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All Journal JURNAL ILMIAH GEOMATIKA International Journal of Social Service and Research Action Research Literate (ARL) JURNAL RETENTUM
Wiweka Wiweka
Kantor Kedeputian Penginderaan Jauh LAPAN Jl. Lapan 70 Pekayon Pasar Rebo Jakarta Timur 13710
Humanities Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Social Sciences

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ANALISA SEDIMENTASI DI MUARA KALI PORONG AKIBAT PEMBUANGAN LUMPUR LAPINDO MENGGUNAKAN DATA CITRA SATELIT ASTER Pahlevi, Arizona Maulidiyan; Wiweka, Wiweka
GEOMATIKA Vol 16, No 2 (2010)
Publisher : Badan Informasi Geospasial in Partnership with MAPIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1383.094 KB) | DOI: 10.24895/JIG.2010.16-2.237

Abstract

Kali Porong is Lapindo mud vulcano disposal area, possibility that Lapindo mud vulcano flow caused sediment material in the area of Kali Porong estuary, which is located in the Madura strait. Therefore, necessary of research on sedimentation use remote sensing technology, with Aster satellite imagery as main data, Landsat7 and Landsat 5 satellite imagery as comparing data. Image processing used Lemigas algoritm (1997), which is based on the Digital Number (DN) and Jing Li algorithm (2008), which is based on the reflectan values. It also sought land change and potential for sediment deposition, based on the results of image processing, tidal data, tidal currents, and bathimetric contours. Results of this research are Lemigas algorithm have determination coefficient (R2) of 0.605 against the field data, and Jing Li algorithms have determination coefficient (R2) of 0.827 against the field data. Sedimentation distribution in Kali Porong estuary likely dynamic, influenced by seasonal factors, tidal and tidal currents, bathimetric contours, and source of materials sediment. Potential precipitation occurs in the sediments along sidoarjo-Pasuruan coast, especially in the Kali Ketingan Estuary and Kali Porong Estuary. The largest rate of Land change occurred in the year 2006 - 2007 with a rate 93.298 ha / year.Keywords : Sedimentation, Lemigas Algorithm, Jing Li Algorithm, Land changeABSTRAKKali Porong merupakan area pembuangan lumpur lapindo. Tidak menutup kemungkinan bahwa adanya aliran lumpur lapindo mengakibatkan material mengendap di daerah muara Kali Porong, yang berada di Selat Madura. Oleh karena itu diperlukan penelitian mengenai sedimentasi menggunakan teknologi penginderaan jauh, yaitu dengan data citra satelit ASTER tahun 2005 hingga 2008 sebagai data utama, citra satelit Landsat7 ETM+ tahun 2003 dan Landsat 5 TM tahun 1994 sebagai data pembanding. Algoritma yang digunakan untuk pengolahan citra adalah algoritma Lemigas (1997) yang didasarkan pada Digital Number (DN) dan algoritma Jing Li (2008) yang didasarkan pada nilai reflektan. Selain itu juga dicari perubahan daratan serta potensi endapan sedimen berdasarkan hasil pengolahan citra, data pasang surut, data arus, dan kontur bathimetri. Hasil penelitian ini adalah algoritma Lemigas mempunyai nilai koefisien determinasi (R2) sebesar 0.605 terhadap data lapangan, untuk algoritma Jing Li mempunyai nilai koefisien determinasi (R2) sebesar 0.827 terhadap data lapangan. persebaran sedimentasi di Muara Kali Porong cenderung dinamis, dengan dipengaruhi oleh faktor musim, pasang surut dan arus pasang surut, serta kontur bathimetri dan sumber material sedimen. Potensi pengendapan sedimen terbesar terjadi di hampir sepanjang pesisir sidoarjo-pasuruan, terutama di Muara Kali Ketingan dan Muara Kali Porong. Laju pertambahan daratan terbesar adalah tahun 2006-2007, dengan laju 93.298 Ha/tahun.Kata Kunci: Sedimentasi, algoritma Lemigas, Algoritma Jing Li, Perubahan lahan
PENDEKATAN PROBABILISTIC NEURAL NETWORK (PNN) BERBASIS EXPECTATION MAXIMUM (EM) UNTUK PERMASALAHAN KLASIFIKASI GABUNGAN Wiweka, Wiweka; Setiawan, Wawan
GEOMATIKA Vol 18, No 1 (2012)
Publisher : Badan Informasi Geospasial in Partnership with MAPIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (553.166 KB)

Abstract

Makalah ini menyajikan desain pengklasifikasi dengan pendekatan jaringan neural (syaraf) yang didasarkan pada penggunaan metode Ekapentasi Maksimum (EM). Aturan keputusan pengklasifikasi Bayes menggunakan kesalahan minimum dalam klasifikasi citra gabungan  multi waktu. Dalam khasus ini, model jaringan neural perceptron multi lapis Probabilistic Neural Network (PNN), digunakan untuk mengestimasi nonparametrik probabilitas posterior suatu kelas. Korelasi temporal citra dihitung dengan probabilitas gabungan masing-masing kelas secara otomatis dengan menerapkan formula khusus yaitu algoritma ekspektasi maksimum dari citra multi waktu. Eksperimen dilakukan pada dua citra multi waktu yaitu citra Saguling yang diambil pada dua waktu yang berbeda. Berdasarkan hasil eksperimen pada dua daerah uji tersebut, dapat ditunjukkan bahwa tingkat akurasi pengklasifikasi PNN rata-rata lebih baik dibandingkan dengan model Propagasi Balik (BP), dan Ekepektasi Maksimum (EM)  dapat meningkatkan kemampuan suatu pengklasifikasi. Pengklasifikai PNN dengan menerapkan ekpektasi maksimum memiliki kemampuan pengenalan yang konsisten untuk citra multi waktu, dan juga konsisten untuk setiap pengenalan kategori kelas obyek. Metodologi klasifikasi yang diusulkan dapat memecahkan permasalahan multi  waktu secara efektif.KataKunci:Probabilistik Jaringan Syaraf, Ekspektasi Maksimm, Citra Multitemporal, Kelas Objek, Pengenalan  ABSTRACTThis paper presents a classifiers design of neural network approachbased on Expectations Maximum (EM), a Bayes classifier decision rule using the Minimum Error to clasify combined multi-temporal imageries. In this particular, multilayer perceptron neural network model with Probabilistic Neural Network (PNN) is used for nonparametric estimation of posterior class probabilities. Temporal image correlation was calculated  automatically usingprior joint probabilities of each class by applying a special formula that is algorithm expectation maximum of multi-temporal imagery. Experiments wasperformed on two multi-temporal Saguling imagestakenat two different  epochs. Based on experimental results on two test areas, it can be shown that the average accuracy rate of PNN classifier is better than the Back Propagation (BP), and the Expectation Maximum (EM) can increase the classifiers ability. Multinomial PNN classifierapplying the maximum expected have a consistent recognition capability for multitemporal imagery, and also consistent for each object class category. The proposed classification methodology can effectively solve the problem when classifying multi-temporalimagery.Keywords: Probablistic Neural Networks, Expectation Maximum, Multitemporal Images, Class Object, Recognition
Analysis of Political Law and Public Policy on the Issue of BPJS Health Losses in the JKN Program in 2024 Wiweka, Wiweka; Arifin Hoesein, Zainal
JURNAL RETENTUM Vol 5 No 1 (2023): MARET
Publisher : Pascasarjana UDA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46930/retentum.v7i1.5288

Abstract

In 2024, BPJS Health will be in the spotlight regarding the alleged loss of IDR 20 trillion in the JKN Program, due to potential fraud and inconsistencies in fund management. This issue raises questions about the effectiveness of public policy and legal politics in managing BPJS Health as well as supervision of programs that affect public health services. This study aims to analyze the influence of politics, law, and public policies implemented in 2024 on BPJS Health's financial governance, especially related to losses in the JKN program, as well as to find solutions to improve financial management and reduce losses. The research method used is normative juridical, using a legislative approach and an analytical approach. The results show that the imbalance between the receipt of contributions and claim costs, as well as inefficient cross-subsidy policies, are the main causes of losses. Suggested policy solutions include adjustment of contribution rates, improvement of cross-subsidies, strengthening supervision of medical claims, and management based on more accurate data. This study shows the need for more responsive, efficient, and data-based policies to overcome BPJS Health losses, as well as the importance of transparent and accountable management so that the JKN program can run sustainably and provide equal access to health for all Indonesian people.
THE LEGAL PROTECTION OF HOSPITALS IN THE CASE OF NON-BPJS PATIENTS WHO ABSCOND AS A FORM OF BAD FAITH DUE TO THEIR INABILITY TO PAY Wiweka, Wiweka
International Journal of Social Service and Research Vol. 4 No. 11 (2024): International Journal of Social Service and Research
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/ijssr.v4i11.1117

Abstract

Hospitals often encounter financial difficulties when non-BPJS patients evade payment due to financial incapacity, with some institutions unfairly shifting the financial burden onto doctors. This situation raises serious legal, ethical, and employment concerns, especially in light of Law No. 17 of 2023 on Health, which mandates institutional responsibility for patient management. Meanwhile, Artificial Intelligence (AI) offers promising solutions for predicting and mitigating financial risks by identifying high-risk patients, though it introduces new challenges regarding data privacy, accountability, and liability. This study aims to explore the legal protections available to doctors when patients abscond without paying, and to propose a legal framework for integrating AI in healthcare to prevent such incidents. Using a normative legal approach, the research analyzes key provisions of Law No. 17/2023, employment regulations, and relevant case studies involving financial disputes between doctors and hospitals. The results show that imposing financial liability on doctors not only breaches employment principles but also contradicts healthcare regulations. Furthermore, AI can improve financial risk management by helping hospitals predict and prevent non-payment cases, though its implementation requires clear legal guidelines to avoid unintended consequences for medical staff. In conclusion, hospitals must bear financial responsibility for unpaid patient bills to protect doctors' legal rights. Additionally, a comprehensive regulatory framework for AI is essential to ensure that the technology is implemented fairly, safeguarding both healthcare professionals and patient interests.
Detention of Incapacitated Patients by Hospitals as a Violation of Constitutional Rights in Health Services Wiweka, Wiweka; Barthos, Megawati
International Journal of Social Service and Research Vol. 5 No. 6 (2025): International Journal of Social Service and Research
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/ijssr.v5i6.1247

Abstract

Detention of patients in hospitals for inability to pay is a practice that is contrary to the principles of human rights and social justice. This practice not only violates the right to individual liberty as stipulated in Article 28G paragraph (1) and Article 28H paragraph (1) of the 1945 Constitution of the Republic of Indonesia, but also contradicts the mandate of Article 189 paragraph (1) letter f of Law Number 17 of 2023 concerning Health which requires hospitals to carry out social functions by providing services to underprivileged patients. This research aims to examine the applicable legal arrangements, evaluate the implementation of the social function of hospitals, and formulate fair and proportionate legal reforms in the face of the reality of patient detention. Using empirical juridical approaches and qualitative methods, data were collected through literature studies and interviews with relevant parties. The results of the study show that there is an imbalance between the hospital's obligation to carry out social functions and the hospital's institutional needs to cover operational costs. Unclear financing mechanisms for underprivileged patients, weak coordination between government agencies, and suboptimal regulatory supervision lead to violations of patients' rights. Therefore, comprehensive legal reform is needed by emphasizing the state's obligation to ensure health services without discrimination, as well as developing a financing mechanism that ensures the sustainability of hospitals. The reformulation of legal norms in the Health Law and its derivative apparatus must be based on the principles of social justice and the state's responsibility for the right to health, so that the law truly protects the basic rights of citizens while maintaining the balance of the health service system
Mengidentifikasi Manajemen Bimbingan Konseling di Sekolah SMP Negeri 11 Medan Linto, Ofa; Rejeki, Desi Sri; Azzahra, Tary; Christy, Veranita; Wiweka, Wiweka
Action Research Literate Vol. 8 No. 12 (2024): Action Research Literate
Publisher : Ridwan Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/arl.v8i12.2530

Abstract

Manajemen bimbingan dan konseling di sekolah merupakan aspek penting dalam memberikan dukungan holistik kepada siswa yang mencakup akademik, emosional, sosial dan kesejahteraan. Program ini diciptakan untuk membantu siswa mengatasi perkembangan, tekanan akademik dan bisang perilaku positif. Selain itu, bimbingan akademik dapat membantu mengarahkan siswa merencanakan dan mencapai tujuan mereka. Penelitian ini bertujuan untuk meneliti mengenai pengdentifikasian manajemen bimbingan konseling di Sekolah SMP Negeri 11 Medan. Metode pada penelitian ini adalah metode deskriptif kualitatif dengan pendekatan wawancara mendalam. Teknik pengumpulan data pada penelitian ini menggunakan Wawancara, observasi dan dokumentasi. SMP Negeri 11 Medan mendukung perkembangan siswa secara holistik, membantu mengatasi tekanan akademik dan masalah interpersonal, serta mempromosikan perilaku positif. Meskipun ada kendala sumber daya, evaluasi menunjukkan perlunya peningkatan metode dan kerjasama dengan orang tua serta komunitas untuk memastikan relevansi layanan dengan kebutuhan siswa.
Co-Authors Azzahra, Tary Barthos, Megawati Christy, Veranita Desi Sri Rejeki Linto, Ofa Pahlevi, Arizona Maulidiyan Siti Hawariyah Surlan Surlan Wawan Setiawan Zainal Arifin Hoesein