Oyster mushroom is one of the horticultural commodities in Indonesia. This community empowerment program through oyster mushroom cultivation is designed as an effort to provide a sense of equality, partnership, and togetherness for the improvement of the community's economy. Islamic and Social Education Foundation "Ar-Rohmah" with its abundant natural and human resource potential, can be a part of the process of social change. Student empowerment at this foundation manages students to do something beneficial for the community, including through training programs and mentoring in oyster mushroom (Pleurotus spp) cultivation. Accompanied by the Institute for Research and Community Service (LP2M) Team at the University of Jember, this activity was carried out to the students of the "Ar-Rohmah" Islamic and Social Education Foundation in Suren village, Ledokombo District, Jember through the presentation of theory and field practice on cultivation. mushrooms. This community service activity will form a small industry that is able to provide income for students of the "Ar-Rohmah" Islamic and Social Education Foundation in Suren Village, Ledokombo District, Jember. During the execution of program, students were showing high antusiams toward prospect and cultivation technology of oyster mushroom by giving contributions, suggestions and creative ideas.

Sentinel-2 merupakan satelit eropa yang memiliki 13 band spektral. Citra sentinel-2 dapat digunakan dalam beragam bidang salah satunya bidang pertanian. Pada bidang pertanian citra sentinel-2 dapat dimanfaaatkan untuk memetakan luas sawah di Kabupaten Jember. Penelitian ini bertujuan untuk mengolah data citra Sentinel-2 menjadi peta luasan sawah Kabupaten Jember dengan metode MLC, dan membandingkan luasan pada musim kemarau dan hujan. Tahapan penelitian ini adalah (1) unduh data satellite Sentinel-2 pada bulan Juni dan Oktober 2019 dan survei lapang untuk sebagai Ground Control Point (GCP), digunakan sebagai training area; (2) pra pengolahan data (atmospheric correction, composite, mosaic, dan clipping); (3) pengolahan data (pembuatan training area, klasifikasi metode MLC menggunakan aplikasi Multispec; (4) Uji akurasi; (5) Analisa hasil. Klasifikasi yang digunakan pada penelitian ini adalah: (1) hutan; (2) badan air; (3) pemukiman; (4) tegalan; (5) lahan kering/lahan kosong; (6) sawah, Pada hasil klasifikasi terdapat perbedaan luas sawah pada bulan Juni dan Oktober sebesar 134,332 km2. Hasil dari confussion matrix menunjukkan bahwa klasifikasi terdapat banyak kesalahan pada kedua klasifikasi yakni pada kelas sawah dengan hutan dan kelas tegalan dengan lahan kering. Nilai akurasi hasil klasifikasi bulan Juni untuk uji Overall : 93,3% dan Kappa accuracy : 90,1%. Untuk hasil klasifikasi bulan Oktober untuk uji Overall : 94,27% dan Kappa accuracy : 90,55%. Terdapat perbedaan luas sawah pada daerah irigasi (DI) Salmon2 antara hasil klasifikasi dengan digitasi lapang. Hal ini menandakan bahwa klasifikasi citra sentinel-2 dengan metode maximum likelihood tidak dapat menginterpretasikan luas sawah dengan baik.

This paper presents the use of satellite data (i.e., Landsat-5 & Landsat-8) to interpret the change of land cover from 1997 to 2020. The study area covers the administrative boundary of Lumajang Regency. The land-cover map of the year 1997 derived from Landsat-5. The Land-cover map of the year 2020 interpreted from Landsat-8. This study uses two methods of image classifications (i.e., unsupervised and supervised). The procedure includes image enhancement, registration, and classification. Then, classification results evaluated by confusion-matrix (overall and kappa accuracy). The supervised classification produces 7 classes of Land cover (i.e., forest, pavement/urban area), paddy field, plantation, rural area, water body and sand mining area. Unsupervised classification produced four 5 class i.e., forest, built-area, paddy field, rural area, and plantation. Supervised classification done the overall and kappa accuracy = 86% and  82%, while unsupervised classification = 73% and 64% for 1997 imagery. Furthermore, for 2020 image, the Supervised classification reaches the overall and kappa accuracy = 93% and  90%, while unsupervised classification done 81% and 72%. The supervised classification method gives a better result than un-supervised. Comparison of 1997 to 2020, it also shows the increase in pavement or build-area, followed by paddy field, rural area, and sand-mining. The change also appears as the decrease in forest and plantation areas.Keywords:   Landsat-5, Landsat-8, Unsupervised, Supervised, Lumajang

Nowadays, vegetation classification can be used to find out the latest information about the characteristics and distribution of vegetation in an area. However, a conservative process to differentiate vegetation was ineffective. Some of those limitations are poor accessibility that does work less safety, time-consuming, and needs a lot of human resources. On the other hand, remote sensing offers solutions that cannot be done by the simple method, such as how to take the data, time-consuming are less, and human resource needs are less as well. The purpose of this study was to classify, measured the area of each vegetation, and compared the effectiveness of the unsupervised used K-Means algorithm and supervised used Object Base Image Analysis algorithm methods vegetation classification. For accuracy calculation with confusion matrix, the classification results of the two methods were compared with the manual digitization method. Data was taken using drones in the area of the Curah Manis Sempolan Nature Reserve 1. Classification of vegetation consists of 5 vegetation types, which was apak, bush, pine, bendo, and dadap. The total area of the study area was 1.633 ha, and area vegetation of each classification was apak 0.224 ha; bush 0.748 ha; pine 0.394 ha; bendo 0.222 ha; and dadap 0.045 ha. The results of the calculation of accuracy showed that the unsupervised method had a value for overall accuracy of 80% and kappa accuracy of 73.58%. Then, in the supervised for overall accuracy is 68% and kappa accuracy of 58.72%. Keywords: classification, drone, remote sensing, satellite

ABSTRAKLidah buaya atau aloe vera adalah tumbuhan yang mudah dan cepat tumbuh di daerah tropis dengan lahan berpasir dan memiliki sedikit air. Lidah buaya bermanfaat untuk digunakan sebagai bahan baku industri farmasi, kosmetika, bahan baku makanan dan minuman kesehatan, obat-obatan yang tidak mengandung bahan pengawet kimia. Lidah buaya dapat ditanam baik secara langsung di tanah maupun di pot sehingga lahan-lahan pekarangan yang kosong pun dapat dimanfaatkan untuk budidaya lidah buaya.  Permasalahan yang dihadapi masyarakat sasaran adalah kurangnya keterlibatan anak-anak didalam melakukan kegiatan bertanam tanaman budidaya. Selain itu  lemahnya jiwa kreativitas anak-anak karena kurang dilakukan kegiatan yang bersifat aktif dan partisipatif. Program ini dilakukan dengan memperkenalkan cara bertanam lidah buaya didalam pot bagi anak-anak di kecamatan Patrang, Jember. Adapun tujuan pelaksanaan pengabdian ini adalah untuk: (1) mengasah daya kreativitas anak-anak, (2) melatih bertanam tanaman lidah buaya dan (3) membina anak-anak untuk menyukai kegiatan bercocok-tanam. Partisipasi aktif dari peserta menunjukkan semangat dan antusiasme peserta didalam bertanam lidah buaya. Adanya program ini diharapkan dapat memberikan pengetahuan dan keterampilan yang lebih luas sehingga anak-anak memiliki rasa percaya diri yang lebih tinggi. Kata kunci: anak-anak; berkebun; kreativitas; lidah buaya. ABSTRACTAloe vera is a plant that is easy and fast to grow in tropical areas with sandy soil and little water. Aloe vera is useful as a raw material for the pharmaceutical, cosmetic, health food and beverage industries, medicines that do not contain chemical preservatives. Aloe can be planted either directly in the ground or in pots so that the empty yard can be used for aloe vera cultivation. The problem faced by the target community is the lack of involvement of children in carrying out cultivation activities. In addition, the creative spirit of children is weak because they are less active and participative. This program is carried out by introducing how to grow aloe vera in pots for children in Patrang District, Jember. This service aims to: (1) train children's creativity, (2) train to cultivate aloe vera plants, and (3) foster children's farming activities. The active participation of the participants showed the enthusiasm of the participants in planting aloe vera. This program is expected to provide broader knowledge and skills so that children have higher self-confidence. Keywords: aloe vera; creativity; children; gardening.