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Atikah Adyas; Promotor: Ascobat Gani; Ko-promotor: Azrul Azwar; Penguji: Sudijanto Kamso, Hasbullah Thabrany, Soekidjo Notoatmodjo, Soewarta Kosen, Sudarsono Hardjo Soekarta, Mardiati Nadjib, Prastuti C. Soewondo
D-204
Depok : FKM-UI, 2007
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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Novita Rina Antarsih; Promotor: Besral; Kopromotor: Rima Irwinda, Eka Budiarto; Penguji: Kemal Nazaruddin Siregar, Sutanto Priyo Hastono, Prihatin Oktivasari, Soewarta Koesen, Indra Supradewi, Omo Abdul Majid
Abstrak:
Latar Belakang: Intrauterine Growth Restriction (IUGR) merupakan salah satu penyebab utama morbiditas dan mortalitas perinatal. Deteksi dini di Puskesmas masih menghadapi keterbatasan akses ultrasonografi, variasi kemampuan skrining, dan keterlambatan rujukan. Pemanfaatan Artificial Intelligence Clinical Decision Support System (AI-CDSS) berpotensi mendukung skrining dan pengambilan keputusan rujukan secara lebih konsisten. Tujuan: Mengembangkan model Artificial Intelligence (AI) berbasis data antenatal untuk skrining risiko IUGR di Puskesmas, menilai efikasi diagnostiknya dibandingkan metode konvensional, serta mengevaluasi dampak potensial implementasi sistem AI terintegrasi telehealth terhadap deteksi dini dan ketepatan rujukan IUGR di Puskesmas. Metode: Penelitian pengembangan dengan pendekatan multiphase mixed-methods ini dilakukan dalam lima tahap, yaitu analisis kebutuhan sistem, pengembangan model AI, evaluasi usability dan feasibility, uji efikasi diagnostik, serta evaluasi dampak potensial implementasi (simulated effectiveness). Pengembangan model menggunakan 1.761 data longitudinal dari 571 ibu hamil. Uji efikasi dan evaluasi dampak potensial melibatkan 604 ibu hamil di empat Puskesmas. Hasil: Model hybrid yang menggabungkan data maternal, tinggi fundus uteri, dan biometrik janin dari USG non-citra menunjukkan performa terbaik. AI-CDSS mencapai sensitivitas 100% (95%CI: 0,95–1,00), spesifisitas 87% (95%CI: 0,84–0,90), akurasi 89%, dan AUC 0,935 (95%CI: 0,916–0,954; p<0,001). Pada evaluasi dampak potensial implementasi, penggunaan sistem meningkatkan deteksi risiko IUGR dari 14,7% menjadi 25,8% (p=0,001) dan mengidentifikasi tambahan 67 kasus yang sebelumnya tidak terdeteksi. Kesimpulan: AI-CDSS VITA-Scan menunjukkan performa yang baik sebagai alat bantu skrining risiko IUGR di Puskesmas. Integrasi AI, aturan klinis, dan telehealth berpotensi meningkatkan deteksi dini serta mendukung ketepatan rujukan maternal.
Background: Intrauterine Growth Restriction (IUGR) remains a major contributor to perinatal morbidity and mortality. Early detection in Indonesian primary healthcare centers (Puskesmas) is often challenged by limited access to ultrasonography, variations in screening practices, and delayed referral decisions. Artificial Intelligence Clinical Decision Support Systems (AI-CDSS) may help improve screening consistency and support timely referral decisions. Objective: To develop an artificial intelligence (AI)-based antenatal screening model for identifying the risk of IUGR in primary healthcare centers, assess its diagnostic efficacy compared with conventional approaches, and evaluate the potential impact of an AI-CDSS integrated with telehealth on early detection and referral accuracy. Methods: This multiphase mixed-methods study was conducted in five stages: needs assessment, AI model development, usability and feasibility evaluation, diagnostic efficacy testing, and simulated effectiveness evaluation. Model development used 1,761 longitudinal records from 571 pregnant women. The model integrated maternal characteristics, symphysis-fundal height measurements, and non-image ultrasound fetal biometric parameters using a hybrid approach that combined machine learning and clinical rules. Diagnostic efficacy and simulated effectiveness were evaluated among 604 pregnant women from four Puskesmas. Results: The hybrid model demonstrated the best performance. The AI-CDSS achieved a sensitivity of 100% (95% CI: 0.95–1.00), specificity of 87% (95% CI: 0.84–0.90), accuracy of 89%, and an AUC of 0.935 (95% CI: 0.916–0.954; p<0.001). During simulated effectiveness evaluation, the system increased IUGR risk detection from 14.7% to 25.8% (p=0.001) and identified 67 additional cases that were not detected through routine practice. Conclusions: VITA-Scan AI-CDSS demonstrated good performance as a decision-support tool for IUGR risk screening in primary healthcare centers. The integration of AI, clinical rules, and telehealth has the potential to improve early detection and support more appropriate maternal referral decisions.
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D-639
Depok : FKM-UI, 2026
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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Surya Ede Darmawan; Promotor: Purnawan Junadi; Ko Promotor: Adang Bachtiar, Mardiati Nadjib; Penguji: Anhari Achadi, Amal C. Sjaaf, Soekidjo Notoatmodjo, Trihono, Nana Mulyana, Kodrat Pramudho
D-251
Depok : FKM-UI, 2011
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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Yaslis Ilyas; Promotor: Soekidjo Notoatmodjo; Kopromotor: Suprijanto Rijadi, Purnawan Junadi; Penguji: Azrul Azwar, Aris Ananta, Anhari Achadi, Sudarto Ronoatmodjo, Soewarta Kosen, Amal Chalik Sjaaf
D-26
Depok : FKM-UI, 1998
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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Jumhati, Siti; Promotor: Sabarinah; Kopromotor: Kemal Nazaruddin Siregar; Penguji: Agustin Kusumayati, Artha Prabawa, Kemal Nazaruddin Siregar, Sabarinah, Sudarto Ronoatmodjo, Maryati, Arietta Pusponegoro, Ade Jubaedah, Trihono
Abstrak:
Hasil Long Form sensus penduduk 2020 (LF SP 2020) AKI di Indonesia sebesar 189 per 100.000 KH, sementara AKI di Provinsi Banten sebesar 127/100.000 KH. Penurunan angka kematian ibu dari hasil LF SP2020 mencapai 45 persen. Meskipun AKI pada tahun 2020 sudah ada penurunan dibanding dengan AKI pada tahun 2015, akan tetapi masih perlu usaha keras untuk mencapai target SDGs. Deteksi dini preeklampsi pada ibu hamil adalah bagian dari asuhan antenatal yang merupakan salah satu kunci intervensi utama untuk menurunkan angka kematian ibu dan mencapai target Sustainable Development Goals (SDGs) yang telah diterapkan diberbagai Negara. Tujuan penelitian ini untuk menguatkan keaktifan bidan dan kader Kesehatan di Puskesmas dalam mempengaruhi ibu hamil melakukan deteksi dini preeklampsia menggunakan mHealth. Metode penelitian ini menggunakan desain Mixs Methods Exploratory Sequential. Penelitian kualitatif dilakukan untuk pengembangan intervensi. Informan pada penelitian kualitatif terdiri dari Dinas Kesehatan, Ibu hamil, keluarga ibu hamil, bidan Puskesmas, kader kesehatan dan masyarakat. Penelitian kuantitatif menggunakan desain Quasi eksperimental. Penelitian dilakukan di Kecamatan Angsana, Kaduhejo (intervensi) dan Cikupa Pandeglang, Cadasari (kontrol) di Kabupaten Pandeglang Provinsi Banten. Populasi penelitian seluruh ibu hamil umur 15-49 tahun, di Kabupaten Pandeglang. Sampel penelitian yaitu Ibu hamil umur 15-49 tahun, usia kehamilan ≤ 34 minggu yang memenuhi kriteria inklusi dan eksklusi, besar sampel 100 orang. Teknik pengambilan sampel dengan Purposive sampling. Pada kelompok intervensi dilakukan edukasi menggunakan mHealth untuk penguatan pemeriksaan deteksi dini preeklampsi pada ibu hamil oleh bidan dan kader, pada kelompok kontrol tidak dilakukan intervensi. Analisa data dengan menggunakan analisa univariat, bivariat, multivariat: Risk Ratio (RR), Attributable Risk (AR), AR% (absolute) dan Difference in Difference (DiD). Hasil studi kualitatif Ibu hamil mempersepsikan bahwa tidak sulit untuk mengakses pelayanan kesehatan terkait deteksi dini preeklampsi, dan orang tua adalah orang yang paling banyak memberikan saran dan masukan selama kehamilan. Meskipun demikian mayoritas ibu hamil masih belum melakukan pemeriksaan deteksi dini preeklampsi dengan baik, dan masih ada beberapa ibu hamil yang tidak ingin memeriksakan kehamilannya ke bidan maupun ke dokter kandungan. Hasil studi kuantitatif variabel yang paling dominan mempengaruhi perilaku deteksi dini preeklampsi adalah Intervensi bidan dan kader kesehatan, sikap dan dukungan tenaga kesehatan terhadap deteksi dini preeklampsi dengan nilai (p-value < 0,05). Intervensi edukasi menggunakan mHealth oleh bidan dan kader secara signifikan (p value < 0,05) memberikan dampak meningkatkan perilaku well detection terhadap preeklampsi pada ibu hamil sebesar 47,1 % (AR) dan 38% (DiD).

The results of the Long Form Population Census 2020 (LF SP 2020) showed that the MMR in Indonesia was 189 per 100,000 KH, while the MMR in Banten Province was 127/100,000 KH. The reduction in maternal mortality from the LF SP2020 results reached 45 per cent. Although the MMR in 2020 has decreased compared to the MMR in 2015, it still needs hard efforts to achieve the SDGs target. Early detection of preeclampsia in pregnant women is part of antenatal care which is one of the key interventions to reduce maternal mortality and achieve Sustainable Development Goals (SDGs) targets that have been implemented in various countries. The purpose of this study was to strengthen the activeness of midwives at Puskesmas in influencing pregnant women to do early detection of preeclampsia using mHealth. This research method uses Mixs Methods Exploratory Sequential design. Qualitative research was conducted for intervention development. Informants in qualitative research consisted of the Health Office, pregnant women, families of pregnant women, Puskesmas midwives, health cadres and the community. Quantitative research used a Quasi-experimental design. The study was conducted in Angsana, Kadu Hejo (intervention) and Cikupa, Cadasari (control) sub-districts in Pandeglang Regency, Banten Province. The study population was all pregnant women aged 15-49 years, in Pandeglang Regency. The study sample was pregnant women aged 15-49 years, gestational age ≤ 34 weeks who met the inclusion and exclusion criteria, a sample size of 100 people. Purposive sampling technique. In the intervention group, education using mHealth was carried out to strengthen the early detection of preeclampsia in pregnant women by midwives and cadres, in the control group no intervention was carried out. Data analysis using univariate, bivariate, multivariate: Risk Ratio (RR), Attributable Risk (AR), AR% (absolute) and Difference in Difference (DiD). Qualitative study results Pregnant women perceive that it is not difficult to access health services related to early detection of preeclampsia, and parents are the people who provide the most advice and input during pregnancy. However, the majority of pregnant women still do not perform early detection of preeclampsia properly, and there are still some pregnant women who do not want to check their pregnancy with a midwife or obstetrician. The results of the quantitative study of the most dominant variable affecting the early detection of preeclampsia was the Educational interventions using mHealth by midwives and , and health worker support. Educational interventions using mHealth by midwives and CHWs significantly (p value <0.05) had an impact on improving the early detection behaviour of preeclampsia in pregnant women by 47,1% (AR) and 38% (DiD).
 
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D-536
Depok : FKM UI, 2024
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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Setya Haksama; Promotor: Amal C. Syaaf, ; Ko-Promotor: Purnawan Junadi, Adang Bachtiar; Penguji: Anhari Achadi, Sudarti Kresno, Dian Ayubi, Boy Subirosa Sabarguna, Delina Hasan
D-250
Depok : FKM UI, 2011
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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Solha Elrifda; Promotor: Anhari Achadi; Ko Promotor: Sudijanto Kamso, Harimat Hendrawan; Penguji: Purnawan Junadi, Kusharisupeni, Adang Bachtiar, Tri Krianto, Soewarta Kosen
D-309
Depok : FKM-UI, 2015
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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Ruwayda; Promotor: Sutanto Priyo Hastono; Kopromotor: Evi Martha, Kemal Nazaruddin Siregar; Penguji: Anhari Achadi, Rita Damayanti, Ade Jubaedah, Muldiasman, Dwi Tyastuti
Abstrak:

ABSTRAK

Latar Belakang: Tingginya angka kematian ibu dan neonatus di Indonesia dipengaruhi oleh berbagai faktor, termasuk kualitas pelayanan kesehatan ibu dan anak (KIA) yang belum mencapai target. Kinerja bidan desa, sebagai ujung tombak pelayanan, dipandang sebagai salah satu faktor krusial yang dapat ditingkatkan melalui supervisi dari bidan koordinator puskesmas. Meskipun demikian, data menunjukkan pelaksanaan supervisi fasilitatif KIA di provinsi Jambi pada tahun 2022 dan 2023 baru mencapai 10.86% dan 17.38% dari target 90%. Khususnya di kabupaten Muaro Jambi, capaiannya lebih rendah lagi, yaitu 11.64% (2022) dan 15.07% (2023). Kesenjangan ini menunjukkan perlunya intervensi strategis untuk meningkatkan kualitas supervisi demi mengoptimalkan kinerja bidan dalam pelayanan KIA.
Tujuan: Mengetahui pengaruh model integrasi midwifery opinion leader dan supervisi fasilitatif terhadap kinerja bidan dan dampaknya pada cakupan pelayanan kesehatan ibu dan anak di Provinsi Jambi tahun 2025.
Metode Penelitian: Penelitian ini merupakan penelitian mixed methods exploratory sequential design terdiri dari 3 tahap yaitu tahap I diawali scoping review, studi pendahuluan dan uji coba instrumen dilanjutkan identifikasi kebutuhan model menggunakan metode kualitatif dengan desain phenomenology. Tahap II meliputi pengembangan model, panel expert, pelatihan dan uji coba model. Tahap III dilakukan uji model terhadap kinerja bidan dengan indikator standar kompetensi kinerja (SKK) dan cakupan pelayanan KIA dengan penelitian quasi experiment pretest-posttest with control designs. Populasi adalah seluruh bidan desa/pustu di provinsi Jambi. Sampel yaitu kelompok intervensi sebanyak 60 responden (di kabupaten Muaro Jambi) dilakukan intervensi model integrasi MOL dan supervisi fasilitatif, sedangkan kelompok kontrol 60 responden (di kota Jambi) dilakukan hanya supervisi fasilitatif. Waktu penelitian pada bulan Mei 2024 hingga Agustus 2025, analisis data dengan univariat, bivariat dan multivariat (Difference in Difference).
Hasil: Berdasarkan identifikasi kebutuhan ditemukan subtema: kinerja bidan, kebutuhan supervisi dan model supervisi. Selanjutnya dilakukan pengembangan model supervisi dengan pendekatan teori COM-B, supportif supervision, midwifery leadership dan coaching sehingga diperoleh model midwifery opinion leader (MOL) yang dapat diintegrasikan dengan program supervisi fasilitatif KIA puskesmas. Hasil uji penerimaan model diperoleh hasil skor tertinggi yaitu sikap terhadap penggunaan rata-rata 4.9 dan terendah yaitu persepsi manfaat dengan skor 4.71. Hasil analisis diff in diff diketahui pada 2 kelompok sebelum dan sesudah intervensi terhadap skor standar kompetensi kerja: penataan pelayanan 1.36(0.24-1.60), asuhan bayi baru lahir 2.36(0.75-3.12) pemeriksaan kehamilan 1.33(0.48-1.82), pemeriksaan ibu bersalin 1.93(1.72-3.65) dan asuhan ibu nifas 1.43(0.30-1.74).Uji dampak model terhadap cakupan KIA yaitu: kunjungan ibu hamil ke-4 (K4)18.25(3.83-22.08), persalinan nakes (PN) 15.53(3.47-19.00), kunjungan nifas (KNF) 15.59(3.41-19.00), kunjungan neonatal lengkap (KNL) 14.35(9.97-24.33), kunjungan bayi (KBY) 19.08 (7.26-26.35) dan kunjungan balita (KBAL) 5.81 (16.14-21.95).
Kesimpulan dan Saran: Model integrasi Midwifery Opinion Leader (MOL) dan supervisi fasilitatif berpengaruh dalam meningkatkan kinerja bidan dalam pelayanan KIA. Disarankan mempertimbangkan model ini dalam kegiatan program supervisi kesehatan ibu dan anak di Puskesmas.

ABSTRACT


Background: The high maternal and neonatal mortality rates in Indonesia are influenced by various factors, including the quality of maternal and child health (MCH) services, which have not yet reached their targets. The performance of village midwives, as the frontline of service delivery, is seen as a crucial factor that can be improved through supervision by health center coordinator midwives. However, data shows that the implementation of facilitative MCH supervision in Jambi province in 2022 and 2023 has only reached 10.86% and 17.38% of the 90% target. In Muaro Jambi district, in particular, the achievement was even lower, at 11.64% (2022) and 15.07% (2023). This gap indicates the need for strategic interventions to improve the quality of supervision in order to optimize the performance of midwives in MCH services.
Objective: To determine the effect of the midwifery opinion leader integration model and facilitative supervision on midwives' performance and its impact on the coverage of maternal and child health services in Jambi Province in 2025.
Research Method: This research is a mixed methods exploratory sequential design consisting of 3 stages, namely stage I, which begins with a scoping review, preliminary study, and instrument testing, followed by the identification of model requirements using a qualitative method with a phenomenology design. Stage II includes model development, expert panel, training, and model testing. Phase III involved testing the model on midwives' performance using standard competency performance (SKK) indicators and MCH service coverage using a quasi-experimental pretest-posttest with control designs. The population consisted of all village midwives/health workers in Jambi Province. The sample consisted of an intervention group of 60 respondents (in Muaro Jambi district) who underwent the MOL integration model intervention and facilitative supervision, while the control group of 60 respondents (in Jambi city) only underwent facilitative supervision. The research period was from May 2024 to August 2025, with data analysis using univariate, bivariate, and multivariate (Difference in Difference) methods.
Results: Based on the identification of needs, the following sub-themes were found: midwife performance, supervision needs, and supervision models. Subsequently, a supervision model was developed using the COM-B theory, supportive supervision, midwifery leadership, and coaching approaches, resulting in a midwifery opinion leader (MOL) model that can be integrated with the KIA puskesmas facilitative supervision program. The model acceptance test results showed the highest score for attitude toward use, with an average of 4.9, and the lowest score for perceived benefits, with a score of 4.71. The results of the diff in diff analysis showed that in the two groups before and after the intervention, the standard work competency scores were: service management 1.36 (0.24-1.60), newborn care 2.36 (0.75-3.12), pregnancy check-ups 1.33 (0.48-1.82), maternity check-ups 1.93 (1.72-3.65), and postpartum care 1.43 (0.30-1.74). The model's impact on MCH coverage was as follows: fourth antenatal visit (K4) 18.25 (3.83-22.08), skilled birth attendance (PN) 15.53 (3.47-19.00), postnatal visit (KNF) 15.59 (3.41-19. 00), complete neonatal visits (KNL) 14.35 (9.97-24.33), infant visits (KBY) 19.08 (7.26-26.35), and toddler visits (KBAL) 5.81 (16.14-21.95).
Conclusion and Recommendations: The integration model of Midwifery Opinion Leader (MOL) and facilitative supervision has an impact on improving midwives' performance in maternal and child health services. It is recommended to consider this model in maternal and child health supervision program activities at health centers.

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D-603
Depok : FKM-UI, 2025
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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Maulidiya Muliawati; Pembimbing: Wiku Bakti Bawono Adisasmito; Penguji: Ede Surya Darmawan, Mira Miranti Puspitasari
Abstrak: Pelaksanaan SIK terintegrasi di Indonesia masih belum sepenuhnya terlaksanasecara optimal karena masih adanya fragmentasi pelaporan data dari daerahmenuju pusat. Skripsi ini membahas gambaran SIMPUS sebagai salah satu bentukSIK terintegrasi untuk mendukung manajemen pelayanan kesehatan melalui studikasus pelaksanaan di Kota Depok. Penelitian ini merupakan penelitian kualitatifdengan studi desktriptif menggunakan pendekatan 7 komponen dari National e-Health Strategy Toolkit milik WHO serta proses dalam manajemen pelayanankesehatan. Penelitian ini menggunakan metode wawancara mendalam danobservasi untuk mendapatkan data primer, serta didukung oleh telaah dokumenuntuk mendapatkan data sekunder. Informan dalam penelitian ini adalah 1 orangpenanggung jawab pelaksanaan SIMPUS di Dinkes Kota Depok serta 11 orangpenanggung jawab pelaksanaan SIMPUS di UPT Puskesmas Kota Depok yangdidapatkan dari teknik purposive sampling. Hasil penelitian didapatkan bahwaberdasarkan National e-Health Strategy Toolkit dari WHO, aplikasi SIMPUSbelum cukup optimal dalam pelaksanaannya sebagai bentuk SIK Terintegrasi diKota Depok. Hal tersebut dapat dilihat dari infrastruktur jaringan dan sistem yangmasih sering eror, kompetensi tenaga kerja yang masih belum seragam dan sesuai,hingga belum adanya pemanfaatan data untuk pengambilan keputusan dankebijakan. Selain itu, analisis dengan manajemen pelayanan kesehatanmenunjukkan SIMPUS masih membutuhkan optimalisasi di setiap tahapanprosesnya, yaitu planning (perencanaan), organizing (pengorganisasian),actuating (implementasi), evaluation (evaluasi), dan controlling (pengawasan danpengendalian).
Kata Kunci: SIK terintegrasi, SIMPUS, National e-Health Strategy Toolkit, aplikasi kesehatan,Interoperabilitas.
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S-10253
Depok : FKM UI, 2020
S1 - Skripsi   Pusat Informasi Kesehatan Masyarakat
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Harimat Hendarwan; Promotor; Amal C. Sjaaf; Kopromotor: Adang Bachtiar, Anhari Achadi; Penguji: Purnawan Junadi, Soewarta Kosen, Dian Ayubi, Delina Hasan
D-246
Depok : FKM-UI, 2011
S3 - Disertasi   Pusat Informasi Kesehatan Masyarakat
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:: Pengguna : Pusat Informasi Kesehatan Masyarakat
Library Automation and Digital Archive