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All Journal Universa Medicina Jurnal Informatika Teknologi dan Sains (Jinteks)
Iskandar Muda Siregar, Iskandar Muda
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Computer Science & IT Control & Systems Engineering Health Professions Immunology & microbiology Medicine & Pharmacology Public Health

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Protective effects of Cyclea barbata Miers leaves against aspirin-induced gastric ulcer in mice Siregar, Iskandar Muda; Miladiyah, Isnatin
Universa Medicina Vol 30, No 2 (2011)
Publisher : Faculty of Medicine, Trisakti University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18051/UnivMed.2011.v30.88-94

Abstract

One side effect of non-steroidal anti-inflammatory drugs is gastric mucosal irritation, possibly causing gastric ulcers. The aim of this study was to evaluate the protective effect of cincau leaves (Cyclea barbata Miers) on aspirin-induced gastric ulcer in Balb/c mice. Twenty five Balb/c mice (20-30 g, 2-3 months old) were randomly divided into 5 groups. Group I-III were given cincau leave infusion at dosages of 2.5 mg/kg BW, 5 mg/kg BW, and 10 mg/kg BW, respectively, while group IV (positive control) received antacid at a dosage of 20 mg/kg BW, and group V (negative control) one milliliter of distilled water. All interventions were given by the oral route, once daily for seven days. On day 7, the mice were given aspirin (600 mg/kg BW) to induce gastric ulcer. After 30 minutes, all mice were sacrified, and their stomachs examined macroscopically for gastric ulcer, characterized by the presence of ulcer(s) and bleeding. Total ulcer scores were analyzed by one-way Anova to compare between-group protective effect of interventions against aspirin-induced gastric ulcer. Results showed that groups treated with cincau leaf infusion at all dosages experienced a gastric ulcer protective effect. There were significant differences (p=0.002) between treatments, compared to the negative control, but no significant differences (p>0.05) when compared to the positive control. Thus cincau leaves (Cyclea barbata Miers) at dosages of 2.5 mg/kg BW, 5 mg/kg BW, and 10 mg/kg BW, had a protective effect against aspirin-induced gastric ulcer in mice. Higher dosages of cincau leaf infusion have a correspondingly higher gastric ulcer protective power.
IMPLEMENTASI BIG DATA DALAM ANALISIS SENTIMEN ULASAN PENGGUNA TOKOPEDIA BERBASIS APLIKASI WEB MENGGUNAKAN METODE NAIVE BAYES Lubis, Febri Ananda; Siregar, Iskandar Muda; Azry, Aldipan; Simbolon, Khalil Elhamdi; Sitorus, Sahat Parulian
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 1 (2026): EDISI 27
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i1.7190

Abstract

Pesatnya perkembangan e-commerce mendorong meningkatnya jumlah ulasan pengguna yang memuat opini dan pengalaman terhadap layanan yang digunakan. Data ulasan tersebut memiliki karakteristik Big Data, seperti volume yang besar, variasi bahasa, dan pertumbuhan data yang cepat, sehingga analisis manual menjadi tidak efisien. Penelitian ini bertujuan mengimplementasikan konsep Big Data dalam analisis sentimen ulasan pengguna Tokopedia berbasis aplikasi web menggunakan algoritma Multinomial Naive Bayes. Metode penelitian yang digunakan adalah pendekatan kuantitatif dengan tahapan pengumpulan data, preprocessing teks, ekstraksi fitur menggunakan Term Frequency–Inverse Document Frequency (TF-IDF), serta klasifikasi sentimen ke dalam kategori positif, negatif, dan netral. Dataset yang digunakan terdiri dari 4.000 ulasan pengguna yang dibagi menjadi data latih dan data uji. Evaluasi kinerja model dilakukan menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa metode Naive Bayes mampu mengklasifikasikan sentimen ulasan dengan performa yang baik. Visualisasi hasil analisis dalam bentuk dashboard aplikasi web memudahkan interpretasi distribusi sentimen. Dominasi sentimen negatif mengindikasikan adanya tingkat ketidakpuasan pengguna terhadap layanan pada data yang dianalisis. Kontribusi penelitian ini terletak pada penerapan analisis sentimen berbasis Big Data yang terintegrasi dengan aplikasi web sebagai alat evaluasi layanan e-commerce yang bersifat aplikatif dan skalabel.
Co-Authors Azry, Aldipan Isnatin Miladiyah Lubis, Febri Ananda Simbolon, Khalil Elhamdi Sitorus, Sahat Parulian