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All Journal Bulletin of Social Informatics Theory and Application EKOTON
Diane Pioh
Sam Ratulangi University
Agriculture, Biological Sciences & Forestry Computer Science & IT Environmental Science Social Sciences

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Web-Based System for Medicinal Plants Identification Using Convolutional Neural Network Luther Latumakulita; Franklin Mandagi; Frangky Paat; Dedie Tooy; Sandra Pakasi; Sofia Wantasen; Diane Pioh; Rinny Mamarimbing; Bobby Polii; Jantje Pongoh; Arthur Pinaria; Edwin Tenda; Noorul Islam
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
Evaluation of Land Suitability for Durian (Durio zibethinus M.) Plants In Kombi District, Minahasa Regency Based on Geographic Information Systems Sandra Pakasi; Anatasya Siahaan; Jemmy Najoan; Diane Pioh; Sofia Wantasen
EKOTON Vol. 4 No. 1 (2022): ISSUE JANUARI - JUNI 2022
Publisher : PPLH-SDA, Lembaga Penelitian Unsrat Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35801/ekoton.v5i1.49530

Abstract

This study aims to determine the land suitability class and the distribution map of the durian land suitability class in Kombi District by utilizing the Geographic Information System (GIS). This research was conducted using a survey method in the field. In this study, land units were obtained from the results of overlaying land use maps, soil types, and slopes consisting of 52 land units. The results of this study are that the land suitability class for durian plant development in Kombi District is divided into 2 class classifications, namely marginally suitable (S3) with limiting factor for soil texture (r) and nitrogen (n) and not suitable (N) with slope factor (e) The distribution of land suitability class for durian plants in Kombi District is for marginally suitable class (S3) with an area of 5276.71 ha spread over 16 land units and non-suitable class (N) with an area of 2153.44 ha spread over 7 land units. Keywords: Geographic information system (GIS), land suitability evaluation, durian plant Abstrak Penelitian ini bertujuan untuk mengetahui kelas kesesuaian lahan dan peta persebaran kelas kesesuaian lahan durian di Kecamatan Kombi dengan memanfaatkan Sistem Informasi Geografis (SIG). Penelitian ini dilakukan dengan menggunakan metode survei di lapangan. Pada penelitian ini satuan lahan diperoleh dari hasil overlay peta penggunaan lahan, jenis tanah, dan lereng yang terdiri dari 52 satuan lahan. Hasil penelitian ini kelas kesesuaian lahan untuk pengembangan tanaman durian di Kecamatan Kombi terbagi menjadi 2 klasifikasi kelas yaitu sesuai marginal (S3) dengan faktor pembatas tekstur tanah (r) dan nitrogen (n) dan tidak sesuai (N). ) dengan faktor kemiringan (e) Sebaran kelas kesesuaian lahan untuk tanaman durian di Kecamatan Kombi adalah untuk kelas sesuai marginal (S3) dengan luas 5.276,71 ha yang tersebar di 16 satuan lahan dan kelas tidak sesuai (N) dengan luas 2153,44 ha yang tersebar di 7 satuan lahan. Kata kunci: Sistem informasi geografis (SIG), evaluasi kesesuaian lahan, tanaman durian.
Land Landscape Analysis Using the Digital Elevation Model (DEM) Method in the Tetempangan Tourism Object, Mandolang District, Minahasa Regency Sandra Pakasi; Wiske Rotinsulu; Jooudie Luntungan; Diane Pioh
EKOTON Vol. 4 No. 1 (2022): ISSUE JANUARI - JUNI 2022
Publisher : PPLH-SDA, Lembaga Penelitian Unsrat Manado

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35801/ekoton.v5i1.49537

Abstract

Abstract. Sandra E. Pakasi*), Vicky Fransiskus Solum ,Tommy D. Sondakh , Wiske Ch. Rotinsulu, Frangky J. Paat , Jooudie N. Luntungan, Diane D. Pioh. Land Landscape Analysis Using the Digital Elevation Model (DEM) Method in the Tetempangan Tourism Object, Mandolang District, Minahasa Regency. Ekoton   5. 36-43. This study aims to determine the state of the landscape in the Bukit Tetempangan Tourism Object, Mandolang District, Minahasa Regency. This study uses the Digital Elevation Model (DEM) method to obtain the state of the landscape, elevation data, and slope in the Tetempangan Tourism Object area.   Data collection and processing techniques using the ArcGis 10.3 application. The results obtained in the Bukit Tetempangan Tourism Object Area have 3 slope classes, 0 - 25% (somewhat flat) with an area of 17.8 Ha, 25 - 40% (a bit steep) with an area of 5.33 Ha, and >40% (very steep) with an area of 14.87 ha and a height of 568 meters above sea level (masl). The total altitude data obtained can reach 1986 points. Thus, at this location, there must be a conservation application to prevent erosion and landslides. Keywords: Analysis, Landscapes, Digital Elevation Model
Co-Authors Anatasya Siahaan Arthur Pinaria Bobby Polii Dedie Tooy Frangky Paat Franklin Mandagi Jantje Pongoh Jemmy Najoan Jooudie Luntungan Luther Latumakulita Noorul Islam Rinny Mamarimbing Sandra Pakasi Sofia Wantasen Tenda, Edwin Wiske Rotinsulu