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All Journal Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Jurnal Keteknikan Pertanian Tropis dan Biosistem Jurnal Informatika dan Teknik Elektro Terapan agriTECH Indonesian Journal of Science and Technology Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Agrotek Tropika Batoboh : Jurnal Pengabdian Pada Masyarakat Jurnal Peternakan (Jurnal of Animal Science) Jurnal Kesehatan Barometer Agroteknika Jurnal Pengabdian Kepada Masyarakat (JPKM) Tabikpun Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat International Journal of Electronics and Communications Systems Jurnal Agricultural Biosystem Engineering Applied Research in Science and Technology Open Science and Technology Aceh International Journal of Science and Technology Education, Language, and Arts: Jurnal Pengabdian Kepada Masyarakat Journal of Engineering and Technological Sciences
Mareli Telaumbanua
Department Of Agricultural Engineering, Faculty Of Agriculture, Lampung University
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APLIKASI BUDIDAYA SAYURAN HIDROPONIK SEBAGAI SARANA PEMBELAJARAN ANAK USIA DINI Haryanto, Agus; Telaumbanua, Mareli; Triyono, Sugeng; Suharyatun, Siti
Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan Vol. 7 No. 2 (2023)
Publisher : Lembaga Penelitian dan Pengabdian Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jss.v7i2.259

Abstract

Kegiatan ini bertujuan untuk mengenalkan dan mengaplikasikan budidaya sayuran menggunakan teknologi hidroponik kepada anak-anak usia dini. Kegiatan dilaksanakan di TK IT Insan Taqwa di Desa Sidosari, Kecamatan Natar, Kabupaten Lampung Selatan. Kegiatan dilakukan dengan merancang, membuat dan menginstal perangkat budidaya hidroponik sistem ABC menggunakan pipa PVC 3 inchi sepanjang 16 m yang dilengkapi dengan ember kapasitas 80 L, pompa 125 W, dan timer analog 15 menitan. Setelah instalasi perangkat hidroponik, kegiatan dilanjutkan dengan pelatihan budidaya hidroponik yang disertai praktek penanaman sayuran selada. Hasil kegiatan menunjukkan bahwa setelah kurang lebih 4minggu, tanaman selada tumbuh dengan baik yang ditunjukkan oleh figur tanaman yang segar dan besar. Pada akhir minggu ke-5, tanaman selada dipanen oleh para. Dapat disimpulkan bahwa kegiatan ini berjalan dengan sukses yang ditunjukkan dari indikator keberhasilan yang meliputi (1) tersedianya satu unit kit hidroponik,(2) terlaksananya kegiatan sosialisasi dan praktek budidaya hidroponik, (3) terlaksananya budidaya hidroponik yang dikerjakan oleh guru dan siswa TK IT Insan Taqwa dari penanaman hingga panen.
Diseminasi Teknologi Alat Pembuat Pupuk Cair Otomatis Mendukung Pertanian Berkelanjutan Mareli Telaumbanua; Febryan Kusuma Wisnu; Etha ‘Azizah Hasiib; Witangingsih Witangingsih; Rita Anggraini
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 6 No. 2 (2026): Maret 2026 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v6i2.1016

Abstract

Indonesia adalah negara agraris dengan beras sebagai makanan pokok utama. Salah satu sentra pertanian padi di provinsi lampung adalah Desa Sukoharjo I dengan luas lahan persawahan 127 ha. Untuk menghasikan panen padi yang maksimal, petani memiliki kendala, diantaranya harga pupuk kimia yang mahal. Selain itu, juga menghasilkan limbah pertanian. Untuk itu dikembangkanlah pupuk organik cair dari limbah pertanian. Petani memiliki kesulitan dalam membuat pupuk cair, terutama dalam proses pengadukan dan monitoring suhu. Tujuan kegiatan ini ialah meningkatkan keterampilan petani dalam pembuatan pupuk organik cair. Kegaitan dilakukan selama 3 bulan dari bulan Agustus hingga November 2024, melibatkan 20 orang. Metode pelaksanaan kegiatan terdiri dari sosialisasi, diskusi, tanya jawab, demonstrasi dan praktik. Evaluasi kegiatan pengabdian menunjukkan adanya peningkatan pengetahuan mitra kelompok sebesar 75.45 % dan keterampilan sebesar 90.62 %. Dengan demikian, pengabdian ini telah berhasil meningkatkan pengetahuan dan keterampilan mitra dalam pembuatan pupuk organik cair dan  aplikasi alat.
Artificial Neural Network Backpropagation Method for Predicting Soil Nutrient Content: Artificial Neural Network Backpropagation Method for Predicting Soil Nutrient Content Witaningsih Witaningsih; Sri Ratna Sulistiyanti; Mareli Telaumbanua; F X Arinto Setyawan; Helmy Fitriawan; Rita Anggraini
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 14 No. 6 (2025): December 2025
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v14i6.2424-2438

Abstract

Monitoring soil nutrient levels such as nitrogen (N), phosphorus (P), and potassium (K) is essential to support fertilizer efficiency and sustainable agricultural land management. However, commonly used laboratory-based analytical methods are time-consuming and costly. Therefore, alternative approaches that are more practical and efficient are needed. This study aimed to develop an Artificial Neural Network (ANN)-based system for predicting soil nutrient levels using soil physical parameters, namely pH, temperature, moisture content, and electrical resistance, as input variables. Data were collected from red-yellow podzolic soil subjected to different fertilization treatments. After normalization, the data were trained using an ANN model with four input nodes, two hidden layers (each consisting of five nodes), and one output node, employing the backpropagation algorithm and evaluating 27 combinations of activation functions. The training results showed coefficients of determination (R²) of 0.9642 for nitrogen, 1.0000 for phosphorus, and 0.9996 for potassium, with RMSE values of 0.0107, 10.5386, and 0.016457 and RRMSE values of 8.5048%, 0.79786%, and 1.581111%, respectively. During validation, R² values of 0.7218 (nitrogen), 0.6479 (phosphorus), and 0.6137 (potassium) were obtained. Nitrogen prediction exhibited good accuracy (RMSE 0.0222; RRMSE 15.54%), potassium prediction showed moderate accuracy (RMSE 0.2963; RRMSE 28.46%), while phosphorus prediction resulted in relatively high errors (RMSE 1066.77; RRMSE 80.98%), indicating the need for further model development.
Design and Implementation of an Artificial Neural Network Model for Soil Nitrogen Prediction Rita Anggraini; Sri Ratna Sulistiyanti; Helmy Fitriawan; FX Arinto Setyawan; Mareli Telaumbanua; Witaningsih Witaningsih
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 15 No. 2 (2026): April 2026
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtepl.v15i2.732-742

Abstract

The availability of nitrogen in soil is a crucial factor determining crop productivity. However, the measurement of total nitrogen (N-total) content requires considerable time and cost. Therefore, a fast, accurate, and easy prediction method is needed to support the agricultural development. This study aims to develop an Artificial Neural Network (ANN) model based on the backpropagation algorithm to identify soil N-total content using soil pH, moisture content, and soil resistance as input parameters. The model was trained using the trainbr training function with variations of logsig and tansig activation functions and hidden layer structures of 5–5, 8–8, and 12–12 to obtain the best configuration. The training results indicate that the tansig–tansig combination with 8–8 hidden layer structure achieved the highest performance, with a R2 training of 0.953 and a R2 testing of 0.911. The model was implemented in the form of a Graphical User Interface (GUI) application to facilitate field-level prediction. Validation using 40 testing data samples showed a classification accuracy of 70% and an R² value of 0.932 for nitrogen prediction. The model correctly classified 28 data samples out of the total 40 tested data. These results indicate that the proposed model is capable of predicting soil nitrogen content accurately and reliably.
Prototipe Portabel Berbasis pH dan Turbiditas untuk Estimasi Cepat Asam Lemak Bebas pada Minyak Sawit Mentah Abimanyu, Akhmad Asrho Berlian; Wisnu, Febryan Kusuma; Telaumbanua, Mareli; Warji, Warji; Asmara, Sandi; Wijaya, I Gede Krishna
Jurnal Agricultural Biosystem Engineering Vol. 5 No. 1 (2026): March 2026
Publisher : abe.fp.unila.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jabe.v5i1.12903

Abstract

Free fatty acid is an important parameter in determining the quality of crude palm oil. High free fatty acid content can reduce oil quality and cause economic losses in palm oil processing. The conventional method commonly used to determine free fatty acid content is acid-base titration, but this method requires chemicals, laboratory equipment, and relatively long analysis time. This study aimed to design a portable device for rapid detection of free fatty acid content in crude palm oil using pH meter, turbidity meter, and artificial neural network. Oil samples were obtained from oil palm fruitlets with different physical damage levels. Free fatty acid content was measured using titration, while pH and turbidity were used as input variables in the artificial neural network model. The results showed that pH had a relationship with free fatty acid content with a coefficient of determination of 0.3516, while turbidity had a stronger relationship with a coefficient of determination of 0.7636. The best artificial neural network model was obtained using the tansig-logsig-logsig activation function, with R² of 0.9501 and RMSE of 0.6390 in calibration. In the testing stage, the model produced R² of 0.8061 and RMSE of 1.9222. The developed prototype can be used as a rapid method to estimate free fatty acid content in crude palm oil.
Co-Authors Abimanyu, Akhmad Asrho Berlian Adi Susilo Agus Haryanto Agus Haryanto Agus Haryanto Agustin, Stefani Silvi Ahmad Suudi Aldo Christian Alvin Fatikhunnada, Alvin Amieria Citra Gita Amieria Citra Gita Andi Setiadi Andrianto, Rifqi Rhama Anggia Indriyani Annisa Nur Rachmawaty Asil Barus Attamimi, Tahani Farhat Bambang Purwantana Bambang Purwantana Br Ginting, Daria Budianto Lanya Budianto Lanya Cicih Sugianti Dermiyati Dermiyati Diding Suhandy Eka Yana Ekaliana Ekaliana Eko Putra Elhamida Rezkia Amien Etha ‘Azizah Hasiib F X Arinto Setyawan Febryan Kusuma Wisnu Fil'aini, Raizummi Fil’aini, Raizummi Gigih Forda Nama Gita, Amiera Citra Helmy Fitriawan Herry Wardono Huda, Zulmiftah Imam Santosa Indriyawati, Agapetalia Irza Sukmana Jordy, Abdul Rachman Juanto, Benedictus khusnul khotimah Kiromah, Isrofiatul Kurniawan, Ahmad Ridho Kus Hendarto Lilik Sutiarso Lilik Sutiarso M. Haviz Marcus, Patrice Kevin Martinus Martinus Martinus, Martinus Meinilwita Yulia Meizano Ardhi Muhammad Meizano Ardi Muhammad Meizano Ardi Muhammad Mohammad Affan Fajar Falah Mufidah, Zunanik Muhammad Amin Muhammad Haviz Muhammad Pijar Muhammad, Meizano Ardhi Mulyani, Yessi murwanto, bambang Novi Apratiwi Panji Kurniawan Pulung Karo-Karo Purnomo, Cahyo Eko Putri, Laily Rahmadani Ribut Eko Wahyono Ridho Nurrohmanysah Rifqi Rhama Andrianto Ristanti Ristanti Riszal, Akhmad Rita Anggraini Rizza Wijaya Sandi Asmara Saputra, Muhamad Ogas Setiawan, Wahyu Hendi Setyawan, FX Arinto Simanjuntak, Fajar Agustus Siti Suharyatun Sony Ferbangkara Sri Rahayoe Sri Ratna Sulistiyanti Sri Waluyo Sri Waluyo Sugeng Triyono Sugeng Triyono Suskandini Ratih Dirmawati Syah, Aminudin Tamrin Tamrin Telaumbanua, Syukur Telaumbanua, Syukur F Teuku Irmansyah Titin Yulianti Tri Novita Sari, Tri Novita Tri Wahyu Saputra Tri Wahyu Saputra Trisya Septiana Valentino, Fandy Warji Warji Wijaya, I Gede Krishna Winda Rahmawati Winda Rahmawati Winda Rahmawati Wisnu, Febrian Kusuma Witangingsih Witangingsih Witaningsih Witaningsih Yohannes C Ginting