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All Journal CommIT (Communication & Information Technology) Jurnal Matematika Sains dan Teknologi Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika FITOFARMAKA: Jurnal Ilmiah Farmasi EKOLOGIA : Jurnal Ilmiah Ilmu Dasar dan Lingkungan Hidup JURNAL ILMU KEFARMASIAN INDONESIA Jurnal Sosial dan Teknologi Gunung Djati Conference Series
Triastinurmiatiningsih, -
Program Studi Biologi, FMIPA, Universitas Pakuan
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Other

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Journal : Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika

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KAMUS DIGITAL TANAMAN OBAT MENGGUNAKAN ALGORITMA ROCCHIO BERBASIS MOBILE Arie Qur’ania; Triastinurmiatiningsih -; Nazar Muhamad Ikhbal
KOMPUTASI Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (590.157 KB) | DOI: 10.33751/komputasi.v17i2.2145

Abstract

Digital dictionaries have been widely used to facilitate word processing and word search through digital media such as mobile phones. Society generally knows the efficacy and how to mix medicinal plants from the experience of previous parents or through books and writings. Searching through books or writings requires a short time compared to searching through digital media, one of which is a digital dictionary. The research aims to create a digital dictionary of mobile-based medicinal plants which has a search facility based on the words entered, for example, the contents of the medicinal plants. The digital dictionary application of medicinal plants uses a search method with the Rocchio algorithm with relevance feedback techniques to check the proximity of the query to the average document relevant to the level of similarity calculation through the stages of tokenizing, filtering, stemming, and Term Weighting with a total data of 200 medicinal plants.
Kamus Digital Tanaman Obat Menggunakan Algoritme Knuth Morris Pratt Berbasis Mobile Arie Qurania; Triastinurmiatiningsih -; Erika Candra
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol 19, No 1 (2022): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v19i1.4269

Abstract

Digital dictionary of medicinal plants a collection of applications a collection of names of medicinal plants. This application was developed to make it easier for users to access the use of medicinal plants based on keywords, names of common diseases such as asthma, diarrhea, fever, headache, diabetes, and so on. The obstacle in using the digital dictionary application of medicinal plants is that it is difficult to find exact information on drug searches, because the vocabulary in producing several other items is not necessarily the same as what is being sought. This study uses the Knuth Morris Pratt (KMP) algorithm search technique on a digital dictionary of medicinal plants by matching keywords as input with strings between text and patterns. This study aims to develop previous research on a digital dictionary of medicinal plants using a mobile-based Rocchio algorithm that searches medicinal plant data by querying proximity in a database that has weaknesses in words that have the same meaning with different words, using another search technique, namely KMP. is expected to get optimal results on search results based on the keyword name of the disease. The test results with 30 keywords on 640 medicinal plant data resulted in a precision value of 92.4, accuracy and recall of 100%.
Co-Authors Ade Kusmiati Alexander Agung Santoso Gunawan Ardiani, Weni Arie Qur’ania Bilkis, F.G Bina Lohita Sari Deden Ardiansyah E. Mulyati Effendi Erika Candra Ertina, - Ghina Athyah Wahid Haris Shobir Hikmah, Arfa Ul Ihat Ismawat Indah Nur Sayyidah Ismanto, - Lili Ayu Wulandhari Maelani, D.G. MOERFIAH . Moerfiah Moerfiah Nazar Muhamad Ikhbal Prihastuti Harsani Rahayu, S.Y. Srie Rangga Eka S. P Rina Yulianti Roni Jayawinangun Soliha, Eha Sri Wiedarti Sugiharti, Dewi Tampubolon, Jureka Tri Saptari Haryani Yulianita Yulianita