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Mental health is an important component in the realization of the quality of life ofsociety as a whole. The prevention of mental health disorders can be earlydetection in primary health care facilities. However, not all primary health carefacilities are able to provide mental health services. The rapid development ofInternet technology today can be a solution in early detection services usinginternet-based media website. This study aims to develop a prototype mentalhealth early detection that can be used for detection of mental health communityand media promotion. Researchers identify determinants mental health (man,material, method, machine and market) to determine the needs of system by usingqualitative research methods. The prototype system was developed by SystemDevelopment Life Cycle (SDLC) which the stages are planning, analysis, design,and implementation of system. This research resulted a prototype website thatprovides information level overview of mental disorder of visitors website as asimple portrait of mental health community problems, media information andeducation. The prototype can be developed with the addition of online chatfeatures as well as mapping ODMK (People With Mental Health Problems) area-based to support access community mental health services.Keywords: development, website, early detection, mental health
Permasalahan kesehatan masyarakat terkait pelaksanaan kegiatan deteksi tumbuh kembang anak di Kabupaten Nunukan adalah rendahnya jumlah anak yang dideteksi tumbuh kembang. Jumlah anak yang dideteksi tumbuh kembang pada tahun 2007 sebesar 23,5% (target pada standart pelayanan minimal = 90%). Rendahnya cakupan anak yang di deteksi menyebabkan beberapa anak yang tidak datang lepas dari pengamatan, sehingga perubahan tumbuh kembang tidak bisa terdeteksi secara berkala. Kejadian tersebut menyebabkan kejadian gangguan tumbuh kembang tidak bisa diketahui secara cepat dan akurat. Akibatnya anak terlambat untuk dirujuk ke tempat pelayanan kesehatan lanjutan karena kejadiannya lambat diketahui. Sistem informasi pemantauan gangguan tumbuh kembang anak yang sedang berjalan belum bisa menjawab kebutuhan manajemen program, sehingga penelitian ini bertujuan agar tersusun model sistem pemantauan yang efektif dan efisien dengan prototipe program dan basis data sehingga dapat mendukung manajemen program. Prototipe diharapkan dapat menghasilkan laporan tepat waktu, cakupan indikator tumbuh kembang anak yang lebih valid, daftar kasus yang terinci, jumlah anak yang melakukan deteksi secara rutin, daftar anak yang harus dideteksi dan informasi keberadaan tenaga terlatih di posyandu, TK dan puskesmas. Rancangan penelitian ini menggunakan metodologi pengembangan sistem dengan metode incremental yaitu menggabungkan elemen-elemen dalam model berurutan linear dengan filosofi iteratif dari metode prototipe. Hasil penelitian menunjukkan bahwa pelaksanaan pemantauan gangguan tumbuh kembang anak di Kabupaten Nunukan belum berjalan sesuai pedoman. Tenaga pelaksana belum melibatkan kader dan guru TK, keluaran sistem belum menghasilkan informasi kasus baru atau lama, jumlah anak yang dideteksi secara rutin dan persen puskesmas, posyandu dan TK dengan tenaga terlatih. Kesimpulan penelitian ini menunjukkan bahwa 1)Rendahnya cakupan deteksi disebabkan karena belum ada keterlibatan masyarakat dan lintas sektor terkait dalam kegiatan ini. 2) Sistem informasi yang dikembangkan menggunakan visual programming dengan database dari SQL, agar dapat ditanam di website. 3)Sistem baru dapat menghasilkan indikator input, proses dan output yang lebih valid dan lebih cepat. 4) Menghasilkan daftar sasaran yang harus dideteksi tumbuh kembang secara rinci sehingga permasalahan pemantauan gangguan tumbuh kembang anak di Kabupaten Nunukan dapat terselesaikan.
It has already known that the problems of publich health about development and growth monitoring abnormally children program in Nunukan Regency on 2007th is the descent number of the children who detected development and growth. The number of the children who detected development and growth on 2007th is 23,5% (minimum standart = 90%). The descent of the children who detected coverage to make some children who don?t come to detection and stimulation place out of evaluation, so that development and growth change can?t detection regularly. It has to make the children development and growth abnormal can not known on time and accurately. The impact it, the children late revered to the publich health serveice, because it has to late to known. The information system development to monitor development and growth abnormally children in Nunukan Regency can not given yet manajemen program demand., so that this research goal is to create effective and efficient monitoring system with prototype and basis data so that be able to support manajemen program. Prototype be hoped can to produce routine and incidental report, development and growth indicator program more valid, listing case detail, number of the children who detected routinely, the children listing who have to detected and man power. This research design to develop system with incremental and iterative model to add elemens in the linear structure. Result of this research known that monitor abnormal development and growth children in Nunukan Regency haven?t been doing like the guidens program yet. Kader posyandu and kindergarden teacher not joint this program yet, output system not result 1) old and new case information 2) number of children to detected routinely and 3) persen posyandu, kindergarden and puskesmas with man power have trained. This research conclussion to show that 1) Descent of children detected coverage, because kader and another departemet not joined this program yet 2) The information system development with visual programming and SQL database in order to upload website. 3) New system able to produce indicator input, proses and output more valid and fastly. 4) Produce children listing who have to detected development and growth detail so that the problem of abnormal development and growth children in Nunukan Regency can to solved.
Latar Belakang: Fraud dalam klaim Jaminan Kesehatan Nasional (JKN), khususnya dalam bentuk upcoding diagnosis penyakit kardiovaskular, merupakan tantangan serius yang dapat mengancam keberlanjutan sistem jaminan kesehatan di Indonesia. Penyakit kardiovaskular, sebagai penyebab beban biaya tertinggi dalam layanan rawat inap, rentan terhadap praktik kecurangan yang sulit dideteksi melalui metode konvensional. Oleh karena itu, diperlukan pendekatan berbasis data dan teknologi untuk mendeteksi potensi fraud secara lebih efisien. Metode: Penelitian ini menggunakan pendekatan kuantitatif eksploratif dengan metode supervised machine learning. Data klaim rawat inap penyakit kardiovaskular tahun 2022–2024 dianalisis berdasarkan beberapa variabel yaitu lama hari rawat, lama rawat di ICU, waktu penggunaan ventilator, jumlah diagnosis sekunder, jumlah prosedur, dan biaya RS. Proses mencakup cleansing, encoding, pseudo-labeling, feature selection, serta pelatihan model menggunakan beberapa algoritma supervised, seperti Random Forest, Tree, Gradient Boosting, Neural Network, Naïve Bayes, Logistic Regression, Support Vector Machine (SVM), dan kNN. Evaluasi kinerja model dilakukan dengan menggunakan metrik akurasi, precision, recall, F1-score, dan AUC. Hasil: Hasil penelitian menunjukkan bahwa algoritma Random Forest menghasilkan performa terbaik dalam mendeteksi potensi fraud pada sebagian besar kategori diagnosis dan kelas rumah sakit. Nilai akurasi dan AUC yang dihasilkan berada dalam kategori baik hingga sangat baik. Selain itu, analisis pola klaim menunjukkan adanya perbedaan distribusi biaya dan indikator klinis antara klaim normal dan klaim yang terindikasi anomali, mendukung keberadaan pola upcoding Kesimpulan: Model machine learning, khususnya Random Forest, terbukti efektif dalam mendeteksi potensi fraud upcoding diagnosis penyakit kardiovaskular pada klaim JKN. Penerapan sistem berbasis algoritma ini berpotensi menjadi alat bantu auditor dalam pengawasan klaim yang lebih akurat dan efisien. Hasil penelitian ini memberikan dasar bagi pengembangan sistem deteksi fraud terintegrasi di masa depan guna meningkatkan akuntabilitas dan efisiensi pembiayaan kesehatan.
Background: Fraud in the National Health Insurance (JKN) claims, particularly in the form of upcoding for cardiovascular disease diagnoses, poses a serious threat to the sustainability of Indonesia’s health financing system. As the leading contributor to inpatient service expenditures, cardiovascular disease claims are highly susceptible to fraudulent practices that are difficult to detect using conventional methods. Therefore, a data-driven and technology-based approach is essential for more efficient fraud detection. Methods: This study employed a quantitative exploratory approach using supervised machine learning methods. The dataset consisted of inpatient cardiovascular disease claims from 2022 to 2024. The analysis involved data cleansing, encoding, pseudo-labeling, feature selection, and model training using several classification algorithms such as Random Forest, XGBoost, and Logistic Regression. Model performance was evaluated using metrics including accuracy, precision, recall, F1-score, and AUC. Results: The results demonstrated that the Random Forest algorithm achieved the highest performance in detecting potential fraud across most diagnosis categories and hospital classes. The accuracy and AUC values indicated good to excellent classification performance. Furthermore, the claim pattern analysis revealed distinct differences in cost and clinical indicators between normal and anomaly-labeled claims, supporting the presence of potential upcoding. Conclusion: Machine learning models, particularly Random Forest, proved to be effective in detecting potential upcoding fraud in cardiovascular disease claims within the JKN program. The implementation of algorithm-based fraud detection systems can serve as a decision-support tool for auditors, enabling more accurate and efficient claim monitoring. This study provides a foundation for the future development of integrated fraud detection systems to enhance accountability and efficiency in national health financing.
Kabupaten Pidie dengan jumlah Puskesmas sebanyak ( 26 Euskesmas telah memiliki jumlah perawat puskesmas yang telah mengikuti pelatihan BC dan IC CMHN sebanyak 46 perawat dengan jumlah pasien gangguan jiwa 808 orang (0,16%) dari jumlah penduduk Kabupaten Pidie. Jumlah pasien yang telah dirawat oleh perawat CMHN di Puskesmas sebanyak 285 orang (35,3 %} dari jumlah pasien di Kabupaten Pidie. Masalah keperawatan pada pasien gangguan jiwa yang telah dirawat oleh Perawat CMHN di Kabupaten Pidie adaHl alusinasi Q2,6 %), Isolasi Sosial (12,3 %), Harga Diri Rendah (10,5 %), Waham (§,5 %' Defisit Perawatan Diri (17,9 %) dan Prilaku Kekerasan (17, 2 %). Adapun Diagnosa Medis ¥ang sering muncul pada pasien gangguan jiwa di puskesmas adalah gangguan mental organik (demensia, delirium), gangguan penggunaan napza (gangguan penggunaan zat, gangguan penggunaan pengetahuan masyarakat tentang masalah gangguan jiwa, masih adanya stigma masyarakat terhadap penderita gangguan jiwa dan tingginya angka kemiskinan di Kabupaten Pidie. Metodologi yang digunakan dalam tesis ini adalah metode incremental dan iterative melalui tahapan perencananalisis, perancangan, pengkodean dan uji coba sistem. Identifikasi dan analisis masalah sistem dilakukan dengan wawancara rnendalam, telaah dokumen dan observasi pafla unit kerja dinas kesehatan dan puskesmas serta beberapa informan yang terkait. Perancangan prototype dilakukan dengan menggunakan bahasa pemrograman PHP dan basis data mysql yang bersifat open source. Uji coba prototfpe dilakukan menggunakan data sampel di Laboratorium Komputer Fakultas Kesehatan Masayarakat Departemen Biostatistika: Universitas Indonesia. Sistem informasi kesehatan jiwa masyarakat yang dikembangkan ini akan memberikan informasi yang berkualitas yang dapat dapat digunakan sebagai pendukung keputusan bagi pengambil kebijakan di Dinas Kesehatan Kabupaten Pidie dalam pelaksanaan program penanggulangan masalah kesehatan jiwa masyafakat. Sebagai suatu decision support system, system infonnasi kesehatan jiwa masyarakat dapat memberikan dukungan sampai level empat yaitu estimate ded sion c nsequences. Pada level ini informasi yang dihasilkan memungkinkan.jajaran pimpinan dinas kesehatan melihat dampak-dampak yang timbul dari program yang telab. dilaksanakan. Hasil analisis ini juga da:P-at dipergusnebagai umpan balik. pada puskesmas. Hasil dari pengembangan sistem infonnasi ini adalah dihasilkan prototype.
Pidie regency, whith has 26 health centre, have 46 nurses who have been accompanied in BC and IC CMHN training this regen y has 808 mental illness people or 0.16% of the poJ?ulation there. The patients who has been care by CMHN nurses are 285 patient (35.3%} of all patient there The problems of these patient are hallucination (32.6%), social isolation (12.3%) low self esteem (10.5%), delusion (9,5%), self care deficit (17,9%) and violence (17.2%). Therefote medical diagnosis which often happened on mentally iUness patients re eranic mental (desorder, delirium), drugs abused, skizofrenia, psychotic cronic, psychotic acute, depresif, neurotic (fobic, panic and anxiety), anxiety and epression, adaptation disruption, mental retardation, mentally sick in children and adulesiont, behayior disruptioannd epilepi). The problems that should be solved by the government are first, the functions of department and local clinic and another related sources. Prototype planning is done by PHP programming language and database My SQL which is open source. Prototype trial is done by sample data in computer laboratory of Biostatistic Department of Public health faculty. This information system development will give a good information which can be used as a support of decision for policy maker in health department of Pidie regency in preventing mental health.problem program. As dicision support systeinformation system could give support to the fourth level which is estimate decision consequences. In this level, Ute information cou d make the channan of health department top at the effects of the programs done. The analysis results also could be used as a facder or clinic. The result of thts information system devel-opment is pmduced by the prototype of public mental health information system of health departmen in Pidie regency in 2008 which could be operated onlin o offline. To makes this information system wo9cs well and continuoysly, we need the commitment and supporting policy, include a fimds, human resources, feeder mechanism, monitoring and eval uation.
