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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Journal of Economics, Business, & Accountancy Ventura Journal of Information Systems Engineering and Business Intelligence Tech-E Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputasi JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Tekno Kompak Building of Informatics, Technology and Science Kumawula: Jurnal Pengabdian Kepada Masyarakat Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Sisfotek Global Journal of Computer System and Informatics (JoSYC) Community Development Journal: Jurnal Pengabdian Masyarakat IJPD (International Journal Of Public Devotion) Jurnal Teknologi dan Sistem Tertanam Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Data Mining dan Sistem Informasi Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service J-SAKTI (Jurnal Sains Komputer dan Informatika) Jurnal Sisfotek Global COMMENT: Journal of Community Empowerment Journal of Engineering and Information Technology for Community Service Jurnal Ilmiah Edutic : Pendidikan dan Informatika Jurnal Pengabdian kepada Masyarakat (Nadimas) Jurnal Media Borneo Jurnal Informatika: Jurnal Pengembangan IT Jurnal Media Celebes Journal of Artificial Intelligence and Technology Information Journal of Information Technology, Software Engineering and Computer Science The Indonesian Journal of Computer Science
Alita, Debby
Universitas Teknokrat Indonesia
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Public Health Social Sciences Other

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Implementasi Convolutional Neural Network dengan Arsitektur Alexnet Untuk Klasifikasi Penyakit Kulit Andi Kurniawan; Muhammad Pajar Kharisma Putra; Debby Alita
Jurnal Media Celebes Vol. 1 No. 2 (2024): Volume 1 Number 2 January 2024
Publisher : CV. Keranjang Teknologi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/mediacelebes.v1i2.42

Abstract

Penyakit kulit ialah kelainan pada kulit yang disebabkan karena adanya jamur, kuman, parasit, virus maupun infeksi yang dapat menyerang siapa saja dan kapan saja. Pendeteksian penyakit kulit sejak dini dapat mempercepat pengobatan untuk mencegah penularan ke wilayah yang lebih luas. Pentingnya deteksi dini penyakit kulit memungkinkan orang yang terinfeksi untuk segera memulai pengobatan yang tepat. Penelitian ini dilakukan untuk melakukan pengujian performa dari algoritma CNN untuk mengetahui seberapa efektif algoritma CNN dalam melakukan klasifikasi penyakit kulit. Objek yang digunakan dalam penelitian ini berjumlah 1200 data penyakit kulit yang terdiri dari tiga class yaitu penyakit kulit scabies, melanoma, dan juga nevus dengan perbandingan 80% digunakan sebagai data latih dan 20% sebagai data uji. Sebelum di lakukan pengolahan data, dilakukan terlebih dahulu proses data preprocessing yang bertujuan untuk mempersiapkan data sebelum proses pelatihan model. Data akan diolah menggunakan metode Convolutional Neural Network (CNN) arsitektur Alexnet untuk melakukan tugas klasifikasi. Hasil dari pengujian kinerja model menggunakan metode Confusion Matrix diperoleh nilai akurasi mencapai 81%, sehingga metode CNN dengan arsitektur AlexNet dapat digunakan untuk tugas klasifikasi penyakit kulit dengan cukup baik.
Sentimen Analisis Vaksin Covid-19 Menggunakan Naive Bayes Dan Support Vector Machine Debby Alita; RB Ali Shodiqin
Journal of Artificial Intelligence and Technology Information Vol. 1 No. 1 (2023): Volume 1 Number 1 March 2023
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jaiti.v1i1.20

Abstract

Vaccine administration in Indonesia has now reached the booster vaccine stage, various types of vaccines have been given to the Indonesian people from the Sinovac, AstraZeneca, Sinopharm, Moderna, Pfizer vaccines, etc. Not a few Indonesian people use several types of vaccines that are offered up to booster vaccines, but there are some people who think they are still infected with this Covid virus with severe symptoms. Another opinion is that there is also a vaccine. In 2019, people were shocked by a new virus from Wuhan, China, namely the corona virus or called COVID-19 (Corona Virus Disease 2019). The government invites the public to get the Covid-19 vaccine in order to form herd immunity or group immunity to the Covid-19 virus. Sentiment analysis can be used to evaluate a service performance and so on. So the author will conduct a comparison between the Naive Bayer Classifier method and the Support Vector Machine to find out which method is more efficient in knowing people's accurate views of the Covid-19 vaccine. The performance test results of the two methods show that the performance of the Naive Bayes Classifier method (Accuracy 72.88%, Precision 43.49%, Recall 54.95%, and average performance 57.10%) is higher than the average performance of the Support Vector Machine method (Accuracy 77.00% , Precision 75.00%, Recall 7.70%, and average performance 53.52%). Based on the average performance value of the Naive Bayes Classifier method, it can be considered more efficient than the Support Vector Machine method.
Application of SAW Method in Decision Support System for Determination of Exemplary Students Fadila Shely Amalia; Debby Alita
Journal of Information Technology, Software Engineering and Computer Science Vol. 1 No. 1 (2023): Volume 1 Number 1 January 2023
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/itsecs.v1i1.9

Abstract

The decision support system for determining exemplary students using the SAW method is a solution to existing problems so that the results of the assessment of exemplary students become more effective and efficient in terms of time and selection of exemplary students. Decision-making in the determination of exemplary students can be more detailed and more accurate from existing candidates to truly exemplary prospective students who meet the established criteria. This SAW method can help teachers in making decisions using weights that have been determined by the school. The results of the decision support system for determining exemplary students using the SAW method for Rank 1 were obtained by M. Pebi Ramadhan with a value of 0.992857. Rank 2 was obtained by Adittyo Yunanta with a value of 0.984286. Rank 3 was obtained by Aldo Al Farigi with a value of 0.982857.
Online Marketing Readiness of MSMEs in Indonesia: A Perspective of Technology Organizational Environmental Framework Asmawati, Asmawati; Ahmad, Imam; Suwarni, Emi; Alita, Debby; Hasrina, Cut Delsi
Journal of Economics, Business, and Accountancy Ventura Vol. 27 No. 1 (2024): April - July 2024
Publisher : Universitas Hayam Wuruk Perbanas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14414/jebav.v27i1.3399

Abstract

Micro, Small, and Medium-sized Enterprises (MSMEs) play a crucial role in the economic landscape of tourism areas, offering collective services that enhance tourist experiences and convenience at destinations. One key effort to promote tourism is enhancing the technological readiness of MSMEs. This study aims to evaluate the preparedness of MSMEs to adopt e-commerce technology. Data was gathered through interviews and questionnaires distributed randomly to 184 business operators. The research utilized the Technology Organizational Environmental (TOE) framework, encompassing ten indicators identified from various sources. Data analysis was conducted using Structural Equation Modeling (SEM) with four hypotheses. The findings reveal that both organizational readiness and external environmental support have a positive impact on technology adoption readiness. Furthermore, organizational readiness significantly mediates the relationship between environmental support and technological readiness. Therefore, it is essential to develop the organizational readiness of MSMEs to facilitate the adoption of e-commerce technology.
Application of Data Mining for Student Department Using Naive Bayes Classifier Algorithm Yohana Tri Utami; Debby Alita; Ade Dwi Putra
Tech-E Vol. 5 No. 2 (2022): Tech-E
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v5i1.1012

Abstract

SMAN 02 Negeri Agung does not have a system that can assist schools in determining majors. The problem that occurs is that SMAN 02 Negeri Agung, when doing majors, still uses existing data, for example, using a majoring interest questionnaire, there are questions about the interests that students want, and the values of their junior high school report cards, which consist of Indonesian, Mathematics, Science, Social Studies, and English. However, there are still many students who choose majors not based on their interests or historical grades, such as following friends' choices. This can hinder student academic activities in the future, which will affect the value and development of student potential. With this major system, it is hoped that it can help schools and students minimize errors in determining and choosing a major. Based on the problems described above, the authors want to apply the Naïve Bayes method, which will produce a high level of accuracy in determining new student majors more effectively and efficiently.
PELATIHAN PEMANFAATAN METAVERSE DALAM PEMBELAJARAN DI SMA NEGERI 1 BATANGHARI Sari, Raras Kartika; Ahmad, Imam; Puspaningtyas, Nicky Dwi; Alita, Debby; Sena, Fikih Yuhada; Santika, Yuli; Rani, Ni Made Suka
COMMENT: Journal of Community Empowerment Vol 3, No 1 (2023): June
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/comment.v3i1.236

Abstract

AbstractThis activity was carried out with the aim of providing Metaverse training in learning at SMA Negeri 1 Batanghari. The purpose of implementing this training is to provide new insights and knowledge for students about the Metaverse. Metaverse training activities in learning are carried out with offline training for class XII school students. The training was carried out with the first stages, namely providing field surveys, pre-tests, providing training and post-tests. After being given presentation of material about Metaverse, an average of  99.4% of students gave a positive response to the implementation of the activity.Student agree that Metaverse can increase interest in learning, Metaverse can help in understanding thematerial, help to be more active in learninf, increase learning motivation and Metaverse is very easy to use in the learning process. This is because Metaverse is the new Technologi in learning process.Keywords: training, metaverse, learningAbstrakKegiatan ini dilaksanakan dengan tujuan untuk memberikan pelatihan Metaverse dalam Pembelajaran di SMA Negeri 1 Batanghari. Tujuan dari pelaksanaan pelatihan adalah untuk memberikan wawasan dan pengetahuan baru bagi peserta didik tentang Metaverse. Kegiatan pelatihan Metaverse dalam pembelajaran dilaksanakan secara tatap muka kepada peserta didik kelas XII. Pelatihan dilaksanakan dengan tahapan awal yaitu melaksanakan survey lapangan, pemberian pre tes, pelaksanaan pelatihan, dan pemberian post test. Setelah pelaksanaan pelatihan Metaverse, rata-rata 99,4% peserta didik memberikan respon positif terhadap pelaksanaan pelatihan Metaverse. Peserta didik memberikan respon positif dan setuju bahwa Metaverse dapat membuat peserta didik tertarik pada pembelajaran, lebih dapat memahami materi, lebih aktif dalam pembelajaran, lebih termotivasi dalam pembelajaran, dan dapat membuat peserta didik lebih mudah dalam belajar, lebih mudah digunakan saat pembelajaran. Peserta didik sangat antusias saat mengikuti pelatihan, hal ini dikarenakan Metaverse merupakan tekhnologi baru yang mereka gunakan dalam pembelajaran. Kata kunci: pelatihan, metaverse, belajar
Implementation of Iot-Based Smart Farms for Optimizing Chicken Productivity and Product Digitalization to Improve Administration Quality Alita, Debby; Samsugi, Slamet; Suhadi, Miki
International Journal of Public Devotion Vol 6, No 2 (2023): August - December 2023
Publisher : STKIP Singkawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26737/ijpd.v6i2.4779

Abstract

Lampung People Berjaya is one of the visions of the Lampung provincial government to fulfill conditions of safety, advanced culture, competitiveness and prosperity, so that to achieve this the government has one target, namely to move the agricultural and livestock sectors in Bumi Ruwai Jurai so that Lampung can become an agricultural locomotive. and livestock barns. Berkah Poultry Farm (BUF) is a broiler and stud chicken farm located in Jati Agung, South Lampung. The main problems that are a priority to be resolved are: 1) The temperature and humidity control device for the cage is still semi-automatic; 2) Management of daily livestock data is still done manually; 3) There is still low understanding of breeders and their employees regarding chicken farming. Based on the priority problems faced by partners, the solutions offered by the proposing team for this PKM scheme are: 1) Implementing Smart Farm: IoT-based Automatic Temperature and Humidity Control Device; 2) Implement Smart Farm: Web-based livestock data management application; 3) Providing educational training on livestock cultivation for breeders and all BUF employees. The results of this service are an increase in the ability of Berkah Unggas Farm employees as evidenced by pretest and posttest results, increased chicken productivity as evidenced by increased chicken weight and more accurate data reports on consistent temperatures.
Sistem Pengolahan Persediaan Ayam Boiler Berbasis Web Mobile Krisna, Anan; Alita, Debby; Samsugi, S.
Jurnal Media Borneo Vol. 1 No. 3 (2024): Volume 1 Number 3 April 2024
Publisher : CV. Keranjang Teknologi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/mediaborneo.v1i3.62

Abstract

Berkah Unggas Farm Jati Agung is a form of individual business engaged in the business of buying and selling boiler chickens. Based on interviews with the owner of Berkah Unggas Farm that the process of processing chicken inventory data is processing and recording that still uses manual methods (recording using a ledger) so that data inaccuracies, there is a high risk of human error, such as data writing errors, such as incorrect stock or errors in recording transactions. Data inaccuracies can lead to incorrect decisions and disrupt the operational efficiency of boiler chicken entry and exit. Based on these problems, a mobile web-based boiler chicken management system was created. The system, designed and built using the waterfall system development method, and the system was tested using ISO 25010. The system that has been built can help the process of processing chicken inventory data that produces more accurate data, minimizing the risk of human error, especially in data processing, such as data writing errors, such as incorrect stock or errors in recording transactions, facilitating boiler chicken inventory management faster than the previous system. The results of system feasibility testing using ISO 25010 get results of 97%. On a likert scale that the feasibility of the information system that has been made has a very good success, so that the system is feasible to be implemented and implemented at Berkah Unggas Farm Jati Agung.
Perbandingan Random Forest dan SVM dalam Analisis Sentimen Quick Count Pemilu 2024 septiana, ika; Alita, Debby
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.6640

Abstract

The implementation of the 2024 elections is regulated in the General Election Commission Regulation (PKPU) Number 3 of 2022, which also stipulates the election schedule and stages.After the simultaneous general elections that took place on February 14, 2024, problems arose among the public regarding the Quick Count results, especially for the Presidential election.The Quick Count results themselves generated various opinions, both positive and negative.In the post-election Twitter page, there are many conversations in cyberspace related to the Quick Count results on Twitter. Thus, sentiment analysis can be used to classify tweets and comments about the 2024 election quick count results into three categories, namely positive, negative, and neutral.Thus, this analysis is expected to provide some significant benefits related to the quick count results in the 2024 election. Random Forest and Support Vector Machine are two machine learning techniques used to measure how accurate the resulting sentiment analysis is. From the results of the research that has been carried out, there are 2000 data collected during February 2024. After preprocessing and labeling, there are 1,116 positive class data, 730 negative class data and 154 neutral class data.From the results of the comparison of the algorithms evaluated, the accuracy value of the two algorithms was obtained.The Random Forest algorithm produces an accuracy of 78%, while the SVM algorithm produces an accuracy of 80%.This shows that in sentiment analysis on the 2024 election quick count, the SVM method obtained a greater accuracy value compared to Random Forest.
Analisis Sentimen Inses di Social Media menggunakan Algoritma Naïve Bayes Salsabilla, Tasya; Alita, Debby
Jurnal Informatika: Jurnal Pengembangan IT Vol 9, No 3 (2024)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v9i3.6611

Abstract

Sexual violence, especially against women and children, is a serious problem in Indonesia. Cases are increasing every year, including incest, which involves sexual relations between close family members. Girls, who are often considered weak and vulnerable, are the main victims. The latest data from the National Commission on Violence Against Women records a decrease in incest cases from 1,210 in 2017 to 215 in 2020. However, attention is still needed, especially because biological fathers are the largest perpetrators. This research uses the Naïve Bayes algorithm for sentiment analysis. This algorithm is an effective classification method based on Bayes' theorem with simple assumptions but is quite effective. Assuming that each feature in the data is independent, Naïve Bayes can work well in text analysis. The research results showed an accuracy rate of 94%. Continued attention to sexual violence, especially incest, is needed to protect vulnerable girls. Protection efforts must continue to be improved, including the application of sentiment analysis methods such as Naïve Bayes for monitoring and early detection. Public awareness and cross-sector cooperation are also key in overcoming this phenomenon.
Co-Authors ., Rusliyawati Adam Indra Sakti Ade Dwi Putra Ade Setiawan alifa, Chairunnisa fadia Andi Kurniawan Andi Nurkholis Anggraini, Jenny Aris Munandar As Shidiq, M Febrian Asmawati Asmawati Asmawati Asmawati Bambang Satrio Gandhi Cholid Fadilah Hasri Danuarta, Ervin Dedi Darwis Dinda Titian Lestari Dyah Aminatun Dyah Ayu Megawaty Dyah Ayu Megawaty Emi Suwarni Erliyan Redy Susanto Fadila Shely Amalia Feby Amanda Fenty ariany Handika, H Hasrina, Cut Delsi Hayatunnufus Hayatunnufus Heni Sulistiani Ika Septiana Imam Ahmad Imam Ahmad Indah Sari Irwan Tubagus Isnain, Auliya Rahman Jepi Supriyanto Krisna, Anan Lathifah L Lathifah Lathifah Lisa Ariyanti Mandasari, Berlinda Miswanto Miswanto Muhammad Najib Dwi Satria Muhammad Pajar Kharisma Putra Muhammad Saefudin Muhtad Fadly Munti Sarida Nur Rokhman Nurhasan Nugroho Nurman Satya Marga Nurman Satya Marga Nuroji Nuroji Permata Permata Prita Dellia Puspaningtyas, Nicky Dwi Pustika, Reza Putra, Ade Dwi Putri Sukma Dewi Rahmawati, Ira Tri Rani, Ni Made Suka RB Ali Shodiqin Rillya Arundaa Riska Amalia Praptiwi S. Samsugi Salsabilla, Tasya SANTIKA, YULI Saputri, Gita Aprinda Sari, Raras Kartika Sena, Fikih Yuhada Setiawansyah Setiawansyah Sigit Priyanta Styawati Styawati suaidah suaidah Suhadi, Miki Surahman, Ade Suwarni, Emi Syahwaluddin, Risal Taufiq Martiwansyah Tenda, Edwin Wang, Junhai YOHANA TRI UTAMI, YOHANA TRI Yuri Rahmanto Yusra Fernando