Article Per Year (5 Year)
p-Index From 2021 - 2026
7.8
P-Index
This Author published in this journals
All Journal Jurnal Teknologi Informasi dan Ilmu Komputer RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Informatics for Educators and Professional : Journal of Informatics METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Nasional Komputasi dan Teknologi Informasi Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal KOMPUTIKA - Jurnal Sistem Komputer JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Tekno Kompak bit-Tech Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Tekinkom (Teknik Informasi dan Komputer) BERNAS: Jurnal Pengabdian Kepada Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal Ilmu Komputer dan Sistem Informasi (JIKOMSI) Jurnal Pengabdian kepada Masyarakat Nusantara Community Empowerment Inspirasi Ekonomi : Jurnal Ekonomi Manajemen Journal Of Information And Technology Unimor (JITU) Jurnal Abdimas Kartika Wijayakusuma Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Sisfotek Global Indonesian Community Journal Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Atma Inovasia Digital Transformation Technology (Digitech) Smart Techno (Smart Technology, Informatic and Technopreneurship) Journal of Informatics and Computing Jurnal Krisnadana Jurnal Umum Pengabdian Masyarakat (JUPEMAS) Jurnal Komputer dan Teknologi (JUKOMTEK) Glow: Jurnal Pengabdian Kepada Masyarakat Jurnal Sains Sistem Informasi Journal of Mathematics, Computation and Statistics (JMATHCOS)
Baso, Budiman
Universitas Timor
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Mathematics Neuroscience Nursing Public Health Social Sciences Transportation Veterinary Other

Published : 61 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 61 Documents
Search

 2   3   4   5   6 
SISTEM INFORMASI GEOGRAFIS DAERAH RAWAN BENCANA DENGAN FITUR PENDUKUNG KEPUTUSAN PENENTUAN LOKASI PEMBANGUNAN RUMAH DI KOTA KEFAMENANU Budiman Baso; Leonard Peter Gelu; Anastasia Kadek Dety Lestari
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 1 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i1.1052

Abstract

Kefamenanu City is located in East Nusa Tenggara (NTT) Province, precisely in North Central Timor Regency, this city borders land directly with the State of Timor Leste. The population density level in Kefamenanu city is relatively lower when compared to other regions in NTT, but by looking at the fact that most of the area is dominated by dry land and the increase in population growth rate that always increases every year, then in terms of providing land for housing locations will be a challenge for the TTU Regency Government. Determining the location of houses requires consideration of various aspects such as water availability, disaster vulnerability, public facilities, distance from trade centers, road conditions, transportation facilities, and land prices. This research aims to develop a Geographic Information System (GIS) that provides information related to disaster-prone areas and is equipped with a Decision Support System (SPK) using the Simple Additive Weighting (SAW) method. SAW method is used to help people in choosing housing locations based on the criteria they have. The results show that this system is effective in providing information and supporting decision making on housing locations that are safer and more comfortable, and can minimize potential disasters. In conclusion, the proposed system can be a valuable tool for local governments and communities in planning housing development in disaster-prone areas.
Identifikasi Sebaran Karakteristik Kriminal di Indonesia Tahun 2021 Menggunakan Model-Based Clustering Chrisinta, Debora; Gelu, Leonard Peter; Baso, Budiman
Journal of Mathematics, Computations and Statistics Vol. 5 No. 2 (2022): Volume 05 Nomor 02 (Oktober 2022)
Publisher : Jurusan Matematika FMIPA UNM

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

Abstract

Crime is an aspect that affects the smooth running of the economy in society. The importance of the government's role in minimizing the occurrence of crime can be done by knowing the distribution of criminal characteristics in each province. The Model-Based Clustering method can help identify these characteristics. The Clustering process is carried out by ensuring that the distribution of variables is close to the normal distribution as seen from the QQplot and the independence of variable. The results of the Clustering show that there are two characteristics of criminality that are spread across the province of Indonesia. Identify the characteristics of the distribution of crime using the average value in each of the optimal clusters that have been obtained. The first cluster shows the distribution of 16 provinces with lower crime categories, while the second cluster shows the distribution of 18 provinces with high crime categories.
Implementasi Metode Rapid Application Development dalam Pembuatan Aplikasi Bahasa Isyarat Bagi Penyandang Tunarungu Berbasis Android (Studi Kasus : SLB Negeri Benpasi Kefamenanu) Bukifan, Priska Vianey; Rema, Yasinta O. L; Risald; Baso, Budiman
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i2.3282

Abstract

Sign language applications are designed to facilitate deaf people in communicating. Deaf people experience hearing impairment or loss of hearing function that is congenital or appears due to certain factors, such as infection or long-term exposure to loud noises. As a result of hearing limitations, they experience difficulties in speaking or hearing, so they are taught sign language in schools which makes it easier for them to communicate. Sign language is a means of communication that uses lip movements, body movements or facial expressions in order to convey communication messages quickly. Sign language applications are built using the RAD (Rapid Application Development) method because in the process of making applications, it can be done in a short and fast time and ensures adjustment of features from users. Android is used in the process of making this application, because of its wide use and easy access. This application provides a sign language translation feature in the form of videos so that it is easy to understand for deaf people.
PERANCANGAN PROTOTIPE SISTEM INFORMASI MANAJEMEN PPM PADA LPPM UNIVERSITAS TIMOR BERBASIS WEBSITE Baso, Budiman; Risald, Risald
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1742

Abstract

The rapid advancement of information technology has encouraged higher education institutions to improve the efficiency of managing Research and Community Service (PPM) activities. This study aims to design and develop a web-based PPM Management Information System prototype for LPPM Universitas Timor. Using the Research and Development (R&D) method, the study involves need analysis, system design, development, testing, and evaluation of the prototype. The system is designed to facilitate proposal management, status tracking, evaluation processes, and reporting. The research findings indicate that the prototype significantly enhances the efficiency of PPM management by providing a user-friendly interface and automated notification features. Testing with end-users, including lecturers and LPPM administrators, yielded positive feedback on ease of use and process transparency. However, improvements are needed in areas such as system performance when handling large documents and the addition of email-based reminder features. In conclusion, the developed prototype serves as a foundational framework for building more comprehensive PPM management systems in the future, supporting efficiency, productivity, and academic objectives at Universitas Timor.
SISTEM PAKAR MENDIAGNOSA PENYAKIT PADA TANAMAN JAGUNG MENGGUNAKAN METODE TEOREMA BAYES BERBASIS WEBSITE Usfinit, Katarina D.M; Kelen, Yoseph P.K.; Baso, Budiman; Ullu, Hevi Herlina
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 1 (2025): EDISI 23
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i1.5487

Abstract

Kemajuan teknologi telah mendorong terciptanya sistem pakar untuk meningkatkan efisiensi di berbagai sektor, termasuk pertanian. Tujuannya penelitian ini yakni Penelitian ini bertujuan mengembangkan membangun media bantuan yang memanfaatkan teknologi berbasis website dengan menerapkan ilmu biologi yang mana membantu dalam mengetahui dan meneliti kelainan mengenai tanaman jagung dengan menggunakan metode Teorema Bayes. Sistem ini menganalisis 24 gejala dan 4 jenis penyakit yang sering menyerang tanaman jagung di Kabupaten Timor Tengah Utara, Indonesia. Model pengembangan yang dipakai adalah Waterfall, yang mencakup tahapan penelitian yang teratur dan searah. Hasil penelitian menunjukkan bahwa sistem ini efektif dalam mendiagnosis penyakit jagung dengan tingkat akurasi tinggi, seperti diagnosis penyakit hawar daun yang mencapai probabilitas 96,04%. Sistem ini tidak hanya membantu petani dalam mendiagnosis penyakit, tetapi juga memberikan solusi penanganan yang tepat untuk meningkatkan produktivitas pertanian jagung di daerah tersebut
Identifikasi penyakit pada foliage tanaman cendana menggunakan algoritma ID3 berdasarkan fitur GLCM dan Color Moment Seran, Krisantus Jumarto Tey; Baso, Budiman
AITI Vol 22 No 1 (2025)
Publisher : Fakultas Teknologi Informasi Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/aiti.v22i1.73-83

Abstract

The main cause of the decreased economic value of sandalwood trees is disease. There are several ways to detect (identify) diseases in sandalwood trees, one of which is through the leaves. One way to identify the disease is by observing the color and shape of the leaves affected by the disease using image processing or computer vision. In this study, the GLCM feature is combined with the Color Moment feature to analyze the disease of the Sandalwood leaves, especially the mean value of each RGB in the Sandalwood leaf image. The ID3 algorithm is chosen as a learning method to analyze texture and color extraction data to determine the type of disease. The data testing results showed an accuracy level of 92.31% when the GLCM feature is combined with the Color Moment feature. It indicates that the combination of these features provides good results in detecting and classifying the type of disease in Sandalwood leaves.
Introduction of Indonesian Significant Alphabet Images (BISINDO) using The Convolutional Neural Network Algorithm Kabut, Stefanus; Kelen, Yoseph Pius Kurniawan; Baso, Budiman; Chrisinta, Debora
JURNAL SISFOTEK GLOBAL Vol 15, No 1 (2025): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v15i1.15678

Abstract

Bisindo alphabet recognition is the process by which a computer system or software recognizes and recognizes the letters of the Bisindo alphabet. The Bisindo alphabet is a special alphabet used to communicate with people who are hearing or speech impaired. This process uses image processing and machine learning techniques to identify and classify each letter based on its shape and visual characteristics. This study used a dataset consisting of 520 Kaggle images divided into 26 categories. These images are resized, normalized and scaled up to improve model performance. A Convolutional Neural Network (CNN) model was developed and achieved 99.12587% accuracy after training. After the model was developed, the API was implemented using Flask. API functionality is tested using online interactions, ensuring accurate responses to image classification before implementation in mobile applications.
Rancang Bangun Sistem Keamanan Dan Monitoring Suhu Serta Kontrol Lampu Kandang Ayam Broiler Berbasis Internet Of Things (IoT) Egas De Jesus Martins Corbafo; Yoseph P. K. Kelen; Budiman Baso; Willy Sucipto
Smart Techno (Smart Technology, Informatics and Technopreneurship) Vol. 5 No. 2 (2023)
Publisher : Primakara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59356/smart-techno.v5i2.95

Abstract

In this research, a tool was designed to help chicken farmers in their daily farming activities. The common problems faced by chicken farmers are theft and the need to manually check the temperature inside the coop. Therefore, a Security and Temperature Monitoring System as well as Broiler Chicken Coop Lamp Control Based on the Internet of Things (IoT) was created using Arduino Uno as the controller for the entire system. The tools used in this system are Arduino Uno, HC-SR04 Ultrasonic sensor, Buzzer, DHT22, 16x2 LCD, ESP8266, Breadboard, Relay, and Incandescent Lamp. The method used to create this tool is the engineering design method in the automation system. The test results showed that the system was able to maintain the temperature inside the chicken coop according to the ideal conditions for Broiler chickens.
SISTEM PAKAR MENDIAGNOSA GEJALA PENYAKIT KULIT PADA BALITA MENGUNAKAN METODE CERTANTY FACTOR BERBASIS WEB Sutal, Dominika Muti; Kelen, Yoseph Pius Kurniawan; Baso, Budiman
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 2 (2025): EDISI 24
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i2.5610

Abstract

Kulit merupakan bagian dari tubuh manusia yang memiliki banyak peran. Salah satunya sebagai alat pengeluaran berupa kalenjer keringat dan tempat di buatnya vitamin D dengan bantuan sinar matahari. Pada beberapa macam penyakit kulit peran ini terganggu karna kulit terlihat bersisik, tebal, kasar dan kering. Melihat permasalahan tersebut, penulis berusaha merancang dan membangun suatu aplikasi sistem pakar untuk bisa digunakan mendeteksi penyakit kulit dengan tujuan mengimplementasikan metode Certainty Factor ke dalam aplikasi sistem pakar diagnosa penyakit kulit pada balita (studi kasus : Puskesmas Mamsena). Metode yang digunakan dalam pengembangan sistem pakar untuk diagnosa penyakit kulit pada balita ini adalah metode waterfall atau yang biasa disebut metode air terjun. Hasilnya menunjukkan penyakit yang diderita oleh anak, nilai tingkat kepercayaan dari hasil diagnosa tersebut, serta solusi yang dapat dilakukan untuk penyakit yang diderita. Penerapan sistem Pakar ini dapat membantu masyarakat atau para orang tua dalam menangani penyakit kulit pada balita dengan tepat. Kesimpulan yang didapat User dapat menganalisa sendiri penyakit kulit yang dialami oleh balita berdasarkan informasi yang disediakan dalam website. Sistem pakar yang telah dibangun ini masih memiliki beberapa kekurangan sehingga dibutuhkan pengembangan lebih lanjut agar lebih baik lagi.
Analisis Pengaruh Data Augmentasi Pada Klasifikasi Tenun Menggunakan Deep Learning Berbasis Convolutional Neural Network: Analisis Pengaruh Data Augmentasi Pada Klasifikasi Tenun Menggunakan Deep Learning Berbasis Convolutional Neural Network Baso, Budiman; Risald, Risald; Muhammad Akhyar, Ramaulvi
Journal of Information and Technology Vol. 5 No. 1 (2025): Journal of Information and Technology Unimor (JITU)
Publisher : Department of Information Technology, Universitas Timor, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32938/jitu.v5i1.9209

Abstract

This research develops a classification model of Timorese weaving motifs using Deep Learning method based on Convolutional Neural Network (CNN). Timor's diverse weaving motifs reflect the richness of local culture, but manual classification takes a long time and is prone to subjectivity. To improve model performance, Data Augmentation techniques, such as flipping, rotation, and zooming,, are applied to enrich the variety of pre-processed Timor weaving image datasets. In addition, the CNN model was developed using Transfer Learning techniques to improve training efficiency. Experimental results show that CNN without augmentation achieves 95.00% accuracy, 95.00% precision, 95.08% recall, and 95.04% F1-score, with a computation time of 2.37 minutes at 30 epochs. Meanwhile, applying Data Augmentation increased the model accuracy to 96.66%, precision 96.66%, recall 96.87%, and F1-score 96.77%, and reduced the computation time to 2.11 minutes. Analysis of the effect of augmentation data shows that increasing the variety of images contributes to the improvement of model generalization. Therefore, the use of CNN with Data Augmentation is a more optimal solution in the classification of Timorese weaving motifs. This research has the potential to support cultural preservation as well as the development of an artificial intelligence-based weaving motif identification system.
Co-Authors Achmad, Fariz Akhyar, Ramaulvi Muhammad Alfonsus Jefri Oematan Anastasia Kadek Dety Lestari Arisandi, Diki Avin Nahak Ayaq, Siriakus Lalang L Aziz, Syaefudin Banusu, Junita Banusu, Junita Gregoria Benu, Luky Wandika Bere, Mery Ernawati Biandina Meidyani Blegur, Ernes Josias Bukifan, Priska Vianey Chrisinta, Debora Crisintha, Debora Egas De Jesus Martins Corbafo Eko, Yulita Eli , Maria Yuliana Fetronela Rambu Bobu Gelu, Leonard Peter Gelu, Leonard Peter Getrudis Mali, Matilde Haeruddin Handrianus Vianey Melin Wula Herlina Ullu, Hevi Hernur Yoga Priyambodo Hevi Herlina Ullu Hevi Herlina Ullu Irit Maulana Sapta Kabut, Stefanus Kolo, Yesualda Rogeria Korbaffo, Yesus Armiro Kristoforus Fallo Leonard P. Gelu Leonard Piter Gelu Lestari, Anastasia Kadek Dety Lisnahan, Charles V. Luky Wandika Benu Manane, Desmon R. Manane, Desmon Redikson Manek, Patricia G. Manek, Patricia Gertrudis Maneno, Regolinda Manikin, Josep Antonius Maria Yuliana Eli Mudjur, Elisabeth Lusyanti Muhammad Akhyar, Ramaulvi Nababan, Darsono Nanik Suciati Nurul Huda Nurul Huda Patricia Gertrudis Manek Priska Vianey Bukifan Renaldi Yulvengki Kolloh Risald Rizald Saniyatul Mawaddah Selan, Yokmiawanti Sitorus, Detson Ray Halomoan Sutal, Dominika Muti Syaefudin Aziz Tey Seran, Krisantus Jumarto Ullu, Hevi Herlina Usfinit, Katarina D.M Valeriano Fajar Alexandro Nipu Willy Sucipto Willy Sucipto Yasinta O. L Rema Yasinta O.L Rema Yayu Ulfaningsi Subagio Yeremia, Elfira Yeremias Lake Yohanes D B Pay Yohanes D. B Pay Yoseph Pius Kurniawan Kelen Yunita, Elisa