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All Journal JURNAL KESEHATAN LINGKUNGAN: Jurnal dan Aplikasi Teknik Kesehatan Lingkungan The Spirit of Society Journal : International Journal of Society Development and Engagement SINTECH (Science and Information Technology) Journal Jurnal Informatika Universitas Pamulang Journal of Information Technology and Computer Engineering Jurnal PkM (Pengabdian kepada Masyarakat) JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Informatics and Vocational Education
Febri Liantoni
Universitas Sebelas Maret
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Environmental Science Public Health Social Sciences Other

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PERBAIKAN KONTRAS CITRA MAMMOGRAM PADA KLASIFIKASI KANKER PAYUDARA BERDASARKAN FITUR GRAY-LEVEL CO-OCCURRENCE MATRIX Febri Liantoni; Agus Santoso
SINTECH (Science and Information Technology) Journal Vol. 3 No. 1 (2020): SINTECH Journal Edition April 2020
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v3i1.528

Abstract

In this era to recognize breast tumors can be based on mammogram images. This method will expedite the process of recognition and classification of breast cancer. This research was conducted classification techniques of breast cancer using mammogram images. The proposed model targets classification studies for cases of malignant, and benign cancer. The research consisted of five main stages, preprocessing, histogram equalization, convolution, feature extraction, and classification. For preprocessing cropping the image using region of interest (ROI), for convolution, median filter and histogram equalization are used to improve image quality. Feature extraction using Gray-Level Co-Occurrence Matrix (GLCM) with 5 features, entropy, correlation, contrast, homogeneity, and variance. The final step is the classification using Radial Basis Function Neural Network (RBFNN) and Support Vector Machine (SVM). Based on the hypotheses that have been tested and discussed, the accuracy for RBFNN is 86.27%, while the accuracy for SVM is 84.31%. This shows that the RBFNN method is better than SVM in distinguishing types of breast cancer. These results prove the process of improving image construction using histogram equalization and the median filter is useful in the classification process.
Prediksi Penambahan Kasus Covid-19 di Indonesia Melalui Pendekatan Time Series Menggunakan Metode Exponential Smoothing Calvin Mikhailouzna Gibran; Sulis Setiyawati; Febri Liantoni
Jurnal Informatika Universitas Pamulang Vol 6, No 1 (2021): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/informatika.v6i1.9442

Abstract

The Covid-19 pandemic in Indonesia has emerged starting in 2020. To know the development of cases, a good calculation is needed. A prediction system can help in analyzing accurate data on positive causes, cures, and deaths. The right prediction or forecast can be the answer to the question of the impact that will occur, forecasting will provide an overview to the government and the community so that it is hoped that related parties can prepare for future impacts or even reduce the number of cases growth. In this study, the Exponential Smoothing method was used as a prediction calculation. This method is simple but effective in producing accurate predictions. Forecasting data used comes from the Indonesian government with the assumption that the data is valid and reliable. Based on research that has been carried out to predict the increase in new cases of the Indonesian National Covid-19, the best alpha (α) value is 0.33 with an SSE of 1048027,939. This shows that the number of cases is increasing. The results of forecasting in this study using the time series approach and the SES method are more suitable for predicting the percentage increase in cases than knowing the exact number.
Desain Smart Body Vest Untuk Meminimalisir Kecelakaan Kerja Menuju Indonesia Zero Accident Mohammad Iskandar Nur Fahmi; Muhammad Bagus Panuntun; Andayani Yuwana Sari; Febri Liantoni
JURNAL KESEHATAN LINGKUNGAN: Jurnal dan Aplikasi Teknik Kesehatan Lingkungan Vol 17, No 2 (2020): Jurnal Kesehatan Lingkungan Volume 17 No. 2, Juli 2020
Publisher : Poltekkes Kemenkes Banjarmasin Jurusan Kesehatan Lingkungan Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (388.754 KB) | DOI: 10.31964/jkl.v17i2.217

Abstract

The construction sector plays an important role in a country's economy. This is because construction projects such as the construction of buildings, roads, bridges and other infrastructure are one of the benchmarks of economic progress and civilization of a country. Work accidents on construction projects can cause work to stop and result in financial losses and decreased work productivity. According to the Minister of Manpower in 2018 the number of work accidents has increased from the previous year even from the data of the Central Statistics Agency stating that the majority of construction workers are junior high school graduates and below. This is one of the factors causing the increase in occupational accidents in the construction sector. Losses from work accidents are also included in workers' losses, damage to equipment and materials wasted due to work accidents. Occupational health and safety (K3) risk control is very important as a preventive effort to prevent a bigger event. One such control is the use of Personal Protective Equipment (PPE) or more commonly called personal protective equipment (PPE). The existence of PPE is important for workers to minimize the impact of accidents so that each company is obliged to use PPE. This study aims to minimize the number of work accidents in Indonesia, especially in the construction sector. The method used in making the body vest is the addition of an airbag by applying the fall detection algorithm to the K-Nearest Neighbor (KNN), which is to calculate the Euclidean distance which is the distance between the sample and training data and then determine the k nearest data from the sample so that the sample can be classified on the sensor and microcontroller. The way it works is when a collision or a hard collision occurs, workers will generally be thrown or dropped then there will be a change in the acceleration of the position of the body wearing a body vest. The change in acceleration triggers the development of airbags on the body vest. This is expected to reduce injuries to vital organs in the worker's body.
Increased Mammogram Image Contrast Using Histogram Equalization And Gaussian In The Classification Of Breast Cancer Febri Liantoni; Coana Sukmagautama; Risalina Myrtha
JITCE (Journal of Information Technology and Computer Engineering) Vol 4 No 01 (2020): Journal of Information Technology and Computer Engineering
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (613.675 KB) | DOI: 10.25077/jitce.4.01.40-44.2020

Abstract

Breast cancer is one of the most common diseases among women in several countries. One of the most common methods to diagnose breast cancer is mammography. In this study, we propose a classification study to differentiate benign and malignant breast tumors based on mammogram image. The proposed system includes five major steps, i.e. preprocessing, histogram equalization, convolution, feature extraction, and classification. Image is cropped using region of interest (ROI) at preprocessing stage. In this study, we perform image contrast quality enhancement of the mammogram to view the breast cancer better. Image contrast enhancement uses histogram equalization and Gaussian filter. Gray-Level Co-Occurrence Matrix (GLCM) is used to extract the mammogram features. There are five features used i.e. entropy, correlation, contrast, homogeneity, and variance. The last step is to classify using naïve Bayes classifier (NBC) and k-nearest neighbor (KNN). Based on the hypothesis, the accuracy of NBC method is 90% and the accuracy of KKN method is 87.5%. So, the mammogram image contrast enhancement is well performed.
Workshop And Motivation For Improving Student Skills Through The Information And Communications Technology Febri Liantoni; Yusfia Hafid Aristyagama; Nurcahya Pradana Taufik Prakisya; Puspanda Hatta; Cucuk Wawan Budiyanto
THE SPIRIT OF SOCIETY JOURNAL : International Journal of Society Development and Engagement Vol 5 No 1 (2021): September 2021
Publisher : LPPM of NAROTAMA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/scj.v5i1.1431

Abstract

In the digital age, the role of information technology is needed to face competition in the community. Information and communication technology is an important element in contributing to changes that are fundamental to the structure of operations and management of organizations, education, transportation, health, and research. The internet is like two sides of a coin, the content offered is positive and negative, both are very dependent on the behavior of its users. The ease of access to the internet is increasingly being felt by the public with increasingly cheap hardware such as tablets and laptops as well as wider connection support. Various efforts to stem negative information continue to be pursued by various elements of society, but it is not effective if the user behavior is not changed. Teenagers are among the most vulnerable in the misuse of advances in internet technology, so it needs serious efforts to provide the right knowledge and skills in utilizing these advancements. By conducting workshops and motivation to improve the abilities and skills of Girimarto 1 High School students, it is hoped that school students can face the development of the digital era more readily. The results of this training gained a high level of satisfaction with the material that had been carried out.
Pelatihan Desain Dan Internet Untuk Mewujudkan Desa Berliterasi Digital Sutrisno Sutrisno; Muhammad Hamka Ibrahim; Subuh Pramono; Meiyanto Eko Sulistyo; Febri Liantoni
Jurnal PkM (Pengabdian kepada Masyarakat) Vol 6, No 2 (2023): Jurnal PkM: Pengabdian kepada Masyarakat
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jurnalpkm.v6i2.8673

Abstract

Saat ini dunia sudah berada pada era digital dan revolusi industri 4.0, yang berhubungan dengan Internet dan teknologi digital. Kemajuan teknologi informasi dan komunikasi (TIK) yang pesat khususnya internet menjadikan pekerjaan lebih ringan. Dengan kemampuan penggunaan teknologi informasi dan dipadukan kesadaran literasi di era digital maka masyarakat akan mampu menggunakan TIK untuk hal-hal yang positif dan bermanfaat serta terhindar dari hal-hal yang negatif. Namun banyak masyarakat yang belum bisa menggunakan TIK seperti membuat dokumen, desain dasar, dan pemakaian internet. Untuk itu perlu digencarkan pelatihan-pelatihan TIK untuk masyarakat. Pelatihan ini berkerjasama dengan Yayasan Hubbul Khoir yang terletak di Dukuh Ngentak, Bulakrejo, Sukoharjo. Pada pelatihan desain dengan menggunakan aplikasi Inkscape. Aplikasi Inkscape dipilih karena aplikasi ini gratis dan sangat popular untuk saat ini. Pelatihan desain ini telah terlaksana pada tanggal 12-16 September 2020. Karena masih pandemic Covid-19, pelatihan diadakan secara online lewat Whatsapp, Telegram dan Zoom. Peserta menjadi paham dan mengetahui seluk beluk internet dan penggunaan desain sesuai dengan modul/ materi yang telah diberikan.
Inovasi Naive Bayes Classifier dalam Prediksi Rating Game untuk Pengalaman Gaming yang Lebih Menarik Febri Liantoni; Dini Erlinawati; Yuliana Rizki Ikhsanty; Fadil Indra Sanjaya; Mulia Sulistiyono
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 11, No 3 (2023)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v11i3.67228

Abstract

Ada beberapa jenis game yang muncul dan dibuat untuk menarik perhatian para gamers. Beberapa permainan mampu mengobati rasa lelah, panik, sedih, bosan, dan kebanyakan mengisi waktu luang. Penelitian ini bertujuan untuk mengembangkan dan menerapkan metode Naive Bayes Classifier yang inovatif dalam prediksi rating game. Dengan menggunakan pendekatan yang memberikan rekomendasi rating yang akurat untuk setiap permainan yang akan dirilis, dengan tujuan meningkatkan pengalaman gaming pengguna. Dataset yang digunakan dalam penelitian ini mencakup informasi tentang game-game yang telah dirilis sebelumnya, termasuk rating yang diberikan oleh para pengguna. Hasil eksperimen menunjukkan bahwa metode Naive Bayes Classifier yang dikembangkan kami memiliki kinerja yang baik dalam memprediksi rating game. Penelitian ini memiliki potensi untuk meningkatkan pengalaman gaming pengguna dengan memberikan rekomendasi rating yang akurat. Dengan menggunakan metode Naive Bayes Classifier yang inovatif diharapkan dapat membantu pengguna dalam membuat keputusan yang tepat tentang permainan yang akan mereka mainkan.
Improvement of Self Regulated Learning through Flex-Blended Learning Model Assisted by Learning Management System Jihan Amami; Basori; Febri Liantoni
Journal of Informatics and Vocational Education Vol. 7 No. 3 (2024): Journal of Informatics and Vocational Education - November
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v7i3.2407

Abstract

Self-regulated learning is an essential aspect for students so that these students can organize and carry out learning activities independently. Self-regulated learning of students during the pandemic has a low average level. Self-regulated affects student achievement. The higher the level of student self-regulated learning, the better the achievement, and vice versa. This study aims to determine the differences and improvement of student self-regulated learning in applying the flex-type blended learning model assisted by Google Classroom. The method in this study uses quantitative methods with an experimental approach. Data collection was carried out through questionnaires and pretest-posttest as supporting data. The study's results showed differences in self-regulated learning before and after applying the flex-type blended learning model assisted by Google Classroom. This is evidenced by the results of the t-test on self-regulated learning, which shows significant differences. Then calculate the increase in self-regulated learning using N-Gain. In self-regulated learning, an N-Gain score of 0.323 is obtained, which means it is included in the medium category. Then to see the effect of self-regulated learning on student achievement, an N-Gain test was carried out on the pretest and post-test scores with a score of 0.436, which means it is included in the moderate category. From these results, it can be concluded that the increase in self-regulated learning is directly proportional to the rise in student achievement.
Co-Authors Agus Santoso Andayani Yuwana Sari Basori Calvin Mikhailouzna Gibran Coana Sukmagautama Cucuk Wawan Budiyanto Dini Erlinawati Fadil Indra Sanjaya Jihan Amami Meiyanto Eko Sulistyo Mohammad Iskandar Nur Fahmi Muhammad Bagus Panuntun Muhammad Hamka Ibrahim Mulia Sulistiyono Nurcahya Pradana Taufik Prakisya Puspanda Hatta Risalina Myrtha Subuh Pramono Sulis Setiyawati Sutrisno Sutrisno Yuliana Rizki Ikhsanty Yusfia Hafid Aristyagama