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All Journal Jurnal Penelitian dan Evaluasi Pendidikan Jurnal Ilmiah Farmasi e-Journal Pustaka Kesehatan Media Farmasi : Jurnal Ilmu Farmasi (Journal Of Pharmaceutical Science) Jurnal Teknologi Informasi dan Ilmu Komputer Global Medical and Health Communication Jurnal Farmasi Sains dan Komunitas JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Farmasi Galenika (Galenika Journal of Pharmacy) Warta Pengabdian JURNAL FARMASIMED (JFM) Building of Informatics, Technology and Science Abdimasku : Jurnal Pengabdian Masyarakat Community Development Journal: Jurnal Pengabdian Masyarakat Charity : Jurnal Pengabdian Masyarakat SOCIAL CLINICAL PHARMACY INDONESIA JOURNAL Farmasis: Jurnal Sains Farmasi Jurnal Pengabdian Masyarakat Akademisi eProceedings of Engineering Jurnal Farmasi Indonesia Journal of Agropharmacy
Ema Rachmawati
Fakultas Farmasi Universitas Jember
Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Social Sciences

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Pengenalan Jalan Berlubang Berbasis Vision Menggunakan Pyramid Histogram Of Oriented Gradients Fitriansyah, Ahmad Habib; Rachmawati, Ema; Risnandar, Risnandar
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 3: Juni 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023106820

Abstract

Lubang, sejenis kerusakan jalan, dapat merusak kendaraan dan berdampak negatif pada keamanan mengemudi dari pengemudi. Bahkan, dalam kasus yang parah dapat menyebabkan kecelakaan lalu lintas. Manajemen jalan berlubang yang efisien dan preventif di lingkungan jalan yang kompleks memainkan peran penting dalam mengamankan keselamatan pengemudi. Hal ini juga diharapkan dapat memberikan kontribusi terhadap pencegahan kecelakaan lalu lintas dan kelancaran arus lalu lintas. Di masa lalu, deteksi lubang terutama dilakukan melalui inspeksi visual oleh ahli manusia. Baru-baru ini, metode deteksi lubang otomatis menerapkan berbagai teknologi yang menyatukan teknologi dasar seperti sensor dan pemrosesan sinyal. Pada artikel ini, metode berbasis pengolahan citra dan pembelajaran mesin diaplikasikan untuk mengenali lubang di jalan. Penelitian ini menghasilkan model dari bentuk lubang dengan memanfaatkan ciri bentuk yang diekstraksi dari Pyramid Histogram of Oriented Gradients (PHOG). Untuk metode klasifikasi, peneliti menggunakan Support Vector Machine (SVM) dengan hasil terbaik diperoleh pada penggunaan kernel polynomial. Sistem pengenalan jalan berlubang yang diusulkan mampu menunjukkan hasil performa yang sangat baik, yaitu akurasi sebesar 94,45%, precision sebesar 96,13% recall sebesar 95,77%, dan F1-score sebesar 95,95%. AbstractPotholes on roads can damage vehicles and endanger drivers, potentially leading to accidents. Preventative management of potholes is crucial for driver safety and efficient traffic flow. Traditional methods of pothole detection relied on visual inspection, but automatic methods have been developed using sensors and signal processing. This article presents a new approach using image processing and machine learning to identify potholes on roads. The proposed system uses shape features extracted from Pyramid Histogram of Oriented Gradients (PHOG) and a Support Vector Machine (SVM) with polynomial kernels for classification. The system achieves high accuracy, precision, recall, and F1-Score, with an accuracy of 94.45%, precision of 96.130%, recall of 95.77%, and F1-Score of 95.950%.
Prediksi Penuaan Wajah Manusia Berbasis Generative Adversarial Network Elfitri, Beladina; Rachmawati, Ema; Agung Budi Wirayuda, Tjokorda
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 11 No 1: Februari 2024
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.20241116870

Abstract

Karena struktur wajah manusia yang berbeda-beda, wajah merupakan salah satu ciri yang digunakan untuk mengidentifikasi seseorang. Wajah sering digunakan sebagai pengenal biometrik. Namun, seiring bertambahnya usia manusia, wajah mereka bisa berubah karena faktor lingkungan dan gaya hidup. Karena efek penuaan pada wajah, komputer tidak dapat mengenali kemiripan antara citra wajah dari orang yang sama pada usia yang berbeda. Penelitian pengenalan wajah biasanya menggunakan data berpasangan (paired data), yang sangat sulit didapat. Di sisi lain, volume data yang tidak berpasangan (unpaired data) sangat besar dan mudah diakses. Sebaliknya, keterbatasan data berpasangan memotivasi para peneliti untuk mengembangkan teknik sintesis citra yang tidak bergantung pada data berpasangan. Tanpa perlu data berpasangan, metode CycleGAN mampu menghasilkan citra sintetik yang lebih realistis dengan resolusi lebih tinggi. Hal itulah yang memotivasi penelitian ini dalam penggunaan data tidak berpasangan untuk memprediksi penuaan wajah manusia menggunakan CycleGAN. Pada penelitian ini, digunakan citra dari dataset UTKFace yang terdiri atas citra wajah berbagai usia. Untuk keperluan eksperimen, citra dari UTKFace dibagi ke dalam dua ranah, yaitu citra wajah usia muda dan citra wajah usia tua, untuk keperluan sistem penuaan wajah yang dibangun. Dengan demikian, citra wajah berusia muda tidak memiliki pasangan pada citra wajah usia tua (unpaired data). Dengan nilai Frechet Inception Distance (FID) = 2,24, hasil percobaan menunjukkan bahwa metode yang digunakan mampu mencapai kinerja yang sangat baik pada sistem penuaan wajah yang dibangun.
Analisis Minimalisasi Biaya Penggunaan Antiplatelet Pada Pasien Stroke Infark Rawat Inap Wicaksono, Ayssa; Rachmawati, Ema; Norcahyanti, Ika; Aryani, Dhita Evi; Machlaurin, Afifah
Journal of Agropharmacy Vol. 1 No. 1 (2024)
Publisher : Faculty of Pharmacy, University of Jember

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Abstract

Antiplatelets are crucial medications in the treatment of ischemic stroke patients. The management of stroke cases in Indonesia incurs substantial costs, reaching Rp. 3.2 billion annually. This study conducted a simple pharmacoeconomic research using Cost Minimization Analysis (CMA) method, utilizing medical records and patient financing data of ischemic stroke inpatients at RSUD Gambiran, Kediri City from January to December 2022. The study adopts a hospital perspective with the same outcome of patient recovery. Out of 659 stroke patients, 100 eligible participants, predominantly male aged 46-65 years with Diabetes Mellitus as the most common comorbidity, were included. Based on antiplatelet therapy profiles, the majority received a combination of clopidogrel and aspirin (65%), while 35% received clopidogrel monotherapy. The largest cost component was service cost amounting to Rp 2,898,606 (59.37%). According to CMA analysis, combination therapy showed cost-saving benefits compared to monotherapy in drug and medical equipment, laboratory, service, and total overall costs. Thus, for ischemic stroke patients with the same outcome of recovery, combination therapy of clopidogrel and aspirin isrecommended over clopidogrel monotherapy.
Evaluasi Penggunaan Antibiotik pada Pasien ISPA Non-pneumonia di Puskesmas Senduro Kabupaten Lumajang Tahun 2019 Pratiwi, Permata Sari; Rachmawati, Ema; Rachmawati, Sinta; Aryani, Dhita Evi; Norcahyanti, Ika; Machlaurin, Afifah; Muhammad Hilmi Afthoni
Journal of Agropharmacy Vol. 1 No. 2 (2024)
Publisher : Faculty of Pharmacy, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/joa.v1i2.1330

Abstract

Acute Respiratory Infection (ARI) is an infectious disease of the upper and lower respiratory tract. Non-pneumonic ARI is mostly caused by viral infections so symptomatic therapy can be given, but it can also be caused by bacterial infections so antibiotic therapy is needed. Unwise use of antibiotics can increase bacterial resistance, thereby increasing morbidity and mortality rates. Regular evaluations need to be carried out to reduce the unwise use of antibiotics. The evaluation method that can be used is a quantitative method (ATC/DDD) to determine trends in antibiotic use. This research was conducted on 278 outpatient non-pneumonic ARI patients at the Senduro Lumajang Community Health Center in 2019, with the aim of knowing patient characteristics, antibiotic use profile, and description of antibiotic use using the ATC/DDD method. The results showed that female patients (n=154; 55.4%), were more dominant than male (n=124; 44.6%), patients with the highest age range being 36-45 years (n=70; 25, 2%), the highest diagnosis of ARI was other acute infections of the upper respiratory tract (J06) (n=147; 52.9%), the most commonly used antibiotic was amoxicillin (n=227; 81.6%) and the most rarely used was cefadroxil (n=13; 4.7%). Based on the evaluation results using the ATC/DDD method, it shows that amoxicillin is the antibiotic with the highest DDD value of 7.5 DDD/1000 patients/day and the antibiotic levofloxacin with the lowest DDD value of 0.3 DDD/1000 patients/day.
Evaluasi Perencanaan dan Pengadaan Obat dengan Dana JKN di Puskesmas Rambipuji Jember Norcahyanti, Ika; Firandi, Adelia; Ramadhani, Nuril Izzati Farihatur; Rachmawati, Sinta; Rachmawati, Ema; Aryani, Dhita Evi; Wardhani, Firdha Aprillia; Kusumaningrum , Yunita Dyah
Journal of Agropharmacy Vol. 1 No. 3 (2024)
Publisher : Faculty of Pharmacy, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/joa.v1i3.1811

Abstract

Public Health Center is a health facility that organizes drug management activities, including planning and procurement activities. Evaluation needs to assess the success of achieving the objectives and results of the action. Indicators that can use are efficiency indicators published by the Ministry of Health of the Republic of Indonesia and efficiency indicators developed by Pudjaningsih. Rambipuji Public Health Center with spending funds for the most significant drug procurement in Jember Regency in 2020. Therefore, it is necessary to evaluate the results that can improve the quality of service in the next period. This research aims to determine the results of the evaluation of drug planning and procurement with JKN funds at Rambipuji Public Health Center for 2020. This research is descriptive, primary data through interview results. Secondary data includes total funds available, drug procurement funds, Drug Usage Reports, and Drug Demand Sheets for drugs purchased through JKN funds and stock cards. The data is analyzed descriptively, presented in the form of tables supported by interview results. The results showed that the Government of Indonesia had governed drug planning and procurement activities with JKN funds. The percentage indicator of available funds compared to the general funds needed is 114.26%. The percentage indicator of drug procurement fund allocation is 3.46%. Results on percentage indicator procurement conformity with the reality of the use of each drug item amounted to 133.33% and on the procurement frequency indicator of each drug item once a year. Through this research, it can be concluded that the evaluation results on indicators of the efficiency of drug planning and procurement activities at Rambipuji Public Health Center have not been by established standards. This matter was influenced by several factors, including a decrease in the number of patient visits due to the COVID-19 pandemic, changes in the organizational structure in the Jember Health Office that resulted in the frequency of procurement activities only once throughout 2020, and the absence of government regulations that regulate in more detail about the percentage of JKN funds allowed for drug procurement activities.
Evaluasi Penggunaan Antibiotik pada Pasien ISPA non Pneumonia Rawat Jalan dengan pendekatan Drug Utilization 90% Rachmawati, Ema; Norcahyanti, Ika; Aryani, Dhita Evi; Machlaurin, Afifah; Kurniawan, Eka Cahya
Journal of Agropharmacy Vol. 2 No. 1 (2025)
Publisher : Faculty of Pharmacy, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Acute respiratory infections (ARI) are infections most commonly caused by viruses, and antibiotics are not always necessary. However, antibiotics are still frequently used needlessly in ARI patients. Unreasonably using antibiotics can affect the likelihood of adverse medication reactions, raise medical expenses, and lead to antibiotic resistance. Regular assessments are required to prevent the overuse of antibiotics. This surveillance study uses retrospective and cross-sectional data to monitor antibiotic use. We measured the amount of antibiotic use using the DDD method in combination with DU 90%. Outpatient non-pneumonia ARI patients at the Teja Health Center in the Pamekasan Regency in 2020 served as the study's sample. The study's samples consisted of 193 adult non-pneumonia ARI patients. The kind and quantity of antibiotics used were gathered from patient medical records. The daily consumption of each antibiotic was calculated in DDD/1000 inhabitants/day, then grouped into the DU 90% segment. Six types of antibiotics were used for the therapy of non-pneumonia ARI patients: amoxicillin, erythromycin, co-trimoxazole, chloramphenicol, cefadroxil, and ciprofloxacin. The most widely used antibiotic is co-trimoxazole, valued at 4.71 DDD/1000 inhabitants per day. Two antibiotics are included in the 90% DU segment: co-trimoxazole and amoxicillin. This shows that the selection of antibiotics in ARI cases is increasingly specific. However, the use of co-trimoxazole in the therapy of non-pneumonia ARI needs to be further evaluated to assess the accuracy of drug prescription. This is because co-trimoxazole is not included in one of the antibiotic choices in the therapy management guidelines.
Classifying Gender Based on Face Images Using Vision Transformer Tahyudin, Ganjar Gingin; Sulistiyo, Mahmud Dwi; Arzaki, Muhammad; Rachmawati, Ema
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.1923

Abstract

Due to various factors that cause visual alterations in the collected facial images, gender classification based on image processing continues to be a performance challenge for classifier models. The Vision Transformer model is used in this study to suggest a technique for identifying a person’s gender from their face images. This study investigates how well a facial image-based model can distinguish between male and female genders. It also investigates the rarely discussed performance on the variation and complexity of data caused by differences in racial and age groups. We trained on the AFAD dataset and then carried out same-dataset and cross-dataset evaluations, the latter of which considers the UTKFace dataset.  From the experiments and analysis in the same-dataset evaluation, the highest validation accuracy of  happens for the image of size  pixels with eight patches. In comparison, the highest testing accuracy of  occurs for the image of size  pixels with  patches. Moreover, the experiments and analysis in the cross-dataset evaluation show that the model works optimally for the image size  pixels with  patches, with the value of the model’s accuracy, precision, recall, and F1-score being , , , and , respectively. Furthermore, the misclassification analysis shows that the model works optimally in classifying the gender of people between 21-70 years old. The findings of this study can serve as a baseline for conducting further analysis on the effectiveness of gender classifier models considering various physical factors.
PENINGKATAN PENGETAHUAN DAGUSIBU (DAPATKAN, GUNAKAN, SIMPAN, BUANG) OBAT DI DESA JEMBER KIDUL Holidah, Diana; Firandi, Adelia; Kusumaningrum, Yunita Dyah; Rachmawati, Ema
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 6 No. 2 (2025): Volume 6 No. 2 Tahun 2025
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v6i2.44095

Abstract

Kesehatan merupakan kondisi fisik dan mental yang bebas dari penyakit dan dapat meningkatkan kesejahteraaan masyarakat. Obat adalah bahan yang digunakan untuk mencegah, menyembuhkan, dan meningkatkan kesehatan, namun, obat juga dapat bersifat toksik bila tidak digunakan secara rasional. Diketahui bahwa lebih dari 60% masyarakat Indonesia melakukan pengobatan sendiri atau swamedikasi, dan diantaranya, ada yang menyimpan obat keras tanpa resep termasuk antibiotik, menyimpan obat kadaluarsa, dan membuang obat dengan cara yang salah. Hal ini disebabkan karena kurangnya pemahaman dan kesadaran masyarakat terkait cara mendapatkan, menggunakan, menyimpan, dan membuang obat dengan benar. Apoteker memiliki peran dalam meningkatkan derajat kesehatan masyarakat melalui berbagai pelayanan kefarmasian, salah satunya melalui DAGUSIBU (Dapatkan, Gunakan, Simpan, Buang) Obat. Ibu adalah pilar kesehatan yang berperan penting dalam mengatur berbagai hal dalam keluarga, termasuk penyediaan dan pengelolaan obat-obatan dirumah, Oleh karena itu, dilakukan penyuluhan terkait DAGUSIBU secara lisan dan tertulis melalui power point dan leaflet pada ibu-ibu kader PKK di Desa Jember Kidul, Kecamatan Kaliwates, Kabupaten Jember. Evaluasi kegiatan didapatkan terdapat peningkatan pengetahuan peserta sebanyak 27.5% melalui hasil pre-test dan post-test. Oleh karena itu, tema ini layak diadakan secara rutin dan diperluas cakupannya ke wilayah lain untuk meningkatkan pemahaman dan kesadaran individu sehingga dapat mencegah penyalahgunaan obat dan permasalahan kesehatan lainnya
Deteksi Objek Makhluk Hidup dalam Filum Arthropoda Menggunakan YOLOv3 Safarin, Arva Adwitya; Rachmawati, Ema; Kosala, Gamma
eProceedings of Engineering Vol. 10 No. 2 (2023): April 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak-Makhluk hidup yang berasal dari filum Arthropoda merupakan makhluk hidup yang memiliki beragam karakteristik. Karakteristik tersebut bisa dibedakan dengan melihat ordo dari makhluk hidup tersebut. Beberapa jenis makhluk hidup yang ada dalam filum Arthropoda merupakan makhluk sosial. Oleh karena itu, mereka sering ditemukan berada di lokasi yang sama dan berkerumun. Selain itu, sebagian besar spesies yang ada dalam filum Arthropoda memiliki ukuran tubuh yang kecil. Pada tugas akhir ini, metode yang diajukan adalah YOLOv3. YOLOv3 merupakan metode deteksi objek yang memiliki beberapa pembaruan yang memungkinkan metode tersebut lebih mudah mendeteksi objek yang berkerumun dan memiliki ukuran yang kecil. Untuk mengembangkan sistem pendeteksi makhluk hidup dalam filum Arthropoda menggunakan YOLOv3, terdapat 12.082 data citra yang terbagi dalam 7 (tujuh) kelas untuk melatih model tersebut. Hasil terbaik yang didapatkan saat pengujian memakai 1.544 data uji adalah nilai mAP sebesar 57,6% pada IOU 0,5.Kata kunci - deep learning, deteksi objek, You Only Look Once (YOLO), deteksi makhluk hidup
Deteksi Penggunaan Masker Wajah Menggunakan YOLOv5 Dawami, Hasbi; Rachmawati, Ema; Sulistiyo, Mahmud Dwi
eProceedings of Engineering Vol. 10 No. 2 (2023): April 2023
Publisher : eProceedings of Engineering

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Abstract

Abstrak-Pandemi COVID-19 menyebabkan global krisis kesehatan. Mengenakan masker wajah menjadi salah satu protokol kesehatan yang penting dan diwajibkan oleh pemerintah. Namun, masih banyak masyarakat yang enggan mengenakan masker wajah ketika berada di ruang publik. Oleh karena itu, diperlukan sistem yang dapat mendeteksi penggunaan masker wajah pada manusia yang bertujuan untuk membantu petugas dalam menegakkan kedisiplinan masyarakat dalam rangka menerapkan salah satu protokol kesehatan tersebut. Sistem tersebut dirancang dengan model object detection yang akurat dan efisien untuk mendeteksi penggunaan masker wajah pada manusia. Tugas akhir ini membahas bagaimana membangun sistem untuk mendeteksi masker pada wajah menggunakan metode YOLOv5 menggunakan dataset face mask detection yang asli dan yang telah di augmentasi serta berbagai nilai IoU threshold mulai dari 0,1; 0,2; 0,3; 0,5 dan 0,7. YOLOv5 merupakan versi terbaru dari YOLO sehingga memiliki akurasi yang tinggi, kemampuan mendeteksi small object, serta running speed yang cepat. Hasil terbaik jika menggunakan dataset face mask detection original didapatkan dengan nilai IoU threshold sebesar 0,3 yang memilki nilai mAP pada saat testing semua kelas sebesar 0,876. Jika menggunakan dataset face mask detection yang diaugmentasi hasil terbaik didapatkan dengan nilai IoU threshold sebesar 0,5 yang memiliki nilai mAP pada saat testing untuk semua kelas sebesar 0,849.Kata kunci- object detection, you only look once, akurasi, small object, running speed,IoU threshold 
Co-Authors Afifah, Hanin Agnes Jovanka Agung Budi Wirayuda, Tjokorda Agustina, Nur Azizah Akbar, M Raehan Alhafidz, Bagas Millen Amelya Prastica Rahayu Aliong Anditya Arifianto Anis Rohmawati Antonius Nugraha Widhi Pratama Antonius Nugraha Widhi Pratama Aprianti Putri Sujana Aryani, Dhita Evi Astutik, Amelia Windi Bedy Purnama Dawami, Hasbi Deny Haryadi Dhea Nanda Aliefia Dhita Evi Aryani Diana Holidah Elfitri, Beladina Evi Umayah Ulfa Febryanti Sthevanie Firandi, Adelia Firdaus, Fauzan Firdauz, Salma Salsabila Fitriansyah, Ahmad Habib Fransiska Maria C. Fransiska Maria Christianty Gamma Kosala Hazrina, Inasa Husnun, Khoiriyah Haifa Ika Barokah Suryaningsih Ika Norcahyanti Ika Norcahyanti Ika Puspita Dewi, Ika Puspita Inasa Hazrina Indah Yulia Ningsih Khoirotun Nazilah Kurniawan, Eka Cahya Kusumaningrum , Yunita Dyah Lailatul Maghfiroh Machlaurin, Afifah Machlaurin, Afifah Mahmud Dwi Sulistiyo Masito, Dewi Khurmi Muhammad Arzaki Nili Sufianti Ninda Titis Ainorrochma Ningsih, Lidya Prasti Eko Yunanto Pratama , Antonius Nugraha Widhi Pratiwi, Permata Sari Prihwanto Budi Subagijo Pudjoadmojo, Bambang Putri Eka Maryani Putu Harry Gunawan Putu Setia Pratama Ramadhani, Nuril Izzati Farihatur Rikman Aherliwan Rudawan Rimba Whidiana Ciptasari Risnandar, Risnandar S Siswanto Safarin, Arva Adwitya Sagala , Tunggal Panaluan Gabriel Sinta Rachmawati Sinta Rachmawati Supriadi, Muhammad Fadhlan Syahid, Ibadurrahman Tahyudin, Ganjar Gingin Ubaidillah, Rifky Fahrizal Wardhani, Firdha Aprillia Wicaksono, Ayssa Wirasakananda, Dewa Made Aditya Yeni Rahmawati Negara Zaenudin, Mohamad Nor