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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Pendidikan Teknologi dan Kejuruan Teknika Jurnal Simetris Bulletin of Electrical Engineering and Informatics Jurnal Ilmu Komputer dan Agri-Informatika Proceeding International Conference on Information Technology and Business Journal of Information Systems Engineering and Business Intelligence KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal Komputasi InComTech: Jurnal Telekomunikasi dan Komputer Jurnal Sains dan Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING PROSIDING KOMUNIKASI Jurnal Teknoinfo Jurnal Teknologi Komputer dan Sistem Informasi Building of Informatics, Technology and Science JUTIS : Jurnal Teknik Informatika Indonesian Journal of Electrical Engineering and Computer Science Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Informasi dan Sains Teknologi Buguh: Jurnal Pengabdian Kepada Masyarakat Jurnal Pepadun Jurnal Siger Matematika AMMA : Jurnal Pengabdian Masyarakat SULUH ABDI : Jurnal Ilmiah Pengabdian Kepada Masyarakat JTKSI (Jurnal Teknologi Komputer dan Sistem Informasi)

Kurnia Muludi

Jurusan Ilmu Komputer FMIPA Universitas Lampung

Author-ID : 2666901

Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Nursing Social Sciences Other

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SISTEM PENDUKUNG KEPUTUSAN PENERIMA BANTUAN OPERASIONAL DAERAH (BOSDA) UNTUK SMK NEGERI 2 BANDAR LAMPUNG Okta Viana; Machudor Yusman; Kurnia Muludi; Aristoteles Aristoteles
Jurnal Pepadun Vol. 1 No. 1 (2020): December
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

This research was conducted to create a decision support system for selection of candidates for receiving Regional Operational Assistance (BOSDA) in SMK Negeri 2 Bandar Lampung. Decision support systems are made based on the Web and selection of candidates for BOSDA acceptance using the method (Simple Additive Weighting). The data used from the data of SMK Negeri 2 Bandar Lampung. The selection process for prospective BOSDA recipients is carried out by collecting data on prospective BOSDA recipients along with criteria in accordance with the conditions of prospective BOSDA recipients. Data that has been received is processed by the system by determining the priority of each criterion and summing the weight of each criterion value. The result of system functional testing is that the system is compatible on the computer on the computer being tested and all menus on the system are running well. System testing is performed on the Administration computer SMK Negeri 2 Bandar Lampung. The system test results using Black Box Testing using 220 prospective BOSDA recipient students. Based on testing that has been conducted on users, the system can simplify the performance of the verification team in conducting the selection so that it can run effectively and efficiently. Based on the accuracy of the results of the system decision, it is stated that 87% has met the criteria for selecting potential recipients who are entitled to BOSDA.

APLIKASI PERPUSTAKAAN DIGITAL BERBASIS ANDROID PADA PERPUSTAKAN JURUSAN ILMU KOMPUTER UNIVERSITAS LAMPUNG Andika Yuda; Kurnia Muludi
Jurnal Pepadun Vol. 2 No. 1 (2021): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

The Computer Science Department Library of The University of Lampung has implemented a library information system. However, the library information system is only to simplify the book search process and is not yet able to display book information directly. Based on this system, to carry out borrowing and returning books, they still use manual methods, so that in terms of service time efficiency, of course, this is still less effective. For services to library users to be more effective, a digital library system is needed that can accommodate users' needs to access book collections online. The development of the digital library was made beforehand on a small scale which was specialized in the Computer Science Department, University of Lampung. This digital library was built using android and web-based programming with the Java programming language, Php, and MySQL database. The data collection method used is the observation and literature study method. The results of the literature study are taking references based on books, journals, and the internet which provide information about previous research regarding digital library applications as well as related information about Android, Android Studio, and language. Java programming. The results of this study indicate that the application has been successfully built using an online database, based on Android and can be run on a mobile device so that the application supports it to be used anytime and anywhere and also this library system makes it easy for admins to manage book data and make it easier to create library reports.

SISTEM INFORMASI ADMINISTRASI SURAT TINGKAT RT BERBASIS WEB (STUDI KASUS RT 040 KELURAHAN PESAWAHAN) Kenny Claudie Fandau; Akmal Junaidi; Kurnia Muludi
Jurnal Pepadun Vol. 2 No. 2 (2021): August
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Reference letters play an important role in the management of population administration at the sub-district (kelurahan) level. When the residents need a reference letter for their specific purpose, they first must manage the request letter from RT and deliver it to the sub-district office. However, during the COVID-19 pandemic, direct interaction among residents and sub-district officers should be avoided. Even, in some circumstances, the services by the sub-district office must be performed online. For this reason, a web-based RT Level Letter Administration Information System was developed by applying the waterfall approach. The user interaction and communication are modeled by Unified Modeling Language (UML). The system is implemented using PHP. The assessment of the functionality of the system by the Black Box Testing indicates that the system conforms to its requirements. This system is ready to deploy in RT 040 of sub-district Pesawahan, Bandar Lampung to serve residents.

SENTIMENT ANALYSIS PROTOKOL KESEHATAN VIRUS CORONA DARI TWEET MENGGUNAKAN WORD2VEC MODEL DAN RECURRENT NEURAL NETWORK LEARNING Ni Putu Ayu Anesca; Kurnia Muludi; Dewi Asiah Shofiana
Jurnal Pepadun Vol. 2 No. 3 (2021): December
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v2i3.86

Sentiment analysis is a computational study of opinion from various opinions, which is part of the work that conducts a review related to the computational treatment of opinions, sentiments, and perceptions of the text. To solve various problems in sentiment analysis, needed a good text representation method. In this study, a deep learning analysis was carried out using the Recurrent Neural Network (RNN) method and the Word2Vec Model as word embedding in sentiment classification. The sentiment dataset used comes from user reviews on Twitter (tweets) on the health protocols implemented by the public from the government's appeal. The results showed that the RNN model using sigmoid activation resulted in the greatest accuracy of 66%. The training process in this test uses 10 epochs and 32 batch sizes so that the precision value for negative sentiment is 54% and for positive sentiment is 67%.

IMPLEMENTASI SUPPORT VECTOR MACHINE DALAM MEMPREDIKSI HARGA RUMAH PADA PERUMAHAN DI KOTA BANDAR LAMPUNG Favorisen Rossyking Lumbanraja; Reza Aji Saputra; Kurnia Muludi; Astria Hijriani; Akmal Junaidi
Jurnal Pepadun Vol. 2 No. 3 (2021): December
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v2i3.90

Machine Learning has been widely used in terms of predictions for analyzing datasets. One method of Machine Learning is Support Vector Machine (SVM). The house has an important role in the survival of human beings. With the times, many developers are competing to build housing. The purpose of this study is to predicted the housing cost using Support Vector Machine. The data in this research used the data of house in Bandar lampung, the price, the location and the building specification. The amount of data used 51 datas and 33 variables with regression and classification, also used 3 kernels and it's model, 12 times first trial and next 6 experiments done with fitur selection. The trial result was kernel regression polynomial model reached the highest R 2 that was 95,99% linear kernel and gaussian kernel reached R 2 90,99% and 81,43% each. While in accuration classification model trial is obtained in 8 class of gaussian kernel as big as 91,18%, and linear kernel and polynimonal kernel get an accuracy of 90,20% and 89,90%.

IMPLEMENTASI TEKNOLOGI PETA VIRTUAL 3D GEDUNG E TEKNIK SIPIL DAN GEDUNG F LABORATORIUM HIDROLIKA FAKUTAS TEKNIK UNIVERSITAS LAMPUNG Aristoteles Aristoteles; Maya Asterita; Yunda Heningtyas; Kurnia Muludi; Admi Syarif
Jurnal Pepadun Vol. 3 No. 1 (2022): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v3i1.95

Lampung University doing out routine activities every new academic year for students especially for new students college who majoring in Civil Engineering, Faculty of Engineering, Introduction about Campus Life for New Students (PKKMB), one of the main agendas of PKKMB is introducing about everyvbuildings and public facilities in Civil Engineering also every building and the room in it. The current state of the COVID-19 pandemic make the University of Lampung conduct learning activy by network (online). So, it's make every students activities not possible to perform direct tracing. Serving method information follows technological developments, one of which is 3D visualization techniques. With using the Multimedia Development Life Cycle (MDLC) system development method, 3D virtual map applications can be developed that can display building layouts and facilities in 3D. This research is Alpha Testing and Customer satisfaction. Alpha Testing provides test results The application can operate on versions in operation android system 7.1 to 10. The application can operate on smartphone with screen specifications from 5.0 inch to 6.5 inches. The application can operate on smartphones from minimum 3GB RAM to 8GB RAM. Customer Satisfaction Respondents stated that the 3D Virtual Map Application of Building E Civil Engineering and Building F of the Hydraulics Laboratory get good results with a percentage index between 87.5% to 95%.

Penerapan Metode Support Vector Machine (SVM) dalam Klasifikasi Penderita Diabetes Mellitus Fanni Lufiana; Favorisen Rosyking Lumbanraja; Yunda Heningtyas; Kurnia Muludi
Jurnal Pepadun Vol. 4 No. 1 (2023): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v4i1.150

Diabetes Mellitus (DM) is a chronic disease characterized by the body's inability to metabolize carbohydrates, fats, and proteins, resulting in increased blood sugar (hyperglycemia) due to low insulin levels. Diabetes is due to a combination of heredity (genetics) and unhealthy lifestyles. Hemoglobin A1c is a blood test used to diagnose and manage diabetes patients when measuring blood sugar levels. This study aims to analyze predictive models for the classification of people with diabetes using R Shiny and evaluate the results of the support vector machine method's classification performance. There are many ways to diagnose diabetes, and the support vector machine is one of the machine learning algorithms used in this study's classification case (SVM). This study uses data from Diabetes 130-US Hospital For Years 1999-2008, which was sourced from the UCI Machine Learning Repository and consists of 34 variables and 84900 records, with dataset distribution and testing techniques using the 10-fold cross-validation method and three kernels in modeling using SVM, namely linear, Gaussian, and polynomial. The results obtained are a simple predictive model analysis system for classifying people with diabetes with shiny, making it easier for users to find out the prediction results and obtain the highest accuracy result, which is 82.76 percent of the gaussian kernel.

Co-Authors ., Rusliyawati Admi Syarif Aflaha Asri Agus Iriawan Agus Wantoro Agus Wantoro Agus, Isnandar Agustinus Eko Setiawan Ahmad Habibullaah Ahyarudin Akbar, Mohammed Raihan Akmal Junaidi Alfabet Setiawan Alfi, Firmansyah Yuni Andika Yuda Andreas Perdana Andri Winata Andrian, Rico Anggun Falianingrum Apri Candra Widyawati Aprilia, Indri Mada Ari Kurniawan Saputra Aristoteles, Aristoteles Asmiati Asmiati Assidik, Reksa Qodri Astria Hijriani Astria Hijriani Astria Hijriani Astria Hijriani, Astria Aulia Putri Ariqa Bayu Ade Candra, Bayu Ade Bernadhita Herindri S. Utami Budiman Ruliansyah candra, bayu ade dedi kurniawan Dian Kurniasari Didik Kurniawan Dimas Aminudin Saputra Djauharie, Arlyandi S Djuadi, Noverman Dwi Hendratmo Widyantoro Dwi Sakethi Eko Priyanto Erlina Ain Andini Eva Diana Sari Evita Fitriasari Fajri Reskanida Fanni Lufiana Fanni Lufiana Fathur Rahmi Febi Eka Febriansyah Febi Eka Febriansyah Heni Sulistiani Heningtyas, Yunda Herlina Herlina Ida Nurhaida Irawati, Anie Rose Jayawarsa, A.A. Ketut Jihan Aferiansyah Kenny Claudie Fandau Khairun Nisa Khalida Zhia Kurnia Muludi KUSPRIYANTO La Zakaria Lia Atika Rani Lumbanraja, Favorisen R M Said Hasibuan Machudor Yusman Machudor Yusman Mahfut Mardiana Mardiana Maya Asterita Meizari, Ary Mohammad Surya Akbar Muhammad Apriansyah Setiawan Muhammad Iqbal Muhammad Irfan Ardiansyah Muharni, Sita Ni Putu Ayu Anesca Noni Kurniasih Noverina Rahmaniyanti Okta Viana Ossy Dwi Endah Wulansari Pratama, Rinaldo Adi Rahmat Safe'i Rangga Firdaus Rangga Firdaus Rendi Irawan Resti Lucyana Reza Aji Saputra Riska Aprilia Romadhoni, Nuzul Rahmat SAIFUL ANWAR Saur Pangihutan Sinurat Saur Pangihutan Sinurat, Saur Pangihutan Shofiana, Dewi Asiah Singagerda, Faurani Santi Siti Maesaroh Sonianto Sonianto Sonianto Sonianto Sri Ratna Sulistiyanti Sri Wahyuningsih Sutyarso Sutyarso Syangap Diningrat Sitompul Tantut Wahyu Setyoko Taqwan Thamrin Tia Ayu Muliana Tiyara Saghira Triloka, Joko Tristiyanto Tristiyanto Tundjung Tripeni Handayani Warsito Warsito Wartariyus Wartariyus Yugo Prasojo, Diaji Yulia K. Wardani Yuni Rahayu Yuni Rahayu, Yuni Zuhri Nopriyanto Zuriana Zuriana

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