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"Sebagai institusi publik, salah peran Badan Pertanahan adalah melakukan pendaftaran tanah guna memelihara kepastian hukum hak-hak atas tanah. Banyaknya keluhan masyarakat akan lemahnya kualitas dan kuantitas hasil mendorong perlunya reformasi pelayanan khususnya dalam sertifikat tanah. Masyarakat yang semakin maju senantiasa menuntut kualitas mutu layanan publik yang mereka peroleh sejalan dengan dinamika social ekonomi yang semakin berkembang. Kantor Pertanahan Kota Bekasi sebagai kepanjangan tangan Badan Pertanahan Nasional dalam layanan (provider) masyarakat di bidang pertanahan berusaha memberi layanan prima menuju prinsip prinsip Good Governance.Dalam usaha peningkatan pelayanan, Kantor Pertanahan Kota Bekasi ingin memaksimalkan sarana yang ada baik sumber daya manusia, data dan ditunjang dengan penguasaan teknologi, salah satunya adalah kegiatan pemetaan bidang tanah dengan teknologi peta digital.Untuk mengukur keberhasilan pelayanan suatu metode yang relatif baru perlu adanya penelitian. Penelitian dilakukan dengan menggunakan hipotesis asosiatif antara variabel independen "metode pemetaan" terhadap variabel dependen `pelayanan pemetaan". Diharapkan dari penelitian dapat mengidentifikasi respon publik terhadap peningkatan pelayanan apabila dilakukan pemetaan bidang tanah memakai teknofogi digital.Penelitian ini bersifat deskriptif analitis berdasarkan pengolahan hasil survey menggunakan kuisioner. Proses perhitungan menggunakan program SPSS versi 10.5. bengan metode analisis deskriptif dapat dilihat gambaran yang menyeluruh dari hasil survey.Berdasarkan temuan yang diperoleh dalam penelitian ini perlu ditindaklanjuti baik pada tataran akademis maupun praktis. Tindak lanjut kerangka praktis dapat diwujudkan dalam bentuk masukan bagi Kantor Pertanahan, disamping itu tindak lanjut tataran akademis dapat dilakukan berupa pengkajian penelitian lanjutan yang lebih mendalam.

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As one of public institution, the role of Land Affairs Office in providing services in assurance of land owned by people is very big. The advance of the people needs required improvement in quality services. Bekasi's Land Affairs Office as branches of National Land Affairs Office which provide service in land affairs has tried to give its best services in applying the good governance principles.

In order to improve its services, Bekasi's Land Affairs Office has to exploit its resources backed by advance technology, one of them is mapping activity. To assess implementation of digital mapping method needs a research. This research intended to identify public responses to services received after using digital mapping.

To assess the succeed of public services as regulated in MENPAN Decree no. 51 as follows: simplicity, clear, security and convenience, transparency, efficiency, economically, justice, punctuality.

This research is based on analytical descriptive with process on survey result and comprehensive illustration from every variable respondent questioner. I hope it could illustrate field officer responses and the need of customers.

Based on the result acquired, it needs follow up in academic and practical field. Follow up in practical field could be implemented as input to and Affairs Office while follow up in academic field could be in further researches."

"The accuracy of Landsat 5 multispectral scanner (MSS) data for mapping mangrove in Java is investigated and compared with SPOT 1 very-High-Resolution Scanner (XS) data. Supervised classification on mangrove is performed for SPOT XS data sets collected on August 1988 and Landsat MSS on August 1985. A detailed accuracy assesment is conducted based on ground data collected in 1988 and 1989. These results produce overall mangrove area classification accuracies of 74,2 and 82,8 percent for MSS and XS with 7 and 10 classes, respectively. While the accuracies for predominant categories are similar for both sensors, mangrove discrimination for less commonly occurring and/or spatially heterogeneous categories is improved with the XS data set. The MSS, however, performs similar, or better than the XS in classifying large homogeneous areas. The use of MSS data which is expensive than high resolution data appears promising for mangrove monitoring."

"Criminal Investigations & Forensic Science"

"Awalnya, pemetaan lahan gambut dilakukan dengan pengamatan langsung sifat-sifat tanah pada jarak tertentu. Namun saat ini sudah banyak dikembangkan pemetaan jarak jauh menggunakan citra satelit dengan data pendukung lainnya. Selain keunggulannya karena mudah diakses dan memiliki jangkauan yang luas, citra satelit juga memungkinkan interpretasi karakteristik menggunakan metode artificial intelligence (AI). Penelitian yang akan dilakukan adalah melakukan pengembangan terhadap algoritma pengkarakteristik citra satelit sehingga didapatkan hasil yang lebih optimal. Arsitektur Hybrid Residual U-Netdigunakan sebagai algoritma untuk mengklasifikasikan kedalaman lahan gambut. Data yang digunakan berupa citra satelit MODIS yang diakusisi dalam rentang waktu 5 tahun pada tahun 2015 sampai 2019 dan data kedalaman lahan gambut dari Balai Besar Sumberdaya Lahan Pertanian (BBSDLP) dengan 7 kelas kedalaman gambut pada daerah Pulang Pisau Kalimantan Tengah. Citra satelit MODIS diolah menjadi sebuah indeks vegetasi. Citra indeks vegetasi yang digunakan pada penelitian ini sejumlah 9 citra indeks vegetasi. Citra indeks vegetasi dan data kedalaman gambut kemudian dilakukan ekstraksi fitur untuk pembuatan dataset model machine learning menggunakan metode grid dan centeroids. Untuk pembuatan dataset model Hybrid Residual U-Net dilakukan pemotongan region of interest (ROI) pada citra indeks vegetasi dan kedalaman gambut. Pada tahap pelatihan model Hybrid Residual U-Net memiliki nilai akurasi sebesar 99,99% dan pada proses pengujian memiliki nilai akurasi sebesar 96,46%.

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Initially, peatland mapping was carried out by direct observation of soil properties at a certain distance. However, many remote sensing for digital mapping has been developed using satellite imagery with other supporting data. In addition to the advantages of being easily accessible and having a wide range, satellite imagery also allows the interpretation of characteristics using artificial intelligence (AI). The research that will be carried out is to develop an algorithm for characterizing satellite imagery so that more optimal results are obtained. Hybrid Residual U-Net was used as an algorithm to classify the depth of peatlands. The data used are MODIS satellite imagery which was acquired over a period of 5 years from 2015 to 2019 and peatland depth data from the Center for Agricultural Land Resources (BBSDLP) with 7 peat depth classes in Pulang Pisau, Central Borneo. MODIS satellite imagery is processed into a vegetation index. The vegetation index images and peat depth data were then performed for feature extraction to create a machine learning model dataset using the grid and centroids methods. To generate the CNN model’s dataset, the region of interest (ROI) was cut on the vegetation index and peat depth images. The model will process the dataset so that the accuracy value is obtained then a comparison is done between the accuracy values ​​so that the best model is obtained. At the training stage, the Hybrid Residual U-Net model has an accuracy value of 99.99% and in the testing process, it has an accuracy value of 96,46%."

"This edition provides students and practitioners with a solid foundation for understanding the conceptual nature and practice of crime analysis to assist police in preventing and reducing crime and disorder. Author Rachel Boba Santos offers an in-depth description of this emerging field, as well as guidelines and techniques for conducting crime analysis supported by evidence-based research, real world application, and recent innovations in the field."

"Summary:Science maps that can help us understand and navigate the immense amount of results generated by today's science and technology."