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"The mapping of coastal vulnerability using the Coastal Vulnerability Index (CVI) and the Geographic Information System (GIS) at Doreri Bay, Manokwari Regency, West Papua Province was carried out from September 2013 to March 2014. The aims of this study are to analyze and map the coastal vulnerability of Doreri Bay. The study was conducted using a combination of the CVI and GIS methods to assess the geological and physical parameters of the coastal region. The geological parameters consisted of geomorphology, coastline changes (accretion/erosion), the coastline slope, and physical processes. The physical parameters consisted of the relative changes in the sea surface height, the average wave height, and the average tidal height. The results of this research show that the CVI values were within the range of 6.7–43.3, and there were five class categories of coastal vulnerability: (1) very low vulnerability with an area of 6,635.4 Ha or 47.8%, (2) low vulnerability with an area of 2,654.1 Ha or 19.1%, (3) medium vulnerability with an area of 1,692.8 Ha or 12.2%, (4) high vulnerability with an area of 992.7 Ha or 7.2%, and (5) very high vulnerability with an area of 1,904.2 Ha or 13.7%."

"The analytical view exploers in this paper represent the perspective of subsistent farmers in NTT Province when integrated with marketeconomy. It tries to explain why the subsistent community are so vulnerable to become migrant workers and uprooted from their land; itis also attempt to investigate the relation between economic policy on free labour market with death and torture received by migrant workers. While the victims, especially women and children, are publicized and attracted attention from mass media and also social media. However,the publication over the suffering of migrant workers from the margin of Indonesia such as NTT Province, does not get direct impact over the policy makers with the willingness to renew regulation to protect migrant workers. This paper focuses on investigating why the poor migrant women and children are being neglected by policy makers under the neoliberal order. It also tries to explain why the subsistent members are easily uprooted from their land and become migrantworkers during modernization. It also tries to answer why the are often in position as the losers or victims during globalization. Thehope that the State is able to protect the vulnerables is fading away under the domination of pro market policy. Children and women as thesilent victims are the evidence of absolute surrender of the subsistent community. State incapacity to protect the most vulnerable citizens is the evidence of the coming of new wave of neocolonialism. This is also a proof the modernization is also part of conquering when halfhearted modernization has placed them at the bottom of the pyramid of modernity which is vulnerable to be exploited without the ability tospeak and to be listened."

"Penelitian ini membahas strategi alternatif berupa pentargetan program-program bantuan pendidikan yang telah dijalankan oleh pemerintah diantaranya Bantuan Operasional Sekolah (BOS) dan Bantuan Siswa Miskin (BKM). Dilakukan analisis klaster untuk memetakan 497 kabupaten/kota di Indonesia berdasarkan ciri-ciri atau karakteristik pendidikan dasarnya. Pembentukan klaster menggunakan k-means clustering pada 8 variabel yaitu APS SD, APS SMP, Angka Melek Huruf, Lama Sekolah rata-rata, Jumlah Sarana SD, Jumlah Sarana SMP, Jumlah Guru SD dan Jumlah Guru SMP. Hasilnya terbentuk 5 klaster dengan kesamaan karakteristik, yang kemudian disusun strategi bantuan pendidikan yang sesuai untuk masing-masing klaster. Perhitungan Data Indeks Pendidikan juga dilakukan sebagai validasi hasil klaster. Hasil Indeks Pendidikan sejalan dengan asumsi hasil klaster yaitu mengarah pada klaster-4 sebagai klaster terbaik, dilanjutkan oleh klaster-3, klaster-1, klaster-2 dan terakhir klaster-5.

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This study focus on formulating alternative strategy to optimize the targeting of educational aid such as School Operational Aid (BOS) and Poor Student Aid (BSM). Cluster analysis is conducted to map all regencies in Indonesia based on its basic education characteristics. Clustering is done by k-means clustering using 8 variables, which is elementary and junior high school enrollment rate, illiteracy, average years of schooling, number of building facility and number of teachers. The results are formed 5 clusters with the same characteristics, which is then used to set a strategy and priority for educational aid in each cluster. Education Indexing is also done to validate the cluster results. The Education Index results are consistent with cluster results, with cluster-4 as the best, then followed by cluster-3, cluster-1, cluster-2 and cluster-5."

"Peningkatan kebutuhan lahan permukiman mendorong aktivitas manusia yang semakin kompleks, sehingga menimbulkan bencana, salah satunya kebakaran permukiman. Pada tahun 2018-2021, kebakaran permukiman mengalami ekspansi sebesar 14% di Kota Jakarta Timur. Kejadian ini mengakibatkan kerusakan infastrukur dan kerugian ekonomi yang cukup besar serta menyebabkan hilangnya nyawa seseorang. Studi kerentanan bencana menjadi salah satu opsi yang dapat dilakukan dalam upaya mitigasi. Faktor fisik, sosial, dan ekonomi dinilai sebagai faktor penilaian kerentanan bencana yang mengarahkan pada peningkatan dampak bahaya. Penelitian ini bertujuan untuk mengidentifikasi faktor yang paling berpengaruh dan menganalisis karakteristik wilayah rentan bencana kebakaran permukiman di Kota Jakarta Timur. Metode yang digunakan dalam penelitian ini adalah Analytical Hierarchy Process (AHP) melalui analisis Geographic Information System- based Multicriteria Decision Analysis (GIS-MCDA). Hasil penelitian menunjukan bahwa faktor kerentanan fisik memiliki pengaruh yang lebih tinggi dibandingkan faktor sosial dan ekonomi. Berdasarkan analisis tersebut, wilayah rentan kebakaran permukiman tingkat rendah terdistribusi secara mengelompok pada wilayah yang memiliki lebar jalan 6 m, penggunaan tanah berupa industri, kepadatan penduduk rendah, dan dominasi usia produktif serta dominasi penduduk berjenis kelamin laki-laki. Kemudian pada tingkat sedang memiliki pola menyebar pada karakteristik wilayah dengan kepadatan penduduk sedang dengan material bangunan permukiman semi permanen serta dapat menjangkau hidran kota kurang dari 400 m. Sedangkan, pada tingkat tinggi terdistribusi secara mengelompok pada wilayah dengan karakteristik dekat dengan sumber penyalaan api besar, kepadatan bangunan dan penduduk yang tinggi, serta penggunaan lahan permukiman. Analisis ini memiliki kesesuaian dengan nilai 67% dan termasuk model prediksi cukup baik dari hasil perbandingan kondisi aktual riwayat kejadian kebakaran permukiman tahun 2018-2021. Dengan demikian, penelitian ini diharapkan dapat menjadi pertimbangan kajian lebih lanjut yang berguna dalam menentukan wilayah prioritas untuk penyusunan rencana penanggulangan bencana kebakaran permukiman seperti meningkatkan kapasitas masyarakat.

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Complex human activities are encouraged by the growing demand for residential that causing disaster, such as residential fires. Residential fires increased by 14% in East Jakarta City in 2018-2021. This incident resulted in infastructural damage, significant economic loss, and person’s life. One of the choices for mitigation actions is to conduct disaster vulnerability evaluations. Disaster vulnerability assessment elements that increase hazard consequences are evaluated as being physical, social, and economic factors. This study aims to identify the most important factors and analyze the characteristics of vulnerability of residential fires in East Jakarta City. The Analytical Hierarchy Process (AHP) through GIS-MCDA analysis was the method employed in this study. The results showed that physical vulnerability factors had a greater impact than social and economic. Based on this analysis, low-level residential vulnerability areas are clustered with a road width of 6 m, industrial land use, low population density, and dominance of productive age and male population. Then, medium level has dispersed pattern in the characteristics of areas with medium population density also semi-permanent residential building materials and a 400 m or less distance to fire hydrant. Meanwhile, high level are distributed in areas with characteristics close to major fire source, high density of buldings and residents. According to the findings of the comparison on historical intensity of residential fires in 2018-2021, the analysis is valid with a value of 67% and included a fairly to good model prediction. As a result, this research can be considered for additional studies to help identify priority areas for residential fires disaster management plan, such as increasing community capacity."

"Value Stream Mapping harus dilakukan untuk menentukan kondisi arus proses perusahaan saat ini. Penelitian ini dilakukan di PT. X yang telah menjadi produsen pelumas sejak 1996. Metode yang digunakan dalam penelitian ini adalah Value Stream Mapping (VSM) sebagai kerangka kerja untuk aliran proses, Value-Added dan Non- Value-Added (VA-NVA) untuk memahami dan menentukan setiap kegiatan dalam aliran proses. Identifikasi limbah berdasarkan pada Seven Waste (7 Waste) kategori, dan Manufacturing Cycle Efficiency (MCE) untuk membandingkan peningkatan yang dilakukan dari Current VSM dan Proposed VSM. Tujuan dari penelitian ini adalah untuk mengetahui efisiensi siklus manufaktur perusahaan. Ada 4 proses utama yang akan diukur dalam VSM; Delivery, Re-refinery, Blending, dan Filling. Perbaikan dapat dilakukan dengan mengikuti aturan lean thinking untuk mengurangi pemborosan yang terjadi. VSM saat ini menunjukkan, MCE dari PT. X hanya mencapai 0,62% sementara aktivitas Non-Value-Added mereka melebihi 1200 jam. Menggunakan 7 Waste, pemisahan limbah dan kemungkinan strategi peningkatan dibuat, yaitu; Pull System, arus informasi yang disederhanakan, dan pemeriksaan bahan secara teratur. Dengan menggunakan strategi, VSM yang diusulkan dibuat dan mampu mengurangi waktu Non-Value-Added menjadi 654 jam dan menaikkan MCE menjadi 1.17%.

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Value stream mapping should be done to determine the condition of the current company process flow. This research conducted at PT. X which has been a lubricant industry producer since 1996. The methods use in this research are Value Stream Mapping (VSM) as a framework for the process flow, Value-Added and Non-Value- Added (VA-NVA) to understand and specified each activity within the flow of process. Identifying waste based on the seven waste (7 Waste) category, and Manufacturing Cycle Efficiency (MCE) to compare the improvement being made from the current and future VSM. The purpose of this research is to determine the company manufacturing cycle efficiency. There are 4 main process that are going to measure in the VSM; Delivery, Re- refinery, Blending, and Filling. Improvement can be made by following the rules of lean thinking in order to reduce the waste that occurs. Current VSM shows, MCE of PT. X is 0.62% while their non-value-added activities exceed 1200 hours. Using 7 Waste, separation of waste and possible improvement strategy was made, namely; pull system, simplified information flow, and regular material check. Using the strategy, proposed VSM was build and able to decrease non-value-added time into 654 hours and increase MCE into 1.17%."

"Stereoscopic SPOT P and monoscopic SPOT XS data were tested for assessing the SPOT capability for geologic and soil mappings in Indonesia, down to 1:50,000 and 100,000 scales. Methodological approaches for spatial and spectral analysis of SPOT images are briefly discussed and illustrated. The operational SPOT capability was tested with the geologic soil mappings of Wonosari from monoscopic SPOT XS data. Generally speaking, results are compared well with mappings from 1:50,000 infrared aerial stereo-pairs. The paper concludes that SPOT has the potential of a major data source for operational small/medium scale geologic and soil surveys in Indonesia.

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"Terdapat banyak hasil penyelidikan tanah lapangan di DKI Jakarta yang tidak terpakai lagi setelah proyek pembangunan selesai. Sebagai bentuk pemanfaatan data hasil penyelidikan tanah di lapangan, pemetaan nilai N SPT serta qc dan FR CPT dilakukan untuk wilayah DKI Jakarta menggunakan data dari Laboratorium Mekanika Tanah, Universitas Indonesia. Pemetaan dilakukan untuk membuat prediksi hasil pengujian SPT maupun CPT sebagai data pembanding untuk penyelidikan tanah selanjutnya. Analisis geostatistik berupa kriging dilakukan untuk proses pemetaan. Sebelum dilakukan proses pemetaan, data hasil SPT dan CPT dikelompokkan berdasarkan kelompok kedalaman. Dengan bantuan aplikasi ArcGIS, hasil pemetaan prediksi nilai N SPT menunjukkan sebaran nilai yang membentuk kontur dari wilayah selatan menuju utara dengan nilai yang semakin meningkat ke arah selatan. Sedangkan pada peta prediksi nilai qc dan FR CPT ditemukan sebaran nilai yang cenderung homogen di setiap kedalaman yang ditinjau. Hasil prediksi nilai qc dan FR CPT juga digunakan untuk memetakan jenis tanah berdasarkan grafik Soil Behavior Type Robertson. Peta prediksi jenis tanah menunjukkan pada kedalaman 0-10 m akan ditemukan jenis tanah lempung (clay) dan campuran lanau-lempung (silt mixtures). Sedangkan pada kedalaman 10-20 m diprediksi akan ditemukan jenis tanah campuran pasir-lanau (sand mixtures).

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There are many results of field investigations in DKI Jakarta that are not used anymore after the construction project is completed. As a form of utilizing data from soil investigations in the field, mapping of N SPT values as well as qc and FR CPT was conducted for the DKI Jakarta area using data from the Soil Mechanics Laboratory, University of Indonesia. Mapping is done to offer predictions of SPT and CPT test results as comparative data for further soil investigations. Geostatistical analysis in the form of kriging is carried out for the mapping process. Before the mapping process is carried out, the SPT and CPT result data are grouped by depth groups. With the help of the ArcGIS application, the results of mapping the predicted N SPT values shows the distribution of values that form the contours from the south to the north with increasing values to the south. Whereas on the prediction map, the values of qc and FR CPT were found to be uniformly distributed at each depth observed. In addition, the results of prediction of qc and FR CPT are used to map soil types based on Robertson's Soil Behavior Type Graph. A map of soil type predictions shows that at depths of 0-10 m, clay types and silt mixtures will be found. While at a depth of 10-20 m, it is predicted that sand mixtures will be found."

"Value stream mapping sebagai metode implementasi konsep lean bertujuan untuk memvisualisasikan informasi dan aliran material pada suatu proses. Dalam beberapa tahun terakhir, sektor angkutan udara mengalami peningkatan dalam jumlah permintaan volume kargo dikarenakan peningkatan kebutuhan masyarakat yang beralih ke pembelanjaan secara online seiring dengan masa pandemi yang disertakan kelebihan strategis angkutan udara. Oleh karena itu, industri logistik dituntut untuk terus beradaptasi terhadap perubahan dalam pasar untuk memenuhi permintaan yang terus meningkat. Terminal Kargo Outgoing Domestik di Bandara Internasional Juanda PT Angkasa Pura Logistik seringkali tidak dapat mencapai target pengiriman angkutan udara yang telah ditetapkan. Identifikasi awal menunjukkan faktor penyebab keterlambatan yaitu terdapat beberapa barang yang tertinggal dalam proses, dan terdapat proses yang berulang. Dalam penelitian ini, value stream mapping dapat membantu untuk menggambarkan proses secara menyeluruh dan mengidentifikasi pemborosan pada proses Outgoing di Terminal Kargo PT Angkasa Pura Logistik. Hasil penelitian ini menunjukkan bahwa lead time proses pergudangan berkurang 25%, processing time berkurang 28%, dan value added ratio proses pergudangan meningkat dari 48.63% menjadi 69.4%. Rencana perbaikan yang diusulkan dalam penelitian ini adalah perancangan konsep lean 5S, penerapan planned maintenance alat bantu Terminal Kargo, dan melakukan digitalisasi untuk perpindahan data.

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Value stream mapping, as a method of implementing lean concepts, aims to visualize the flow of materials and information within a process. In recent years, the volume of air cargo transportation has increased due to the growing demand as people shift to online shopping during the pandemic, coupled with the strategic advantages of air transportation. Therefore, the logistics industry is required to continuously adapt to market changes to meet the ongoing increase in demand. The Outgoing Domestic Cargo Terminal at Juanda International Airport, operated by PT Angkasa Pura Logistics, often fails to achieve the set targets for air transportation deliveries. Initial identification reveals that some items are left behind in the process, and there exists repetitive processes causing delays. In this study, value stream mapping is used to comprehensively depict the overall process and identify waste in the Outgoing process at PT Angkasa Pura Logistics’ Cargo Terminal. The research results indicate a 25% reduction in warehouse lead time, a 28% reduction in processing time, and an increase in the value-added ratio of the warehousing process from 48.63% to 69.4%. Proposed improvement plans in this research include implementing lean 5S concepts, the implementation of planned maintenance for Cargo Terminal equipment, and the digitization of data transfer processes."