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Muhammad Ridha Syafii Damanik
Universitas Negeri Medan
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Journal : Tunas Geografi

 1 
Analisis Potensi Lahan Pertanian Padi Sawah Di Kabupaten Nias Utara Dengan Memanfaatkan Sistem Informasi Geografi Selamat Gea; Muhammad Ridha Syafii Damanik
Tunas Geografi Vol 7, No 1 (2018): JURNAL TUNAS GEOGRAFI
Publisher : Department of Geography Education, Faculty of Social Sciences, Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/tgeo.v7i1.11085

Abstract

Penelitian ini bertujuan untuk mengetahui (1) Karakteristik fisik wilayah kabupaten Nias Utara berdasarkan parameter IPL. (2) Potensi lahan pertanian padi sawah di Kabupaten Nias Utara. (3) Kelas IPL penggunaan lahan pertanian padi sawah di Kabupaten Nias Utara. Metode yang digunakan adalah metode pengharkatan (skoring) dan tumpang susun (overlay). Pengharkatan dilakukan terhadap parameter-parameter penyusun Indeks Potensi Lahan yang meliputi kelerengan, litologi, jenis tanah dan hidrologi sebagai faktor pendukung serta kerawanan bencana erosi sebagai faktor pembatas. Metode overlay adalah metode menggabungkan dua buah peta atau lebih yang memiliki koordinat yang sama untuk menghasilkan satuan pemetaan baru (peta potensi lahan).Hasil penelitian menunjukkan bahwa (1) Wilayah Kabupaten Nias Utara sebagian besar memiliki lereng berombak – bergelombang, litologi sediment klastik berbutir halus, tekstur tanah agak halus, potensi air tanah kurang berpotensi, kerawanan longsor berpotensi ringan. (2) Kabupaten Nias Utara memiliki potensi lahan pertanian padi sawah kelas sangat tinggi seluas 14.381,44 Ha dengan persentase 11,56%, kelas tinggi seluas 15.529,58 Ha dengan persentase 12,48%, kelas sedang seluas 40.770,89 Ha dengan persentase 32,77%, kelas rendah seluas 46.554,24 Ha dengan persentase 37,42%, kelas sangat rendah seluas 7.182,08 Ha dengan persentase 5,77%. (3) Kelas IPL penggunaan lahan pertanian padi sawah di Kabupaten Nias Utara terdiri dari kelas sangat tinggi seluas 376,42 Ha dengan persentase 9,37%, kelas tinggi 466,92 Ha dengan persentase 11,63%, kelas sedang seluas 1.633,98 Ha dengan persentase 40,69%, kelas rendah seluas 1.476,40 Ha dengan persentase 36,77%, kelas sangat rendah seluas 61,74 Ha dengan persentase 1,54%.
APLIKASI PENGELOLAAN LAHAN KELAPA SAWIT (APLKS) BERBASIS INFORMATION SYSTEM INTERACTIVE MAP DI KEBUN TINJOWAN Surya Ningsih; Dewi Mutiara; Rizqan Khalish; Muhammad Ridha Syafii Damanik
Tunas Geografi Vol 7, No 2 (2018): JURNAL TUNAS GEOGRAFI
Publisher : Department of Geography Education, Faculty of Social Sciences, Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/tgeo.v7i2.11086

Abstract

The need for an easy and fast information system is a demand that must be answered in the current management of oil palm plantations. Application Development of Palm Oil Land Management (APLKS) based on Information System Interactive Map is one way to answer these demands. This research was conducted at Palm Oil Plantation of Tinjowan, North Sumatera Province. The purpose of this research is to know the accuracy of mapping and application of Palm Land Management Application (APLKS) in Tinjowan Palm Oil Plantation. The method used in this research is descriptive qualitative. Data collection technics used are documentary studies, direct observation, and application development. The analysis result shows that the level of Overal Accuracy (overall accuracy) mapping is 94,64%. The results of application implementation measurement indicate that this application is very helpful for companies in palm oil land management especially in the ease and speed of information access location and condition of plantation.
ANALISIS POTENSI LONGSOR SUNGAI DI DAERAH ALIRAN SUNGAI (DAS) PADANG SUMATERA UTARA Muhammad Ridha Syafii Damanik; Ali Nurman; Muhammad Yuliansyah Aminy; Ilham Ritonga
Tunas Geografi Vol 8, No 2 (2019): JURNAL TUNAS GEOGRAFI
Publisher : Department of Geography Education, Faculty of Social Sciences, Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/tgeo.v8i2.16139

Abstract

AbstractThe occurrence of flash floods in 2017 that hit Tebing Tinggi City in North Sumatra Province caused 33,825 lives to be affected. That shows that the potential for flash floods disasters in the North Sumatra region, including in the Padang River Basin, is classified as very high. The purpose of this study is to determine the location of potential riverbank landslides that cause river flow obstructions (natural dams) in the Padang River Basin. The method used in this study is a qualitative method using geographic information systems. The data analysis technique used is the cone stacking technique of research variable maps. The variables used to analyze the potential of riverbank landslides are the appearance of existing landslides, topography (flow accumulation), and geology (faults). The results of this study indicate that there are 86 locations with potential landslides that can cause natural dams. The most potential location is the Padang sub-watershed with 48 sub-areas.Keywords: Disaster Mitigation, Spatial Modeling, Flash floods, Geographic Information Systems AbstrakKejadian banjir bandang tahun 2017 yang melanda Kota Tebing Tinggi  Provinsi Sumatera Utara menyebabkan 33.825 jiwa terdampak. Hal ini menunjukkan bahwa potensi bencana banjir bandang di wilayah Sumatera Utara termasuk di Daerah Aliran Sungai (DAS) Padang tergolong sangat tinggi. Adapun tujuan penelitian ini adalah untuk mengetahui lokasi yang berpotensi terjadi longsor tebing sungai yang mengakibatkan terhambatnya aliran sungai (bendungan alam) di DAS Padang. Metode yang digunakan dalam penelitian ini adalah metode kualitatif dengan menggunakan sistem informasi geografis. Teknik analisis data yang digunakan adalah teknik tumpeng susun peta variabel penelitian. Adapun variabel yang digunakan untuk menganalisis potensi longsor tebing sungai adalah kenampakan longsor eksisting, topografi (akumulasi aliran), dan geologi (patahan). Hasil penelitian ini menunjukkan bahwa terdapat 86 lokasi yang berpotensi longsor yang dapat menyebabkan bendungan alam. Lokasi paling banyak terdapat potensi adalah sub-DAS Padang dengan jumlah sub-area 48 lokasi.   Kata Kunci:   Mitigasi bencana, Permodelan Spasial, Banjir Bandang, Sistem Informasi Geografis
Improving Community Skills in Making Processed Fish Products in Paluh Kurau Village, Deli Serdang, North Sumatra Muhammad Ridha Syafii Damanik; OK Sofyan Hidayat; Meilinda Suriani Harefa; Darwin Parlaungan Lubis
Tunas Geografi Vol 10, No 2 (2021): JURNAL TUNAS GEOGRAFI
Publisher : Department of Geography Education, Faculty of Social Sciences, Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/tgeo.v10i2.28706

Abstract

The purpose of this community service is to find and increase the income generate of Medan State University which has been designated as a Public Service Agency in 2018. When a government institution turns into a Public Service Agency, it will be required to be independent in financial management including in terms of income management. This community service activity is a continuation of the previous year, where the Department of Geography Education, has pioneered the sale of online fresh fish which is a source of income generation. In 2021, the business unit will develop its products not only in fresh fish products but also in processed fish products with high economic value. In addition, this activity aims to help partner community groups to produce processed fish products to be marketed in the Medan State University Business Unit.The stages carried out in this activity are to collaborate with partners. Furthermore, conducting a series of training and mentoring for partner groups so that they can produce processed fish products that are in accordance with standards so that they are worthy of being marketed. This training and mentoring process was carried out in Paluh Kurau Village, District of Perak, Deli Serdang Regency.The output of this activity is the availability of processed fish products which can increase the income of partner groups and become an income generator for Medan State University.Keywords: Business Unit, Processed Fishery, Income Generating
Analysis Changes in Mangrove Forest Cover Using Multi-Sensor Image in North Luwu District South Sulawesi 2015-2020 Maulana Abdul Hakim; Darwin Parlaungan Lubis; Meilinda Suriani Harefa; Muhammad Ridha Syafii Damanik; Ayu Suciani
Tunas Geografi Vol 11, No 2 (2022): JURNAL TUNAS GEOGRAFI
Publisher : Department of Geography Education, Faculty of Social Sciences, Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/tgeo.v11i2.41349

Abstract

Mangrove forest is one of the essential components of natural ecosystems. Mangrove forests have various essential functions, such as holding land sediments, tsunamis, and ocean waves, storing large amounts of carbon, and providing various other benefits for coastal and land areas. However, the conversion of mangrove forests has reduced and degraded mangrove land. Therefore, monitoring and conserving land changes in mangrove forests must be carried out to determine the effects on land ecosystems and coastal areas. Remote sensing has the spatial ability to analyze changes in mangrove ecosystems in coastal regions temporally because it has the advantage of using satellite imagery data. This study compares the classification method using multiple image sensors to analyze land cover changes in mangrove forests in North Luwu Regency, South Sulawesi, in 2015-2020. The technique used in this research is the classification of Object-Based Image Analysis (OBIA) and the variety of Maximum Likelihood. The results of Sentinel-1 image analysis using Maximum Likelihood provide information on changes in mangrove land cover during 2015-2020 with an area of 449.17 (Ha), while the results of Landsat 8 analysis using (OBIA) provide information on changes in mangrove land cover 596 (Ha).Keywords: Optics, Radar, OBIA, Maximum Likelihood, Mangrove
Co-Authors Ali Nurman Ayu Suciani Darwin Parlaungan Lubis Dewi Mutiara Eko Prasetya Harefa, Meilinda Suriani Hidayat, OK Sofyan Ilham Ritonga Maulana Abdul Hakim Muhammad Yuliansyah Aminy Rizqan Khalish Selamat Gea Surya Ningsih Teguh Febri Sudarma