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Laurentius Kuncoro Probo Saputra, Laurentius Kuncoro Probo
Universitas Kristen Duta Wacana
Agriculture, Biological Sciences & Forestry Automotive Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Law, Crime, Criminology & Criminal Justice Mechanical Engineering Public Health Social Sciences Other

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Journal : JOINCS (Journal of Informatics, Network, and Computer Science)

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Testing The Accuracy of Fingerprint Recognition using Levenshtein Distance and Hamming Distance Methods : Uji Ketepatan Pengenalan Sidik Jari dengan Metode Levenshtein Distance dan Hamming Distance Ginantaka, Gregorius Sakti; Saputra, Laurentius Kuncoro Probo; Suwarno, Sri
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 6 No. 1 (2023): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v6i1.1612

Abstract

The presence or evidence of attendance is crucial in monitoring the presence of every individual working in a particular field. Developing an employee attendance system using fingerprints can expedite the processing of data of employees who have or have not attended. One brand of machine used as a fingerprint attendance tool is Fingerspot Flexcode. The data obtained from the machine comes in the form of bitmap images that are converted into strings using encoding. Although the resulting string sequences are different, there is a possibility of similarity in fingerprint data among employees because the system cannot distinguish data precisely. Therefore, the comparison between the Levenshtein Distance and Hamming Distance methods is used to determine which method has the highest accuracy in processing the system's calculation. The method with the highest accuracy will determine the level of compatibility of the method with the tested tool. For example, 6 fingerprint data are taken from each of the 7 different employees, resulting in a total of 42 data as test data. The calculation results show that the accuracy of the Levenshtein Distance method is 80,76 % with a precision of 46,43 %, while the Hamming Distance method is 78,34 % with a precision of 30,50 % in processing string similarity in fingerprint data. Based on these results, it can be concluded that the Levenshtein Distance method is better in calculating similarity in fingerprint data compared to the Hamming Distance method because it has a higher level of accuracy and precision compared to the Hamming Distance method.
Implementation of Internet of Things (IoT) in Smart Medicine Box for the Elderly : Implementasi Internet of Things (IOT) pada Kotak Obat Pintar untuk Lansia Susanto, Yeremia Yudha Setia Graha; Restyandito; Saputra, Laurentius Kuncoro Probo
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 6 No. 1 (2023): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v6i1.1614

Abstract

Consuming medicine on time is important for people who are sick. Medicine that prescribed by a doctor or pharmacist have various kind of rules, for example some medicine must be taken 3 times a day, 2 times a day, and 1 time a day, then there are rules after eating or before eating. Patients treated in the hospital are supervised by nurses, doctors, and receive more supervision from the hospital, but what if the patient is outpatient and the patient is an elderly person. With the presence of IoT technology that is not too expensive, a smart medicine box was made to be used to remind outpatients to take medicine which implements IoT technology and the android application used to manage the pillbox. The medicine box can remind patients to take medicine with the alarm module that is in the smart medicine box. System Usability Scale (SUS) is used to measure the success of the application. Smart medicine box is tested directly with data created to test the existing system. The result of testing the smart medicine box with existing data show that for each existing case, the smart medicine box system runs as it should. Application test results from all respondents received an average score of SUS 73,75. The score results show that the application can be accepted, get a grade scale worth B, and get good grades.
Co-Authors Agata Filiana Bastian, Brian Budi Susanto Dian Widiyanto Chandra Ginantaka, Gregorius Sakti Gloria Virginia Kristian Adi Nugraha Matahari Bhakti Nendya, Matahari Bhakti Restyandito Rini, Maria Nila Anggia Sebastian, Danny Senapartha, I Kadek Dendy Setiawan, Daniel Felix Sri Suwarno Sri Yulianto Joko Prasetyo Suryasatriya Trihandaru Susanto, Yeremia Yudha Setia Graha Sutarto Wijono Tamtama, Gabriel Indra Widi Umi Proboyekti Willy Sudiarto Raharjo Yuan Lukito