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Dedie Tooy
Agricultural Engineering Study Program, Dept. Of Agricultural Technology, Faculty Of Agriculture, Sam Ratulangi University.
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Journal : Bulletin of Social Informatics Theory and Application

 1 
Web-Based System for Medicinal Plants Identification Using Convolutional Neural Network Latumakulita, Luther; Mandagi, Franklin; Paat, Frangky; Tooy, Dedie; Pakasi, Sandra; Wantasen, Sofia; Pioh, Diane; Mamarimbing, Rinny; Polii, Bobby; Pongoh, Jantje; Pinaria, Arthur; Tenda, Edwin; Islam, Noorul
Bulletin of Social Informatics Theory and Application Vol. 6 No. 2 (2022)
Publisher : Association for Scientific Computing Electrical and Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/businta.v6i2.601

Abstract

Indonesia has a variety of medicinal plants that are efficacious for preventing or treating various diseases. Each region has unique medicinal plants, such as in North Sulawesi, there are many medicinal plants with local names of "Jarak" (Jatropha curcas), "Jarak Merah" (Jatropha multifida), "Miana" (Coleus Scutellarioide), and "Sesewanua" (Clerodendron Squmatum Vahl). This research applies the Convolutional Neural Network (CNN) method to identify the types of medicinal plants of North Sulawesi based on leaf images. Data was collected directly by taking photos of medicinal plant leaves and then using the augmentation process to increase the data. The first stage is conducting training and validation processes using 10-fold cross-validation, resulting in 10 classification models. Evaluation results show that the lowest validation accuracy of 98.4% was obtained from fold-4, and the highest was 100% from fold-2. The third stage was to run the testing process using new data. The results showed that the worst model produced a test accuracy of 80.91% while the best model produced an accuracy of 87.73% which means that the identification model is quite good and stable in classifying types of medicinal plants based on its leaf images. The final stage is to develop a web-based system to deploy the best model so people can use it in real-time
Co-Authors A.A. Ketut Agung Cahyawan W Adhiyanto D. Sinadia Afwan Munadi Arthur G. Pinaria Assa, Jan Rudolf Balikan, Chikita M. Bobby Polii Budiman, Glenn Chevin A.T Unsong Christian M. Sumampouw Christine F Mamuaja Christine Mamuaja D. Ludong D. Pangkerego D. Rumambi Daniel P. M. Ludong Daniel P. M. Ludong Daniel P.M. Ludong David P Rumambi David P. Rumambi David Paul Rumambi Defly I. C. Hansang Deisy Pakiti Denny Saroinsong Denny Saroinsong Dewinta Lantang Diana Marice Jitmau E. Kambey Elsje Pauline Manginsela Eva M. R. Mukuan Femi H Elly, Femi H Fidel C. A. Tendeng Fiyoliyandi Djangu Frangky J. Paat Frans Wenur Freeke Pangkerego Gahung, Mikhael Farly Gerson Wohon Grentino Marcelo Durand Handry Rawung Herry F Pinatik Herry F. Pinatik Herry F. Pinatik Herry Frits Pinatik Indriana Indriana, Indriana Ireine A. Longdong Ireine A. Longdong Ireine Adriana Longdong Ireine Adriana Longdong Ireine Longdong Islam, Noorul Jantje Pongoh Jeanne Martje Paulus, Jeanne Martje Jhiro Christian Mailool Johanes F. X. Rogi Johanes F. X. Rogi, Johanes F. X. Juventus Yoel Mochtar Kahar Drakel Kawung, Yosua Koapaha, T. Koibur, Mayko Edison Kusuma, Samuel D. A. Lady C. Ch. E. Lengkey Lady C. Ch. E. Lengkey Lady Ch. E. Lengkey, Lady Ch. E. Lady E. Ch Lengkey Laleleh, Sherina Lamaega, Jolanda Ch E Lantang, Dewinta Leke, Jein R Lengkey, Lady E.Ch. Leo Kalesaran Liwu, Suzanne L. Longdong, Ireine Adriana Ludong, D. Ludong, Daniel P. M. Luther A. Latumakulita Luther Latumakulita Lynda H. Sue Mamuaja, Christine F Mandagi, Franklin Manoppo, Yesica Febriani Maya H. Montolalu, Maya H. Meci Nilam Sari, Meci Nilam Meike C. Kusaly Merywati Maku, Merywati Meylan Kowimbin Mikhael Farly Gahung Mona, Frits Montolalu, Maya Montolalu, Maya Hendrietta Mukhlis Mukhlis Nofri Abdul Azis Amiri Nordy Fritsgerald Lucky Waney Novianti Nari Oessoe, Yoakhim Y.E. Paat, Frangky J Paat, Frangky Jessy Pakiti, Deisy Pangkerego Freeke Pangkerego, D. Pinatik, Herry F Pinatik, Herry Frits Pioh, Diane Prahmawati, Endah Renaldy S Mamangkey Reyfhel H. F. Tagah Rine Kaunang Rinny Mamarimbing Rinny Mamarimbing Rizaldi Akbar Kaplale Robert Molenaar Ruland Rantung Rumambi, David P Rumambi, David Paul Samuel D. A. Kusuma Sandra E. Pakasi Sandra Pakasi Satria Wati Pade Selvie Tumbelaka Silvia Lakumani Sofia Wantasen Stefy Wagiu Steven Humena Suzanne L. Liwu Syahrir, Risal N. R. Tadung, Sri Wanni Jumiati Tangkeallo, Sindy C. T. Telinus Yigibalom Teltje Koapaha Tenda, Edwin Tineke Langi Tineke M. Langi Umboh, Riel J J Verby N.D. Rumintjap Verby N.D. Rumintjap, Verby N.D. Veronika, Reni Walangitan, Khesilya E. Waney, Nordy Fritsgerald Lucky Wangko Iwan Marchel Yoakhim Y.E. Oessoe