bonifacius Vicky Brahmantha, Gede Putra Aditya Budi, Agung Prasetio Buyut Khoirul Umri Cahya Pangestu, Galang Candra Adipradana Candra Aditya Pinuyut Carolina, Vinnesa Patricia Catur Iswahyudi Catur Iswahyudi Catur Riyono Heri Wibowo Cecep Yedi Permana Chan Uswatun Khasanah Chavid Syukri Fatoni Christina Andriyani Constantin Menteng D. 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