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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) MANAJEMEN HUTAN TROPIKA Journal of Tropical Forest Management Jurnal Silvikultur Tropika (JST) Jurnal Pustakawan Indonesia BIOTROPIA - The Southeast Asian Journal of Tropical Biology Jurnal Simetris Bulletin of Electrical Engineering and Informatics Jurnal Ilmu Komputer dan Agri-Informatika Journal of Degraded and Mining Lands Management Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management) Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Scientific Journal of Informatics Edulib JOIN (Jurnal Online Informatika) Jurnal Teknologi dan Sistem Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control BAREKENG: Jurnal Ilmu Matematika dan Terapan Bina Hukum Lingkungan ILKOM Jurnal Ilmiah EDUMATIC: Jurnal Pendidikan Informatika Computer Science and Information Technologies Nusantara Science and Technology Proceedings International Journal of Electronics and Communications Systems Jurnal Pustakawan Indonesia Jurnal Informatika dan Teknologi Informasi Bina Hukum Lingkungan Jurnal INFOTEL Policy Brief Pertanian, Kelautan, dan Biosains Tropika Scientific Journal of Informatics BACA: Jurnal Dokumentasi dan Informasi
Imas Sukaesih Sitanggang
Department Of Computer Science, Faculty Of Mathematics And Natural Sciences, IPB University, Jl. Meranti Wing 20 Level V, IPB Dramaga Campus Bogor, 16680, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences Transportation Veterinary

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Journal : Scientific Journal of Informatics

 1 
Decision Support System for Evaluation of Peatland Agroecology Suitability in Pineapple Plants Putra, Fiqhri Mulianda; Sitanggang, Imas Sukaesih; Sobir, Sobir
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.23819

Abstract

A Pineapple (Ananas comosus (L.) Merr.) It is one of the leading commodities in the Indonesian horticultural sub-sector. Based on data from PDSIP in the last 5 years the development of pineapple production has increased but not too high as well as the harvested area. One of the areas that cultivate pineapple plants in Riau Province is Kampar Regency. Its production in 2015 was 8,482 tons, down from 20,046 tons in 2013. However, this amount is not optimal considering the area in Kampar Regency is still large enough for pineapple cultivation. Kampar District has a potential peatland of around 191,363 ha. About half of the area is thin peat, while the rest varies from moderate to deep peat. The success or failure of peatland management for cultivated land is highly dependent on the condition of its characteristics and the mastery and scientific understanding of the character of peat. This shows the need to evaluate the carrying capacity of land-based on its suitability so that it can be used as a guide in wise land-use planning. This study aims to create a fuzzy inference system model with Mamdani method in determining the agroecological suitability of peatlands for pineapple plants, this is due to the target class of land suitability parameters based on FAO provisions, namely S1, S2, S3, and N. Based on the obtained model, decision support systems will be developed for the suitability of peatland agroecology for pineapple plants.
Decision Support System for Evaluation of Peatland Agroecology Suitability in Pineapple Plants Putra, Fiqhri Mulianda; Sitanggang, Imas Sukaesih; Sobir, Sobir
Scientific Journal of Informatics Vol 7, No 1 (2020): May 2020
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v7i1.23819

Abstract

A Pineapple (Ananas comosus (L.) Merr.) It is one of the leading commodities in the Indonesian horticultural sub-sector. Based on data from PDSIP in the last 5 years the development of pineapple production has increased but not too high as well as the harvested area. One of the areas that cultivate pineapple plants in Riau Province is Kampar Regency. Its production in 2015 was 8,482 tons, down from 20,046 tons in 2013. However, this amount is not optimal considering the area in Kampar Regency is still large enough for pineapple cultivation. Kampar District has a potential peatland of around 191,363 ha. About half of the area is thin peat, while the rest varies from moderate to deep peat. The success or failure of peatland management for cultivated land is highly dependent on the condition of its characteristics and the mastery and scientific understanding of the character of peat. This shows the need to evaluate the carrying capacity of land-based on its suitability so that it can be used as a guide in wise land-use planning. This study aims to create a fuzzy inference system model with Mamdani method in determining the agroecological suitability of peatlands for pineapple plants, this is due to the target class of land suitability parameters based on FAO provisions, namely S1, S2, S3, and N. Based on the obtained model, decision support systems will be developed for the suitability of peatland agroecology for pineapple plants.
CO and PM10 Prediction Model based on Air Quality Index Considering Meteorological Factors in DKI Jakarta using LSTM Wattimena, Emanuella M C; Annisa, Annisa; Sitanggang, Imas Sukaesih
Scientific Journal of Informatics Vol 9, No 2 (2022): November 2022
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v9i2.33791

Abstract

Purpose: This study aimed to make CO and PM10 prediction models in DKI Jakarta using Long Short-Term Memory (LSTM) with and without meteorological variables, consisting of wind speed, solar radiation, air humidity, and air temperature to see how far these variables affect the model.Methods: The method chosen in this study is LSTM recurrent neural network as one of the best algorithms that perform better in predicting time series. The LSTM models in this study were used to compare the performance between modeling using meteorological factors and without meteorological factors.Result: The results show that the use of meteorological predictors in the CO prediction model has no effect on the model used, but the use of meteorological predictors influences the PM10 prediction model. The prediction model with meteorological predictors produces a smaller RMSE and stronger correlation coefficient than modeling without using meteorological predictors.Novelty: In this paper, a comparison between the prediction model of CO and PM10 has been conducted with two scenarios, modeling with meteorological factors and modeling without meteorological factors. After the comparative analysis was done, it was found that the meteorological variables do not affect the CO index in 5 air quality monitoring stations in DKI Jakarta. It can be said that the level of CO pollutants tends to be influenced by factors other than meteorological factors.  
Metadata Modeling of LoRa Based Payload Information for Precision Agriculture Tea Plantation Eddy Prasetyo Nugroho; Taufik Djatna; Imas Sukaesih Sitanggang; Irman Hermadi; Agus Mulyana; Sri Wahjuni; Heru Sukoco
Scientific Journal of Informatics Vol 10, No 2 (2023): May 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i2.43432

Abstract

Purpose: The purpose of this study is to model the metadata of Payload Information on Agriculture Drones which consists of the results of images computational and the Onboard system of the Drone.Methods: The stages of the research were carried out with the process of forming Payload information metadata from the Agriculture Drone with sensors/actuators based on the architecture and computing with Image Processing or Computer Vision on the camera captures. This study describes the metadata modeling process formed from the Internet of Things system with Drone and GCS communication based on the Long Range or Long-Range Wide Area Network protocols with Payload information consisting of drone data and image computation results. Result: The result obtained is the formation of Payload information from LoRa-based Drones with a frame size of 142 bytes. Novelty: Payload information is formed into a metadata model indicator with the formation scheme being part of the tea plantation dataset. The metadata model will be test expected to obtain field data on Drones and GCS communication in the LoRaWAN Network in tea plantations which are rural environments. 
Co-Authors -, Rachmawati Abdul Rahman Saleh Abdul Wakhid Aditia Yudhistira Agus Buono Agus Mulyana Agus Purwito Ahmad Khusaeri Albar, Israr Alusyanti Primawati Anak Agung Istri Sri Wiadnyani Andi Nurkholis Andita Wahyuningtyas Anna Qahhariana Annisa Annisa Annisa Annisa Annisa Awal, Elsa Elvira Aziz Kustiyo Baba Barus Badollahi Mustafa Boedi Tjahjono Bramdito, Vandam Caesariadi Despry Nur Annisa Ahmad, Despry Nur Annisa DEWI APRI ASTUTI Dhani Sulistiyo Wibowo Dini Hayati Dwi Purwantoro Sasongko Eddy Prasetyo Nugroho Efendi, Zuliar Erliza Hambali Fakhri Sukma Afina Febriyanti Bifakhlina Firman Ardiansyah Hardhienata, Medria Kusuma Dewi Hari Agung Adrianto Hasibuan, Lailan Sahrina Hefni Effendi Hendra Rahmawan Hendra Rahmawan Herawan, Yoga Heru Sukoco HUSNUL KHOTIMAH I Nengah Surati Jaya Ikhsan kurniawan Irman Hermadi Istiqomah, Nalar Ivan Maulana Putra Khairani Krisnanto, Ferdian Kurnianto, Andi Lailan Syaufina Lilis Syarifah Luki Abdullah Marlina, Dwi Medria Kusuma Dewi Hardhienata Miftah Farid Mohammad, Farid mufti, abdul Muhammad Abrar Istiadi Muhammad Asyhar Agmalaro Muhammad Murtadha Ramadhan Nia Kurniati Peggy Antonette Soplantila Prasetyo Nugroho, Eddy Pudji Muljono Purwanti , Endang Yuni Purwanti, Endang Yuni Putra, Fiqhri Mulianda Raden Fityan Hakim Raharja, Aditya Cipta Ramadhan, Jeri Rd. Zainal Frihadian Ridwan Raafi'udin Rina Trisminingsih Risa Intan Komaraasih Rizki, Yoze Safrudin, Muhammad Safrul Sakti, Harry Hardian Santoso, Angga Bayu Satyawan, Verda Emmelinda Shelvie Nidya Neyman Sobir Sobir Sonita Veronica Br Barus Sonita Veronica Br Barus Sony Hartono Wijaya Suci Indrawati Irwan Sulistyo Basuki Suradiradja, Kahfi Heryandi Suria Darma Tarigan Surjono Hadi Sutjahjo Syarifah Aini Taihuttu, Helda Yunita Taufik Djatna Taufik Hidayat Tenda, Edwin Tiurma Lumban Gaol Toto Haryanto Trisminingsih, Rina Unik, Mitra Wa Ode Rahma Agus Udaya Manarfa Wattimena, Emanuella M C Wisnu Ananta Kusuma Wulandari WULANDARI Yenni Puspitasari Yoanda, Sely