Article Per Year (5 Year)
p-Index From 2020 - 2025
1.704
P-Index
This Author published in this journals
All Journal Jurnal Masyarakat Informatika Jurnal Simetris JAIS (Journal of Applied Intelligent System) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Building of Informatics, Technology and Science Abdimasku : Jurnal Pengabdian Masyarakat Journal of Soft Computing Exploration Jurnal Informatika Polinema (JIP) Jurnal Tata Rias
Agustina, Feri
Unknown Affiliation
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

Published : 11 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 11 Documents
Search

 1   2 
Prediction of Sleep Disorders Based on Occupation and Lifestyle: Performance Comparison of Decision Tree, Random Forest, and Naïve Bayes Classifier Lestiawan, Heru; Jatmoko, Cahaya; Agustina, Feri; Sinaga, Daurat; Erawan, Lalang
(JAIS) Journal of Applied Intelligent System Vol. 8 No. 3 (2023): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/jais.v8i3.8987

Abstract

Health is a very important thing in life. Therefore, to maintain health, we need adequate rest. Without adequate rest, the body will not be healthy and fit. In this study, a person's sleep disorder prediction will be made based on their lifestyle and work. The predictions made will classify sleep disorders that are absent, sleep apnea and insomnia from certain lifestyles and work. The methods used to make predictions are decision tree classifier, random forest classifier and naïve Bayes classifier. The test was carried out using a total of 375 data which was broken down into 70% training data and 30% testing data. The results obtained after testing with test data are by using the decision tree classifier algorithm to get an accuracy of 89.431%, using the random forest classifier algorithm to get an accuracy of 90.244% and by using the naïve Bayes classifier algorithm to get an accuracy of 86.992%.
Pendampingan Pembelajaran Pemrograman Dasar Bagi Siswa SD Negeri Pendrikan Lor 01 Semarang Utomo, Danang Wahyu; Agustina, Feri
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 7, No 2 (2024): MEI 2024
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v7i2.2264

Abstract

Gabor wavelet and multiclass support vector machine for braille image classification Agustina, Feri; Rachmawanto, Eko Hari; Putri, Ni Kadek Devi Adnyaswari; Saputro, Fakhri Rasyid; Lestiawan, Heru; Suprayogi, Suprayogi; Huda, Solichul
Journal of Soft Computing Exploration Vol. 5 No. 3 (2024): September 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i3.474

Abstract

Braille is a letter designed for the visually impaired. As a family with normal vision who have a visually impaired child find it difficult to Teach their child how to learn and understand the process of learning from home. Learning braille requires good finger sensitivity and memory to memorize each letterform, making it difficult to learn.  With this study, braille letters can be detected from the image using the Gabor Wavelet method to extract braille images and combined with the Multiclass Support Vector Machine (Multiclass SVM) algorithm as a classification method for extracted braille images. Data testing was performed using a confusion matrix to determine the level of precision, accuracy, and recall. According to the results of tests performed on 910 braille data using confusion matrix, the highest recognition accuracy was 98,02%. The accuracy of these results is impacted by the parameters of the training process, the training data, and the test data used. This research has the opportunity to be developed in voice-based card recognition to help the visually impaired in the future research.
Comparative Study of Classification of Eye Disease Types Using DenseNet and EfficientNetB3 Jatmoko, Cahaya; Lestiawan, Heru; Agustina, Feri; Erawan, Lalang
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 3, August 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i3.1931

Abstract

The purpose of this research is to build a classification model that can perform the eye disease identification process so that the diagnosis of eye disease can be known and medical action can be taken as early as possible. This research used a dataset which has a total of 4217 eye image data and had 4 main classes namely cataract, diabetic retinopathy, glaucoma, and normal. With the data distribution of 1038 cataract images, 1098 diabetic retinopathy images, 1007 glaucoma images, and 1074 normal images, which of this data will be divided with a data percentage scheme of 50:10:40, 60:10:30, and 70:10:20, to see the results of which dataset division can produce optimal accuracy. In this study, the classification process will use 2 CNN transfer learning architectures, namely DenseNet, and efficientnetb3, which are both trained using the ImagiNet dataset. The results obtained after completing the testing process on the model built using the DenseNet architecture get optimal accuracy when using data division as much as 60:10:30, which is 78.59% while using the efficientnetb3 architecture optimal accuracy results when using the data division of 70:10:20, which is 95.66%. In research on the classification that had previously been done, it is very rare to find a classification process for eye disease types, therefore, in this study, the classification process will be carried out and provide an overview of the eye disease classification process with the CNN transfer learning method with more optimal accuracy results.
Pengenalan Algoritma Komputasi pada Kelas Robotik pada Siswa SD Islam Bintang Juara dengan Metode Computational Thinking Astuti, Erna Zuni; Agustina, Feri; Dolphina, Erlin; Ningrum, Novita Kurnia
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 8, No 1 (2025): JANUARI 2025
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v8i1.2717

Abstract

Kolaborasi robotika dalam pembelajaran di kelas berdampak pada kemampuan berpikir komputasi siswa. Penelitian ini melibatkan 2 orang guru sekolah dasar (Kelas 3-5) dari empat sekolah yang memperkenalkan perangkat robotika. Hasilnya menunjukkan bahwa mengeksplorasi dengan dan menggunakan perangkat dan aktivitas robotik, membantu guru membangun kepercayaan diri dan pengetahuan mereka untuk memperkenalkan pemikiran komputasi kepada siswa muda. Penelitian ini mengidentifikasi bahwa pengembangan profesional guru. Pendekatan pembelajaran terpadu antara sains, teknologi, teknik dan matematika untuk mengembangkan kreativitas siswa melalui proses pemecahan masalah dalam kehidupan sehari-hari. Sehingga perlu difokuskan secara eksplisit bagaimana mengajarkan aktivitas science, technology, engineering, and mathematics (STEM) berbasis robotika yang sesuai dengan perkembangan yang lebih mengedepankan konsep, praktik, dan perspektif komputasi.  
HELM PINTAR BERBASIS ARDUINO PRO MINI UNTUK MENDETEKSI KECELAKAAN Agustina, Feri; Syahputra, Zulfikar Adi; Moses Setiadi, De Rosal Ignatius
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 11, No 2 (2020): JURNAL SIMETRIS VOLUME 11 NO 2 TAHUN 2020
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v11i2.5414

Abstract

Helm merupakan salah satu atribut yang wajib digunakan saat berkendara dengan sepeda motor. Helm berfungsi untuk melindungi kepala dari benturan saat terjadi kecelakaan. Insiden kecelakaan kendaaran bermotor banyak didominasi oleh kendaraan roda dua, dimana pada kasus tertentu dapat dimungkinan korban tidak membawa surat identitas maupun bisa melewati area yang sangat sepi, sehingga sulit dilakukan pertolongan pertama dan identifikasi korban. Penilitian ini bertujuan untuk membuat terobosan baru yaitu menciptakan helm pintar. Helm ini ditambahkan perangkat pintar yang disematkan pada spoiler helm, tujuannya untuk mengirimkan pesan beserta titik lokasi tempat kecelakaan. Perangkat pintar yang disematkan pada spoiler helm dibangun berbasis Arduino pro mini yang dipadukan dengan perangkat GPS, sensor kemiringan untuk mendeteksi kecelakaan, dan modul SIM  800L untuk mengirim notifikasi berupa SMS. Perangkat pintar juga dilengkapi dengan saklar untuk mematikan dan menghidupkan sistem. Berdasarkan hail pengujian Helm pintar sudah dapat bekerja dengan baik, dengan pemicu terjadinya kemiringan sebesar 180° modul SIM 800L dapat mengirimkan pesan berupa titik koordinat yang valid dan dapat dibuka langsung menggunakan google maps. 
Regionprops Segmentation in Convolutional Neural Network for Identification of Lung Cancer Disease and Position Syafira, Zahra Ghina; Sari, Christy Atika; Mulyono, Ibnu Utomo Wahyu; Agustina, Feri; Suprayogi, Suprayogi; Doheir, Mohamed
Jurnal Masyarakat Informatika Vol 16, No 2 (2025): Issue in Progress
Publisher : Department of Informatics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jmasif.16.2.73967

Abstract

Lung cancer is one of the leading causes of death in the world, so early detection is very important to increase the chances of patient recovery. This study aims to develop a method for identifying lung cancer types using Convolutional Neural Network (CNN) combined with Regionprops segmentation technique to determine the position of cancer in CT scan images. The dataset used consists of 1,294 CT scan images classified into three classes, namely Benign, Malignant, and Normal, with variations in the ratio of training and testing data: 80:20, 70:30, 60:40, 50:50, and 40:60. The CNN method is used to perform classification, while the Regionprops segmentation technique is applied to determine the position of the cancer. The results showed that the model with a data ratio of 80:20 achieved the highest accuracy of 99.54%, indicating a very good generalization ability of the model. The Regionprops segmentation technique successfully separated the nodule area in the CT scan image clearly, thus providing more detailed information regarding the position of the cancer. The conclusion of this study shows that the combination of CNN and Regionprops segmentation methods is effective in detecting and analyzing lung cancer and has the potential to be used as a diagnostic tool in the medical field. This study recommends further testing with a larger dataset and optimization of model parameters to improve classification and segmentation performance.
Prediksi Diabetes Mellitus dengan Ensemble Gradient Boosting dan Advanced Feature Engineering Ramadhan, Daniswara Tegar; Agustina, Feri
Building of Informatics, Technology and Science (BITS) Vol 7 No 2 (2025): September 2025
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i2.8011

Abstract

Diabetes mellitus represents a metabolic disease that constitutes a global health challenge with continuously increasing prevalence rates. Early detection through automated prediction systems can help reduce complications and treatment costs. This study develops a diabetes mellitus prediction system using an ensemble gradient boosting approach optimized with advanced feature engineering. The research dataset combines 768 Pima Indians samples with 5,000 samples from diabetes prediction dataset, resulting in 5,768 total data points subsequently balanced using ADASYN technique. Feature engineering process transforms 8 original features into 25 predictive features encompassing diabetes risk scores, BMI categories, age groups, and glucose categories. Three gradient boosting algorithms (XGBoost, LightGBM, CatBoost) along with ensemble voting classifier were optimized using Optuna framework with Tree-structured Parzen Estimator. Evaluation employed accuracy, precision, recall, F1-score, and ROC-AUC metrics through 5-fold cross validation. Results demonstrate LightGBM achieving optimal performance with 97.14% accuracy and 0.9976 ROC-AUC, followed by CatBoost (97.14%, 0.9973) and XGBoost (96.45%, 0.9971). Feature importance analysis identified DiabetesPedigreeFunction, Pregnancies, and SmokingHistory as key predictors. The developed model can be implemented as a diabetes screening system in primary healthcare facilities
PENGARUH PERBANDINGAN JUMLAH PERONA MATA SISA DAN ZINC STEARATE TERHADAP SIFAT FISIK KOSMETIK PERONA MATA AGUSTINA, FERI
Jurnal Tata Rias Vol. 4 No. 03 (2015): Vol.04 No.03 Edisi Yudisium Oktober 2015
Publisher : Program Studi Pendidikan Tata Rias

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jtr.v4n03.13138

Abstract

Abstrak: Kosmetik merupakan salah satu kebutuhan seseorang akan kecantikan karena dapat mengubah karakter wajah, memperbaiki penampilan, dan menambah rasa percaya diri. Kosmetik perona mata adalah salah satu jenis kosmetik riasan atau dekoratif yang memberi warna, bingkai, dan bentuk pada mata. Salah satu jenis kosmetik perona mata adalah jenis padat dan beberapa diantaranya yang beredar di pasaran tidak dapat melekat dengan baik dan biasanya tidak digunakan, disebut perona mata sisa. Kosmetik ini memiliki kandungan yang tidak memenuhi syarat mutu dan bahan yang telah ditetapkan SNI. Salah satu faktor yang menyebabkan perona mata sisa tidak melekat adalah kurangnya zinc stearate. Tujuan penelitian ini adalah 1)untuk mengetahui pengaruh perbandingan jumlah perona mata sisa dan zinc stearate terhadap sifat fisik kosmetik perona mata, meliputi, warna, daya lekat, tekstur, dan aroma; 2)mengetahui perbandingan terbaik kosmetik perona mata sesuai kriteria SNI; serta 3)masa simpan kosmetik perona mata terbaik. Jenis penelitian ini adalah eksperimen. Variabel bebas dalam penelitian ini adalah perbandingan jumlah perona mata sisa dan zinc strearate yang terdiri atas perbandingan 50:50, 60:40, 70:30, 80:20, 90:10. Variabel terikat pada penelitian ini adalah sifat fisik kosmetik perona mata meliputi warna, daya lekat, tekstur dan aroma serta masa simpan. Pengumpulan data tentang sifat fisik kosmetik perona mata dilakukan dengan metode observasi yang dilakukan oleh 30 panelis. Analisis varian tunggal dilakukan untuk mengetahui pengaruh perbandingan jumlah perona mata sisa dan zinc stearate terhadap sifat fisik perona mata dan dilanjutkan dengan uji Duncan; Analisis rataan skor dilakukan untuk mengetahui kosmetik perona mata dengan perbandingan terbaik; Sedangkan untuk mengetahui masa simpan dilakukan dengan uji mikrobiologi. Hasil penelitian menunjukkan bahwa terdapat pengaruh perbandingan jumlah perona mata sisa dan zinc stearate terhadap sifat fisik warna, daya lekat, dan aroma kosmetik perona mata, tetapi tidak berpengaruh pada tekstur. Hal ini karena zinc stearate memiliki tekstur halus sehingga setelah tercampur dapat menghaluskan kosmetik perona mata. Perbandingan jumlah perona mata sisa 60 persen dan zinc stearate 40 persen merupakan hasil kosmetik perona mata terbaik, dengan warna light magenta red, lekat, bertekstur cukup halus dan cukup beraroma. Masa simpan kosmetik perona mata terbaik adalah dua minggu, sehingga perlu dilakukan uji laboratorium lebih lanjut untuk mengetahui data sifat fisik yang lebih valid, uji coba terhadap kulit manusia, dan uji masa simpan lebih lanjut. Kata kunci : perona mata sisa, kosmetik perona mata, zinc stearate, daya lekat. Abstract: Cosmetic is one of peoples makeup required to change face character, increase personal appearance, and improve their self confident. Eyeshadow cosmetic is a kind of decorative cosmetic which giving color, edging, and shape on eyes. One type of cosmetic eyeshadow is a solid type and a few of them in the market can not be attached properly and are not usually used. It called residual eyeshadow. This cosmetic contain the ingredient that do not need the standard stuff and quality stated by SNI. A factor caused residual eyeshadow was not adhesive is the less of zinc stearate. The aim of this research were1) to know the effect of ratio of residual eyeshadow and zinc stearate on eyeshadow cosmetics’sphysical properties including colour, adhesion, texture, and odor, 2) to know the best proportion of eyeshadow cosmetics according to SNI criteria, and 3) to know the shelf life of the best eyeshadow cosmetics. This research was experimental. The independent variable in this research were the ratio of residual eyeshadow and zinc stearate composed of proportions 50:50, 60:40, 70:30, 80:20, 90:10. Meanwhile, the dependent variable was physical properties rating of eyeshadow cosmetics including color, adhesion, texture, and odor, and its shelf life. The data of the eyeshadow cosmetics’s physical properties was collected?? by observation that conducted by 30 panelists. Single variant analysis(Anova) was conducted to know the effect of the ratio of residual eyeshadow and zinc stearate on the eyeshadow cosmetics’s physical properties, and also Duncan test; Mean analysis was conducted to determine the average scores of eyeshadow cosmetics with the best comparison; While microbiological tests was conducted to determine the shelf life of the best eyeshadow cosmetics. Research showed that there are effect of ratio of residual eyeshadow and zinc stearate on physical properties of eyeshadow cosmetics including color, adhesion, and odor, but not on its texture. This is because zinc stearate has smooth texture so that once mixed can refine cosmetic eyeshadow. The ratio of 60 percentage’s residual eyeshadow and 40 percentage’s zinc stearate is the best eyeshadow cosmetic with light magenta red colour, adhesive, and smooth enough textured and good enough odor. The best eyeshadow cosmetic has shelf life up to 2 weeks. Therefore, it should befurther laboratory teststo determine the physical properties ofthe datais more valid, tests on human skin, and further storage life test. Keywords: residual eyeshadow, eyeshadow cosmetics, zinc stearate, adhesion.
Pemanfaatan Metode CNN Menggunakan Arsitektur Alexnet untuk Peningkatan Kinerja Klasifikasi Penyakit Daun Tomat Prabowo, Dwi Puji; Bastian, Henry; Muqoddas, Ali; Pramunendar, Ricardus Anggi; Agustina, Feri
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 15, No 2 (2024): JURNAL SIMETRIS VOLUME 15 NO 2 TAHUN 2024
Publisher : Fakultas Teknik Universitas Muria Kudus

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24176/simet.v15i2.12529

Abstract

Tomat adalah salah satu komoditas hortikultura dengan nilai ekonomi yang tinggi, tantang yang dihadapi oleh petani salah satunya dalah kerentanan penyakit tomat terhadap penyakit. Identifikasi secara visual pada daun sulit diuraikan dengan sekali pandang, sehingga menyebabkan asumsi yang tidak akurat tentang penyakit tersebut. Akibatnya, mekanisme pencegahan yang dilakukan petani menjadi tidak efektif dan berdampak merugikan. Penelitian ini mengusulkan identifikasi penyakit tomat secara automatis menggunakan metode Convolution Neural Network. Dalam makalah ini kami melakukan evaluasi pada metode CNN dengan arsitektur Alexnet dengan konfigurasi layer untuk mencari hasil kinerja terbaik dari penggunaan parameter tersebut pada architektur Alexnet. Pada penelitian ini juga melakukan analisis yang diperoleh dari hubungan antara parameter yang digunakan terhadap kinerja akurasi, dan analisis terhadap dampak penggunaan parameter dengan jumlah dataset daun tomat dari dataset PlantVillage.
Co-Authors ALI MUQODDAS Award Widya Laksana, Deddy Cahaya Jatmoko Candra Irawan Christy Atika Sari De Rosal Ignatius Moses Setiadi Doheir, Mohamed Dwi Puji Prabowo, Dwi Puji Eko Hari Rachmawanto Erlin Dolphina Erna Zuni Astuti Henry Bastian, Henry Heru Lestiawan Lalang Erawan Mulyono, Ibnu Utomo Wahyu Ningrum, Novita Kurnia Putri, Ni Kadek Devi Adnyaswari Ramadhan, Daniswara Tegar Ricardus Anggi Pramunendar Saputro, Fakhri Rasyid Sinaga, Daurat Solichul Huda, Solichul suprayogi Suprayogi Suprayogi Syafira, Zahra Ghina Syahputra, Zulfikar Adi Utomo, Danang Wahyu