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All Journal EKSAKTA: Journal of Sciences and Data Analysis AJIE (Asian Journal of Innovation and Entrepreneurship) Unisda Journal of Mathematics and Computer Science (UJMC) PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Enthusiastic : International Journal of Applied Statistics and Data Science Khazanah: Jurnal Mahasiswa
Rahmadi Yotenka
Universitas Islam Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences

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Journal : EKSAKTA: Journal of Sciences and Data Analysis

 1 
The Implementation Of Apriori Algorithm And Chi-Square Test In Determining Pattern Of Relationship Among The Rawi Hadis Rahmadi Yotenka
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 17, ISSUE 1, February 2017
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/eksakta.vol17.iss1.art3

Abstract

In this research apriori algorithm was implemented on rawi data of hadits to find out pattern of relationship among the rawi hadits in shahih bukhori book. The analogy that can be compared is by assuming that series or chain of rawi in every sanad of hadis may be regarded as transaction, while rawi hadis were items in transaction. Data mining is the method that was used to analyze with association rule technique. Association rule technique is used to find a pattern rule between a combination of items. To find out association rule by using association rule application, it is used apriori algorithm by observing three important measurement, namely support, confidence, and lift values. The analysis result of apriori algorithm showed that for minimum support 0.03 and minimum confidence 0.9 having 9 strong association pattern based on the sequence of rawi hadis of its sanad. Every rule of association which was strong, then tested by chi-square to prove that the rawis that were in the rule were truly connected or statisticly significance
Clustering of PDQ Participant Student in Faculty of Mathematics and Natural Sciences UII using the ROCK Method Rahmadi Yotenka; sekti kartika dini
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 3, ISSUE 2, August 2022
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol3.iss2.art7

Abstract

The Qur’anic Self-Development (PDQ)-Ta'lim Program is one of the student activities that must be followed by diploma and bachelor program students in Universitas Islam Indonesia (UII). The implementation of PDQ is coordinated by each faculty which is carried out for 4 semesters with 12 meetings for each semester. After carrying out PDQ activities, it is necessary to know the student profiles that can be used as the basis for policy making in the implementation of PDQ activities in the next period. In order to find out the profile of students after participating in PDQ activities, it is necessary to group these students based on related variables. This study uses the ROCK method to group students participating in the PDQ Faculty of Mathematics and Natural Sciences (FMIPA) UII batch 2020. The ROCK method is a robust agglomerative hierarchical-clustering algorithm based on the notion of links. The ROCK method is a suitable clustering method for grouping data with categorical variables. Based on the results of the analysis of the ROCK method of student data for the batch 2020 FMIPA UII, obtained three optimum clusters (k=3) at a threshold value of θ of 0.20. Threshold 0.20 has the smallest SW/SB ratio value of 0.0514 or 5.14% and the largest R-squared value is 61.76% compared to other thresholds.
Co-Authors Anisa Nabila Baiq Nina Febriati Baritoadi Buldan Rayaganda Rito Dian Widya Lestari Dian Fazano Fikri El Huda Juan Sheptiadi Efendi Lazuardy Ilham Effendie Muhaimin Muhaimin Muhammad Muhajir Muhammad Muhajir Muhammad Muhajir, Muhammad Novendri Isra Asriny R.A. Nurul F.A. Asnawi Sekti Kartika Dini Tarisya Qurrota A'yuni