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ACCELERATION OF STARTS UP BUSINESS IN AGRICULTURE THROUGH IMPROVEMENT OF PRODUCTION, FINANCIAL AND MARKETING SYSTEM Laila, Alfu; Cahyanti, Lutfy Ditya; Etica, Use; Trisnaningrum, Niken
ASEAN Journal of Community Engagement Vol. 3 No. 1 (2019)
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Due to decrease unemployment graduates, University of Darussalam Gontor-Indonesia provided the requirement through strengthening entrepreneurship development program for starts up business in Agricultural sector. The aims of the program are 1) improvement of production; 2) building financial system and 3) expanding network both of domestic and aboard market. To achieve the objectives, this program created four strategic levels which were 1) assessment; 2) training; 3) mentoring; and 4) evaluation. This program applied to 8 starts up business including in sub sectors of horticulture production, aquaculture, livestock and agro-industrial. The program resulted increasing on crop production, improvement of feasibility business analysis and internet marketing used.

MORPHOLOGICAL VARIATION OF EARLY DAYS TO FLOWERING ON LOCAL RICE ACCESSIONS COLLECTED FROM PONOROGO Niken Trisnaningrum; Alfu Laila
Jurnal Teknosains Vol 7, No 1 (2017): December
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/teknosains.31134

Local rice germplasm may play an important role in improving rice quality. One of the important to improve rice cultivar trait is days to flowering. Ponorogo is one of district of center rice production area where the farmers cultivate local rice varieties which is early days to flowering or short vegetative phase. Exploration of local early days to flowering rice accessions in Ponorogo resulted in 9 accessions. Flowering times ranged 51 to 91 days after sowing. Based on morphological variation, there were variation of plant height, number of leaves, number of tiller, number of panicle, number of grains per panicle, flowering time, grain size and weight of 100 grains. Morphological dendrogram made possible to identify three groups at similarity 0.88.

ISOLATION AND CLONING OF cDNA OF GENE ENCODING FOR METALLOTHIONEIN TYPE 2 FROM MELASTOMA AFFINE SUHARSONO SUHARSONO; NIKEN TRISNANINGRUM; LULUT DWI SULISTYANINGSIH; UTUT WIDYASTUTI
BIOTROPIA Vol. 16 No. 1 (2009)
Publisher : SEAMEO BIOTROP

Metallothionein is an important protein for detoxifying heavy metal ions. This research was conducted to isolate and clone cDNA of gene encoding for metallothionein type 2 from Melastoma affine. Total RNA was isolated from young leaves. Total cDNA was synthesized from the total RNA by reverse transcription. The MaMt2 cDNA was successfully isolated by PCR technique. The MaMt2 cDNA was inserted into pGEM-T Easy and the recombinant plasmid was successfully introduced into Escherichia coli DH5Î±. DNA sequencing analysis showed that this cDNA is full length consisting of 246 pb encoding 81 amino acid residues. This cDNA is identical to mRNA of AtMt2 from Arabidopsis thaliana. It does not contain any restriction sites found in the cloning sites of pGEM-T easy. The deduced protein of MaMT2 contains 14 cysteine residues distributed in the Cys-Cys, Cys-X-Cys, and Cys-X-X-Cys motifs. Â Key words: cDNA, metallothionein, Melastoma affine, cloning, cysteine

Pelatihan Kewirausahaan Berbasis Pertanian di Universitas Darussalam Gontor Ponorogo Use Etica; Lutfy Ditya Cahyanti; Niken Trisnaningrum
Khadimul Ummah Vol 4, No 1 (2020): November 2020
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/ku.v4i1.5276

Di tengah permasalahan ekonomi yang semakin besar dan lapangan pekerjaan yang semakin sempit akibat pandemic Covid19, kewirausahaan dirasakan sebagai jalan yang paling efektif untuk membangkitkan kembali kehidupan perekonomian masyarakat. Dengan latar belakang tersebut, tim PPK Universitas Darussalam Gontor mengadakan workshop kewirausahaan dan diharapkan setelah pelatihan peserta pelatihan memperoleh keterampilan berwirausaha agar dapat mencapai efektivitas dalam melaksanakan tugas tertentu terkhusus dalam berwirausaha melalui pengembangan proses berfikir, sikap, pengetahuan, kecakapan, dan kemampuan. Workshop kewirausahaan ini diikuti oleh 20 tenant. Materi yang diberikan meliputi motivasi kewirausahaan, etika bisnis dalam Islam, perencanaan bisnis model kanvas, perencanaan keuangan, akuntansi, pemasaran melalui marketplace, pembuatan iklan, perancangan dan branding produk, penanganan dan keamanan produk pangan segar, serta pentingnya HaKI bagi startup.

HiT-LIDIA: A Framework for Rice Leaf Disease Classification using Ensemble and Hierarchical Transfer Learning Oddy Virgantara Putra; Niken Trisnaningrum; Niken Sylvia Puspitasari; Agung Toto Wibowo; Ema Rachmawaty
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol 13 No 3 (2022): Vol. 13, No. 3 December 2022
Publisher : Institute for Research and Community Services, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/LKJITI.2022.v13.i03.p06

Rice is one of the global most critical harvests, and a great many people eat it as a staple eating routine. Different rice plant diseases harm, spread, and drastically reduce crop yields. In extreme situations, they may result in no grain harvest at all, posing a severe threat to food security. In this paper, to amplify the recognition ability for rice leaf disease (RLD) classification, we proposed hierarchical transfer learning (HTL) methods incorporating ensemble models containing two-step. In the first step, an ensemble combining MobileNet and DenseNet was addressed to tackle the diseased leaf problem. Consequently, DenseNet and XceptionNet were fused to identify three RLDs. Here, we compare our models with state-of-the-art deep learning models such as ResNet, DenseNet, InceptionNet, Xception, MobileNet, and EfficientNet. Our framework at top-notch with 89 % and 91 % for accuracy. In future works, RLD segmentation is suggested to pinpoint the illness and quantify the afflicted region.

Segmentasi Semantik pada Citra Hama Leafblast Menggunakan Unet dan Optimasi Hyperband Moch. Nasheh Annafii; Oddy Virgantara Putra; Triana Harmini; Niken Trisnaningrum
Prosiding Seminar Sains Nasional dan Teknologi Vol 12, No 1 (2022): VOL 12, NO 1 (2022): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI
Publisher : Fakultas Teknik Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/psnst.v12i1.7230

Padi menjadi konsumsi primer di Indonesia. Penyakit padi menjadi salah satu faktor yang menyebabkan menurunnya jumlah produksi padi. Meningkatnya konsumsi beras menjadi masalah dengan menurunnya jumlah produksi padi pada tahun 2021. Luasnya lahan dan lambatnya proses identifikasi keparahan menjadikan kurang maksimalnya penanganan penyakit padi, yang berujung tidak maksimalnya hasil panen bahkan terancam gagal panen. Penelitian ini berupaya untuk mensegmen daun padi yang terkena hama leafblast dengan model yang dioptimalkan. Penelitian ini menggunakan metode algoritma Convolutional Neural Network dengan model UNet yang ditingkatkan dengan optimasi model Hyperband optimization. Dengan banyaknya penelitian mengenai UNet, UNet menjadi populer dan berkembang dengan pesat. Perkembangan yang pesat ini ditandai dengan banyaknya penelitian yang menggunakan UNet dan banyaknya modifikasi yang terus dikembangkan. Dataset yang digunakan pada penelitian ini merupakan murni hasil observasi peneliti dan telah divalidasi oleh ahli, dengan total 300 data asli dan data label. Dalam model yang digunakan, digambarkan terdapat bagian encoder dan decoder yang masing masing memiliki beberapa blok konvolusi. Hasil yang diperoleh dari model yang sudah dioptimasi terbukti 3 kali lebih ringan dengan perbandingan jumlah parameter yang cukup signifikan dan hasil valuasi akurasi mencapai 97.72%.

Klasifikasi Tingkat Keparahan Penyakit Leafblast Tanaman Padi Menggunakan MobileNetv2 Imam Fauzi Annur; Jumhurul Umami; Moch. Nasheh Annafii; Niken Trisnaningrum; Oddy Virgantara Putra
Fountain of Informatics Journal Vol. 8 No. 1 (2023): Mei
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/fij.v8i1.9419

AbstrakPadi merupakan tanaman pangan pokok di Indonesia, dan produksinya merupakan kunci ketahanan pangan negara. Keberhasilan panen merupakan faktor penting dalam pencegahan impor bahan pangan pokok. Tantangan terbesar dalam memanen tanaman adalah adanya virus, jamur, dan hama yang dapat merusak tanaman. Penelitian ini bertujuan untuk membuat sistem klasifikasi tingkat keparahan penyakit daun pada tanaman padi yang terkena penyakit blas daun dengan bantuan algoritma machine learning. MobileNetV2 adalah arsitektur Convolutional Neural Network (CNN) yang menggunakan Depthwise Separable Convolution untuk membangun model yang ringan dan dirancang untuk mengatasi proses yang memiliki resource yang berlebih. Dataset yang digunakan pada penelitian ini merupakan hasil murni observasi peneliti yang sudah divalidasi oleh ahli dengan total 300 data asli. Model MobileNetV2 ternyata sangat berhasil dalam mengklasifikasikan objek, dengan akurasi 78,33%. dengan hasil penelitian ini, petani dapat terbantu dalam mengenali tingkat keparahan penyakit leafblast pada tanaman padi sehingga pemberian bahan kimia berupa fungisida sesuai dengan dosis anjuran tingkat keparahan. Kata kunci: Klasifikasi, leafblast, padi, citra, model pre-trained, MobileNetV2. Abstract[Classification Of Rice Blast Disease Using MobileNetV2] Rice is a staple food crop in Indonesia, and its production is key to the country's food security. Successful harvesting is an important factor in preventing imports of staple foods. The biggest challenge in harvesting crops is the presence of viruses, fungi, and pests that can damage plants. This research aims to create a classification system for leaf disease severity in rice plants affected by leaf blast disease with the help of machine learning algorithms. MobileNetV2 is a Convolutional Neural Network (CNN) architecture that uses Depthwise Separable Convolution to build lightweight models and is designed to overcome processes that have excessive resources. The dataset used in this study is the result of pure researcher observations that have been validated by experts with a total of 300 original data. The MobileNetV2 model turned out to be very successful in classifying objects, with an accuracy of 78.33%. with the results of this study, farmers can be helped in recognizing the severity of leafblast disease in rice plants so that the provision of chemicals in the form of fungicides in accordance with the recommended dose of severity.Keywords: Classification, leafblast, rice, image, pre-trained model, MobileNetV2

Pelatihan Kewirausahaan Berbasis Pertanian di Universitas Darussalam Gontor Ponorogo Etica, Use; Cahyanti, Lutfy Ditya; Trisnaningrum, Niken
Khadimul Ummah Vol. 4 No. 1 (2020): November 2020
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/ku.v4i1.5276

Di tengah permasalahan ekonomi yang semakin besar dan lapangan pekerjaan yang semakin sempit akibat pandemic Covid19, kewirausahaan dirasakan sebagai jalan yang paling efektif untuk membangkitkan kembali kehidupan perekonomian masyarakat. Dengan latar belakang tersebut, tim PPK Universitas Darussalam Gontor mengadakan workshop kewirausahaan dan diharapkan setelah pelatihan peserta pelatihan memperoleh keterampilan berwirausaha agar dapat mencapai efektivitas dalam melaksanakan tugas tertentu terkhusus dalam berwirausaha melalui pengembangan proses berfikir, sikap, pengetahuan, kecakapan, dan kemampuan. Workshop kewirausahaan ini diikuti oleh 20 tenant. Materi yang diberikan meliputi motivasi kewirausahaan, etika bisnis dalam Islam, perencanaan bisnis model kanvas, perencanaan keuangan, akuntansi, pemasaran melalui marketplace, pembuatan iklan, perancangan dan branding produk, penanganan dan keamanan produk pangan segar, serta pentingnya HaKI bagi startup.

PEMBERDAYAAN SANTRI DALAM PEMBIBITAN DAN PENANAMAN TANAMAN DURIAN DI PONDOK PESANTREN DARUL QIYAM MAGELANG Trisnaningrum, Niken; Hamawi, Mahmudah; Parwi, Parwi; Muhammad, Muhammad; Etica, Use; Hanif, Muhammad; Isnatin, Umi
Jurnal Terapan Abdimas Vol 9, No 2 (2024)
Publisher : UNIVERSITAS PGRI MADIUN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25273/jta.v9i2.19275

Abstract. The Darul Qiyam Islamic Boarding School is in Magelang Regency and is a plateau surrounded by 5 (five) mountains, namely Mount Merapi, Merbabu, Andong, Telomoyo, Sumbing, and the Menoreh Mountains. This condition makes most of the Darul Qiyam Islamic boarding school area an area with fertile soil derived from volcanic ash. Based on regional conditions like this, the location of the Darul Qiyam hut is suitable for durian plants. On the one hand, the need for durian fruit for cottage purposes is increasing over time with the demand for bread made from durian. The current need for durian is supplied from markets around Magelang. Durian grows abundantly in the village around the Darul Qiyam cottage, while at the cottage location there are only 3 durian trees. This fact occurs due to the students' lack of knowledge in planting durian trees and durian tree nurseries. The solution offered in this activity is to increase knowledge about planting durian seeds and increase skills regarding the propagation of durian seeds. The method used is counseling and assistance in planting durian seeds as well as training in the propagation of durian seeds. The result of this activity was an increase in students' knowledge about durian planting and breeding. Abstrak. Pondok Pesantren Darul Qiyam berada di Kabupaten Magelang dan merupakan dataran tinggi yang dikelilingi oleh 5 (lima) gunung yaitu Gunung Merapi, Merbabu, Andong, Telomoyo, Sumbing, dan Pegunungan Menoreh. Kondisi ini menjadikan sebagian besar wilayah Pondok pesantren Darul Qiyam merupakan daerah yang tanah subur yang berasal abu vulkanis. Berdasarkan Keadaan wilayah seperti ini maka lokasi pondok Darul Qiyam cocok untuk tanaman durian. Di satu sisi kebutuhan buah durian untuk keperluan pondok semakin lama semakin meningkat dengan adanya perminataan roti yang berbahan baku durian. Kebutuhan durian sementara ini dipasok dari pasar disekitar magelang. Durian tumbuh subur di kampung sekitar pondok Darul Qiyam, sedangkan dilokasi pondok hanya terdapat 3 batang pohon durian. Kenyataan ini terjadi karena kurangnnya pengetahuan santri dalam menanam pohon durian dan pembibitan pohon durian. Solusi yang ditawarkan dalam kegiatan ini adanya peningkatan pengetahuan tentang penanaman bibit durian dan peningkatan ketrampilaan tentang perbanyakan bibit durian. Metode yang dilakuan penyuluhan dan pendampingan penanaman bibit durian serta pelatihan perbanyakan bibit durian. Hasil dari kegiatan ini yaitu terjadi peningkatan pengetahuan santri tentang penanaman dan pembibitan durian sebesar 75% diperoleh dari hasil pretest dan pos test.

Modification of The Synthesis of Silica from Litter Ori Bambusa (Bambusa blumeana) Leaves Using Sodium and Potassium With The Hydrothermal Sol-Gel Method As Agricultural Fertilizer Mahmudah Hamawi; Niken Trisnaningrum; Ilham Mufandi
Agroindustrial Technology Journal Vol. 7 No. 3 (2023): Agroindustrial Technology Journal
Publisher : Universitas Darussalam Gontor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21111/atj.v7i3.10666

Bamboo plants in Indonesia are familiar plants and have not been utilized optimally. Most people only use the stems for daily needs and a small part for industry, while the leaves are left as waste. Bamboo leaves have a fairly high silica content. Bamboo leaves that have fallen and are scattered on the ground (bamboo leaf litter) are a potential source of natural silica. Silica fertilizer in agriculture is still very necessary, especially in nanosized. Through silica extraction from bamboo leaf litter, it is hoped that it will be able to meet agricultural silica needs and reduce bamboo leaf waste. The aim of this research is to modify the synthesis of silica from ori bamboo leaf litter (Bambusa blumeana) by extracting NaOH and KOH using the hydrothermal sol-gel method to produce nano silica. Nano silica production uses the hydrothermal method because it does not require large costs, is more effective, and has a high level of purity. Synthesis of original bamboo leaf litter silica using the hydrothermal sol-gel method. Bamboo leaf litter ash was analyzed using the XRF test, and silica was analyzed using the SEM-EDX mapping test to determine its morphology and content. The research results showed that synthesis with sodium produced higher levels of bamboo leaf silica compared to potassium. The size of the silica particles obtained is still in the form of micrometers (47–52 µm). Bamboo plants in Indonesia are familiar plants and have not been utilized optimally. Most people only use the stems for daily needs and a small part for industry, while the leaves are left as waste. Bamboo leaves have a fairly high silica content. Bamboo leaves that have fallen and are scattered on the ground (bamboo leaf litter) are a potential source of natural silica. Silica fertilizer in agriculture is still very necessary, especially in nanosized. Through silica extraction from bamboo leaf litter, it is hoped that it will be able to meet agricultural silica needs and reduce bamboo leaf waste. The aim of this research is to modify the synthesis of silica from ori bamboo leaf litter (Bambusa blumeana) by extracting NaOH and KOH using the hydrothermal sol-gel method to produce nano silica. Nano silica production uses the hydrothermal method because it does not require large costs, is more effective, and has a high level of purity. Synthesis of original bamboo leaf litter silica using the hydrothermal sol-gel method. Bamboo leaf litter ash was analyzed using the XRF test, and silica was analyzed using the SEM-EDX mapping test to determine its morphology and content. The research results showed that synthesis with sodium produced higher levels of bamboo leaf silica compared to potassium. The size of the silica particles obtained is still in the form of micrometers (47–52 µm).

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