Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

2.782

P-Index

This Author published in this journals

All Journal Jurnal Teknologi Perikanan dan Kelautan Marine Fisheries: Jurnal Teknologi dan Manajemen Perikanan Laut Jurnal Ilmu dan Teknologi Kelautan Tropis Journal of Marine and Aquatic Sciences ILMU KELAUTAN: Indonesian Journal of Marine Sciences Forum Geografi Jurnal Kelautan Tropis Journal of Applied Geospatial Information JURNAL ENGGANO Omni-Akuatika JURNAL ILMIAH GEOMATIKA MAJALAH ILMIAH GLOBE Sumatra Journal of Disaster, Geography and Geography Education Aquasains : Jurnal Ilmu Perikanan dan Sumberdaya Perairan Jurnal Penelitian Perikanan Indonesia Jurnal Kelautan Nasional Jurnal Segara Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital International Journal of Remote Sensing and Earth Sciences (IJReSES) COJ (Coastal and Ocean Journal) Jurnal Manusia dan Lingkungan Journal of Fisheries & Marine Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital The International Journal of Remote Sensing and Earth Sciences (IJReSES)

Vincentius P Siregar

Department Of Marine Science And Technology, Faculty Of Fisheries And Marine Science, IPB University, Jl. Agatis, Babakan, Kec. Dramaga, Kota Bogor, Jawa Barat 16128 Indonesia

Author-ID : 636101

Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

Published : 73 Documents Claim Missing Document

Claim Missing Document

Articles

2 3 4 5 6

Akurasi Tematik Peta Substrat Dasar dari Citra Quickbird (Studi Kasus Gusung Karang Lebar, Kepulauan Seribu, Jakarta) (Thematic Accuracy of Bottom Substrate Map from Quickbrid Imagery (Case study: Gusung Karang Lebar, Kepulauan Seribu, Jakarta)) Muhammad Banda Selamat; Indra Jaya; Vincentius P Siregar; Totok Hestirianoto
ILMU KELAUTAN: Indonesian Journal of Marine Sciences Vol 17, No 3 (2012): Ilmu Kelautan
Publisher : Marine Science Department Diponegoro University

Salah satu kelemahan metode koreksi kolom air adalah dapat memunculkan bias dalam estimasi rasio koefisien attenuasi. Bias ini berkontribusi pada nilai akurasi tematik peta substrat dasar. Studi ini menggunakan pendekatan zonasi geomorfologi untuk meningkatkan akurasi tematik peta substrat yang dihasilkan dari metode koreksi kolom air. Nilai piksel citra Quickbird dikonversi ke radiansi dan dilanjutkan dengan koreksi kolom air untuk menghasilkan peta substrat dasar dengan tiga tema ekosistem, yaitu ekosistem pantai berpasir dengan substrat dominan pasir, ekosistem lamun dan terumbu karang. Data lapangan dikelompokkan menggunakan metode Bray curtis dan menjadi dasar bagi reklasifikasi. Profil geomorfologi pada citra satelit disadap dari gabungan kanal hijau dan merah, mengacu pada hasil survei batimetri. Pendekatan kombinasi ini terbukti dapat meningkatkan akurasi tematik peta substrat dasar hingga lebih dari 20%.Kata kunci: quickbird, substrat dasar, akurasi tematikBias may occur on attenuation coefficient ratio estimated from water column correction method. This bias then contribute to thematic accuracy of bottom substrate images. This study used geomorphologic spatial zonation to improve thematic accuracy of bottom substrate maps that produced from water column correction method. Quickbird pixel values were converted to the top of atmosphere radiance and followed by water column correction to make bottom substrate map with three themes ecosystem i.e. sandy ecosystem, seagrass ecosystem and coral reef ecosystem. Field data were grouped using Bray Curtis method and become basis of image reclassification. Geomorphological profile was extracted from green and red composite images, refer to a bathymetric survey. These combined approaches were significantly proved to improve thematic accuracy up to more than 20%.Key words: quickbird, bottom subtrate, thematic accuracy

Analisis Preferensi Visual Lanskap Pesisir Daerah Istimewa Yogyakarta untuk Pengembangan Pariwisata Pesisir Menuju pada Pengelolaan Wilayah Pesisir Berkelanjutan Nurul Khakhim; Dedi Soedharma; Ani Mardiastuti; Vincentius P. Siregar; Mennofatria Boer
Forum Geografi Vol 22, No 1 (2008): July 2008
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v22i1.4925

The aim of this research is to analyze of DIY coastal landscape with visual preference analysis for suistanble coastal tourism development and management. The unit of analysis that used is coastal typology. The guideline in deciding the classification of coastal typology is using the Response-Process System with relief/slope, main constructing material, genesis process and dominate process happened in the meantime such as tide, wave and river flow. This response-process system divide the coastal typology into seven classes including coastal typology of land erosion coast, sub aerial deposition coast, volcanic coast, structurally shaped coast, wave erosion coast, marine deposition coast and coast built by organism. The method of SBE (Scenic Beauty Estimation) is used for visual preference analysis, and the method used to compose the policy of costal tourism development is SWOT method. Result shows that all seven coastal typology are found in the coastal area. Land erosion coast and coast built by organism dominate in Gunungkidul coastal area and then in Bantul and Kulon Progo coastal area are dominated by marine deposition coast and sub aerial deposition coast. Volcanic coast, structurally shaped coast, wave erosion coast can only be found in a small area of Gunungkidul coast. Each of this coastal typology has a special land characteristic which can be used to develop its potential. Coast built by organism is very suitable for tourism activity proved by the high score of SBE from the respondents. Recommendation for developing coastal area in area of interest is by developing the coastal natural resources suitable to its physical typology, because this will make the management of coastal area for continuous development easier. Recommendations for coastal management in Gunungkidul including mapping and classification of protected karst area and mineable karst area to secure the run of coastal area management, for coastal management in Bantul using Managed realignment which plans for retreat and adopts engineering solutions that recognise natural processes of adjustment, and identifying a new line of defence where to construct new defences and move seaword model by constructing new defenses seaward the original ones. Last, for Kulon Progo coastal area using hold the line model whereby seawalls are constructed around the coastlines.

Penilaian Kerentanan Pantai menggunakan Metode Integrasi CVI-MCA Studi Kasus Pantai Indramayu Faizal Kasim; Vincentius P. Siregar
Forum Geografi Vol 26, No 1 (2012): July 2012
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v26i1.5051

The increasing of sea level due to climate change has been focused many research activities in order to know the coastal response to the change, and determine the important variables which have contribution to the coastal change. This paper presents a method for integrating Coastal Vulnerability Index (CVI), Multi Criteria Analysis (MCA) method and Geographic Information-System (GIS) technology to map the coastal vulnerability. The index is calculated based-on six variables: coastal erosion, geomorphology, slope, significant wave height, sea level change and tidal range. Emphasize has been made to the methodological aspect, essentially which is linked to: (i) the use of GIS technique for constructing, interpolation, filtering and resampling the data for shoreline grid, (ii) the standardization each rank of variables (0-1) and the use of several percentile (20%, 40%, 60%, and 80%) for each rank score, and (iii) the use of variable’s rank to map the relative (local) and standard (global) vulnerability of the coastline. The result show that for local, the index consist of four categories: very high (19.61%), high (68.63%), moderate (1,96%), and low (9.80%). Meanwhile, for global level, the index is constantly in low category.

Pemetaan Kompleksitas Habitat Dasar Perairan Menggunakan Data Batimetri di Perairan Pulau Kemujan Karimunjawa Arip Rahman; Vincentius P. Siregar; James P. Panjaitan
Jurnal Kelautan Tropis Vol 24, No 2 (2021): JURNAL KELAUTAN TROPIS
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jkt.v24i2.10498

The complexity of the substrate of the bottom waters describes the diversity of the bottom structure of the waters. The structure of the complexity of bottom waters can be measured by the rugosity. Manual method for measuring rugosity can be used chain method. Besides that rugosity can be calculated using bathymetry data using Surface Area from Elevation Grid Extension tools that integrated in ArcGIS which produces Arc-chord ratio (ACR) rugosity. Based on this method, a flat area has rugosity close to 1, while an area with high elevated will show rugosity value higher then 1 (>1). Measurement of the complexity of the bottom waters is carried out to see the condition of benthic habitat in the shallow waters of Kemujan Island, Karimunjawa Islands. Based on the rugosity index, conditions of bottom waters of the Kemujan Island are quite complex (ACR rugosity index, 2-2.044). The ACR rugosity index correlated quite well with the rugosity index of the field measurement (r = 0.76). Kompleksitas dasar perairan menggambarkan keragaman struktur dasar perairan. Struktur kompleksitas suatu dasar perairan dapat diukur dengan tingkat kekasaran (rugosity) dasar perairan. Metode pengukuran rugosity secara manual dilakukan dengan menggunakan metode rantai (chain). Selain itu rugosity juga dapat dihitung dengan menggunakan data kedalaman dengan menggunakan Surface Area from Elevation Grid Extension yang terintegrasi pada ArcGIS yang menghasilkan Arc-chord ratio (ACR) rugosity. Berdasarkan metode ini daerah datar memiliki nilai rugosity mendekati 1, sedangkan area dengan relief tinggi akan menunjukkan nilai rugosity yang lebih tinggi (>1). Pengukuran kompleksitas dasar perairan dilakukan untuk melihat kondisi habitat dasar di perairan dangkal Pulau Kemujan Kepulauan Karimunjawa. Berdasarkan indeks rugosity, kondisi dasar perairan Pulau Kemujan memiliki kompleksitas yang cukup tinggi (indeks ACR rugosity 2-2.044). Hal tersebut menggambarkan kondisi dasar perairan di sekitar lokasi penelitian cukup beragam. Indeks rugosity ACR berkorelasi cukup baik dengan indeks rugosity hasil pengukuran lapangan (r=0.76).

OBIA AND BTM INTEGRATION FOR MAPPING HABITAT COMPLEXITY OF CORAL REEFS ON HARAPAN-KELAPA ISLANDS, KEPULAUAN SERIBU Tarlan Subarno; Vincentius Paulus Siregar; Syamsul Bahri Agus
COJ (Coastal and Ocean Journal) Vol. 2 No. 1 (2018): COJ (Coastal and Ocean Journal)
Publisher : Pusat Kajian Sumberdaya Pesisir dan Lautan IPB

The habitat complexity is indirectly closely related to reef fish abundance. This study aims to map reefs habitat complexity by integrating object-based image analysis (OBIA) and habitat complexity analysis using benthic terrain modeler (BTM). The datasets used were SPOT-7 imagery and water depth derived from satellite imagery. The ground check was conducted to collect field data used as reference for classification and accuracy assessment of classification results. Classification of SPOT-7 imagery was performed using support vector machines (SVM) algorithm, by grouping shallow waters habitats into 4 classes on level 2 and 3 classes on level 3. Accuracy assessment was done by confusion matrix and resulting overall accuracy (OA) 83.55% for level 2 and 79.66% for level 3. The habitat complexity was analyzed using rugosity analysis method (Arc-Chord Ratio) from benthic terrain modeler (BTM) to obtain rugosity index in reefs area. The substrate covers were obtained from OBIA and complexity of habitats were obtained from BTM, then the overlay result shows varying rugosity index on the reef area in Harapan-Kelapa Islands. Keywords: coral reefs, OBIA, habitat complexity, rugosity

Development of Kd(490) Algorithm Using Medium Spatial Resolution Landsat 8 OLI Arround Shallow Waters In Panggang Island Budhi Agung Prasetyo; Wikanti Asriningrum; Vincentius Paulus Siregar
Journal of Applied Geospatial Information Vol 5 No 1 (2021): Journal of Applied Geospatial Information (JAGI)
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jagi.v5i1.2773

The state of water quality around Panggang Island, Seribu Islands, in recent decades experienced degradation caused by human activities. The parameters of the diffuse attenuation coefficient (Kd) is an important optical property-related attenuation of light in the water column, and its brightness. Landsat 8 data has potential to map the value of Kd(490) in regional waters in Indonesia. Landsat 8 data could provide solutions to spatial data availability of Kd(490) values in addition to Ocean Color data. The purposes of this research was to developed empirical algorithm of Landsat 8 data to derive values of Kd(490) that can be use as tools for monitoring water quality optically on a regional scale which could not be done by Ocean Color data that has spatial resolution limitation. In-situ measurement of radiometric data was done by using TriOS-RAMSES hyperspectral spectroradiometer with a range of 320 – 890 nm and spectral sampling of 3.3 nm on shallow-waters around Panggang Island. The development of Kd(490) algortihm was done by simulation on ratio of Green and Near-infrared band has great determination values with Kd(490) empirically, which that empirical algorithm can be applied on Landsat 8 data to derive its values. In addition, it is noted that the shallow-waters around Panggang Island, dominant affected by absorption of chlorophyll-a rather than scattering by suspended solids.

PENERAPAN ALGORITMA SPECTRAL ANGLE MAPPER (SAM) UNTUK KLASIFIKASI LAMUN MENGGUNAKAN CITRA SATELIT WORLDVIEW-2 Nunung Noer Aziizah; Vincentius Paulus Siregar; Syamsul Bahri Agus
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 13 No. 2 Desember 2016
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Remote sensing technology has been developed for monitoring and identification of coastal environment and resources, such as seagrasses. In Indonesia, particularly seagrass mapping spectrometer utilizing spectral library has not been done. This study aimed to determine the spectral signature based in situ measurement and image analysis, analyze the implementation of the algorithm Spectral Angle Mapper (SAM) and test accuracy in mapping seagrass to species level based on spectral libraries. Research conducted in seagrass Tunda Island, Banten. Satellite imagery used is WorldView-2 and the seagrass spectral reflectance was measured using a spectrometer USB4000. SAM classification algorithm utilizing spectral libraries and classify objects in a single pixel can be homogeneous. Classification results in the form of class Enhalus acoroides, Cymodocea rotundata, Thalassia hemprichii, and Halophila ovalis. The resulting accuracy of 35.6%. The area of each class is 0.8 hectares for the class Cymodocea rotundata, 2.79 hectares for Enhalus acoroides, class Thalassia hemprichii 3.7 hectares, and 3.5 hectares for Halophila ovalis. Classification of seagrass to species level yet produce good accuracy. Seagrass area with a variety of species and number of channels on a multispectral satellite image is assumed to be the cause of the low value of accuracy. AbstrakPemanfaatan teknologi satelit penginderaan jauh (remote sensing) sangat berkembang untuk identifikasi dan memantau sumberdaya alam wilayah pesisir, seperti lamun. Di Indonesia khususnya pemetaan lamun memanfaatkan pustaka spektral dari spektrometer belum banyak dilakukan. Penelitian ini bertujuan untuk mengetahui besaran spektral lamun berdasarkan pengukuran in situ dan analisis citra satelit, memetakan lamun hingga tingkat spesies berdasarkan pustaka spektral pengukuran in situ dengan penerapan algoritma SAM dan menguji tingkat akurasinya. Penelitian dilaksanakan di ekosistem lamun Pulau Tunda, Banten. Citra satelit yang digunakan adalah WorldView-2 dan reflektansi spektral lamun diukur menggunakan spektrometer USB4000. Algoritma klasifikasi SAM memanfaatkan pustaka spektral dan mengkelaskan obyek dalam satu piksel secara homogen. Hasil klasifikasi berupa kelas lamun Enhalus acoroides, Cymodocea rotundata, Thalassia Hemprichi, dan Halophila ovalis. Akurasi yang dihasilkan sebesar 35.6 %. Luas area masing-masing kelas adalah 0.8 Ha untuk kelas Cymodocea rotundata, 2.79 Ha untuk kelas Enhalus acoroides, 3,7 Ha kelas Thalassia hemprichii, dan 3.5 Ha untuk Halophila ovalis. Klasifikasi lamun hingga tingkat spesies belum menghasilkan akurasi yang baik. Area lamun dengan jenis yang beragam dan jumlah saluran pada citra satelit multispektral diasumsikan menjadi penyebab rendahnya nilai akurasi.

PEMETAAN ZONA GEOMORFOLOGI EKOSISTEM TERUMBU KARANG MENGGUNAKAN METODE OBIA, STUDI KASUS DI PULAU PARI (GEOMORPHIC ZONES MAPPING OF CORAL REEF ECOSYSTEM WITH OBIA METHOD, CASE STUDY IN PARI ISLAND) Ari Anggoro; Vincentius P. Siregar; Syamsul B. Agus
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 12 No. 1 Juni 2015
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1134.461 KB)

Penelitian ini menggunakan penerapan klasifikasi berbasis obyek (OBIA) untuk pemetaan zona geomorfologi ekosistem terumbu karang di Pulau Pari. Penerapan metode OBIA menggunakan algoritma multiresolusi segmentasi dengan parameter skala yang berbeda pada setiap level. Metode klasifikasi yang digunakan untuk level 1 dan 2 dengan klasifikasi kontekstual. Hasil menunjukkan akurasi keseluruhan untuk level 1 (level terumbu) sebesar 97% dan level 2 sebesar 87% (zona geomorfologi). Hasil penelitian ini menunjukkan bahwa metode OBIA mampu memetakan dengan baik dan dapat menjadi metode alternatif pada pemetaan zona geomorfologi ekosistem terumbu karang untuk di wilayah lainnya.Kata Kunci: Segmentasi, OBIA, Zona geomorfologi, Pulau Pari

KLASIFIKASI MULTIKSKALA UNTUK PEMETAAN ZONA GEOMORFOLOGI DAN HABITAT BENTIK MENGGUNAKAN METODE OBIA DI PULAU PARI (MULTISCALE CLASSIFICATION FOR GEOMORPHIC ZONE AND BENTHIC HABITATS MAPPING USING OBIA METHOD IN PARI ISLAND) Ari Anggoro; Vincentius Paulus Siregar; Syamsul B. Agus
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 2 Desember 2017
Publisher : Indonesian National Institute of Aeronautics and Space (LAPAN)

This study used multiscale classification and applied object-based image analysis (OBIA) for geomorphic zone and benthic habitats mapping in Pari islands. An optimized segmentation was performed to get optimum classification result. Classification methods for level 1 and 2 used contextual editing classification and for level 3 used support vector machines classifier. The results showed that overall accuracy for level 1 was 97% (reef level), level 2 was 87% (geomorphic zone), and level 3 was 75% (benthic habitats). Accuracy achieved by support vector machines classification was performed only in level 3 and optimum scale value achieved was 50 in compare with other scale values, i.e. 5, 25, 50, 75, 95. OBIA methods can be used as an alternative for geomorphic zone and benthic habitats map. Abstrak Penelitian ini menggunakan klasifikasi multiskala dan penerapan analisis citra berbasis obyek (OBIA) untuk pemetaan zona geomorfologi dan habitat bentik di Pulau Pari. Analisis berbasis obyek dilakukan optimasi pada proses segmentasi untuk mendapatkan hasil klasifikasi optimal. Metode klasifikasi pada level 1 dan 2 menggunakan klasifikasi contextual editing dan pada level 3 menggunakan klasifikasi Support Vector Machines (SVM). Hasil penelitian ini menunjukkan akurasi keseluruhan pada level 1 yaitu 97% (reef level), level 2 yaitu 87% (Geomorphic level), dan level 3 yaitu 75% (benthic habitat level). Klasifikasi SVM hanya diterapkan pada level 3 dan nilai skala optimum sebesar 50 dari percobaan nilai skala yaitu 5, 25, 50, 75, 95. Metode OBIA dapat digunakan sebagai alternatif untuk pemetaan zona geomorfologi dan habitat bentik.

COASTAL UPWELLING UNDER THE INFLUENCE OF WESTERLY WIND BURST IN THE NORTH OF PAPUA CONTINENT, WESTERN PACIFIC Harold J.D. Waas; Vincentius P Siregar; Indra Jaya; Jonson Lumban Gaol
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 9, No 2 (2012)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Coastal upwelling play an important role in biological productivity and the carbon cycle in the ocean. This research aimed to examine the phenomenon of coastal upwelling that occur in the coastal waters north of Papua continent under the influence of Westerly Wind Burst(WWB) prior to the development of El Nino in the Pacific. Data consisted of sea surface temperature, vertical oceanic temperature, ocean color satellite image, wind stress and vector wind speed image, sea surface high, and Nino 3.4 index. Coastal upwelling events in the northern coastal waters of Papua continent occurred in response to westerly winds and westerly wind burst (WWBs) during December to March characterizing by low sea surface temperature (SST) (25 - 28C), negative sea surface high deviation and phytoplankton blooming, except during pre-development of the El Nino 2006/2007 where weak upwelling followed by positive sea surface high deviation. Strong coastal upwelling occurred during two WWBs in December and March1996/1997 with maximum wind speed in March produced a strong El Nino 1997/1998. Upwelling generally occurred along coastal waters of Jayapura to Papua New Guinea with more intensive in coastal waters north of Papua New Guinea indicated by Ekman transport and Ekman layer depth maximum.

Co-Authors . Rosmasita Ade Ayu Mustika Adriani Sunuddin Afwan Syaugy Agus, Syamsul B. Alfiqi Maulana Alim Setiawan Amelia Suryanita Amran, Muhammad Anshar Andi Alamsyah Rivai Andriani Sunuddin Anggi Tiarasani Ani Mardiastuti Antonius Bambang Wijanarto Ari Anggoro Ari Anggoro Arip Rahman Arip Rahman Aryo Hanggono Asmadin, Asmadin Ayub Sugara Baba Barus Bisman Nababan Budhi Agung Prasetyo Budhi Agung Prasetyo DEDI SOEDHARMA Dedi Soedharma Dietrich G. Bengen Djisman Manurung Doddy M. Yuwono, Doddy M. Domu Simbolon Ega Putra Emma Suri Yanti Siregar Emma Suri Yanti Siregar, Emma Suri Yanti Esty Kurniawati ESTY KURNIAWATI Ety Parwati Faizal Kasim Fanny Meliani Fredinan Yulianda Gatot H. Pramono, Gatot H. Guido Roberto Jerun Parera Harold J.D. Waas Harold J.D.Waas Hartoni Hartoni Henry Munandar Manik Herianto Heru Arafat Hestirianoto, Totok Hidayat Pawitan Hiroki Yasuma I Wayan Nurjaya Ibnu Sofian, Ibnu indah kartika Indra Jaya Indra Jaya Indra Jaya Indra Jaya Indra Jaya Indra Jaya Insaniah Rahimah Irfan Yulianto Iwan E. Setyawan, Iwan E. James Parlindungan Panjaitan Jonniere, Romie Jonson Lumban Gaol Kasim, Faizal Kaulina Silvitiani Khairul Amri Krisna Rendi Awalludin LILIK BUDIPRASETYO Mennofatria Boer Mira Harimurti Miswadi Miswadi Muhammad Banda Selamat Muhammad Banda Selamat Muhammad Banda Selamat Muhammad Iqra Prasetya Muhammad Rizki Nandika Muhammad Siddiq Sangadji Muhammad Sudibjo Mulia Purba Mutiara Alkayakni Harahap Nadia Shalehah Nani Hendiarti Nico Wantona Prabowo Nunung Noer Aziizah Nunung Noer Aziizah Nunung Noer Aziizah Nunung Noer Aziizah, Nunung Noer Nur Audina Nurjannah Nurdin Nurul Khakhim Nurul Khakhim Prasetya, Muhammad Iqra Risti Endriani Arhatin Riza Aitiando Pasaribu Romie Jhonnerie Romy Ketjulan, Romy Ronny I. Wahju Rosmasita, Rosmasita Sabilah, Anisa Aulia Sakka Sakka Sam Wouthuyzen Sam Wouthuyzen Sangadji, Muhammad Siddiq Setyo Budi Susilo Susilo, Setyo B. Syamsul Agus Syamsul B. Agus Syamsul B. Agus Syamsul B. Agus Syamsul B. Agus Syamsul Bahri Agus, Syamsul Bahri Tarlan Subarno Tarlan Subarno, Tarlan Wahidin, Nurhalis Wikanti Asriningrum Wikanti Asriningrum Wikanti Asriningrum Wikanti Asriningrum Wildan Tino Zulhamsyah Imran

Title

Found 73 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 73 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 73 Documents
Search