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All Journal REiD (Research and Evaluation in Education) Jurnal MIPA dan Pembelajarannya
Abadyo Abadyo, Abadyo
Malang State University
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Education Energy Immunology & microbiology Materials Science & Nanotechnology Mathematics

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Analisis model antrian pada sistem single channel multi phase di kantor Satpas Polres kota Probolinggo Pitaluka, Erza; Abadyo, Abadyo
Jurnal MIPA dan Pembelajarannya Vol. 2 No. 11 (2022): Nopember
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um067v2i112022p4

Abstract

Queue is a problem that mostly occurred in public service facility such as Driving License (SIM) renewal service in Satpas (Driving License Administration) Office of Probolinggo City Police Station. For applicant that want to do SIM renewal must go through three steps: applicant comes to do registration in registration counter with submitting form and all requirements, then wait until the applicant is called by counter officer of file checking and do the payment, next the applicant waits to be called by officer to take photo for Driving License Card. The aim of this research was to know queue model that suitable with applicant queue of Driving License renewal and to know performance from queue model that suitable with applicant queue of Driving License renewal in Satpas Office of Probolinggo City Police Station. This research used primary data that was obtained from direct observation to the arrival time and service time for Driving License renewal applicant that served in file checking and payment counter (step 1) and in room to take photo for Driving License (step 2). From analysis result and discussion, it was obtained queue model that suitable for step 1 and step 2, they were . In the step 1, the largest utility was on March, 11th 2016 for 96.05% with the average number of applicant to be served in the queue for 8 applicants, the average number of applicant to be served in the sistem for 9 applicants, the average time of waiting period for each applicant in the queue was 21 minutes, and the average time of waiting period for each applicant in the sistem was 23 minutes. In the step 2, the largest utility was on March, 12th 2016 for 94.20% with the average number of applicant to be served in the queue for 3 applicants, the average number of applicant to be served in the sistem for 4 applicants, the average time of waiting period for each applicant in the queue was 8 minutes, and, the average time of waiting period for each applicant in the queue was 10 minutes.
Penggunaan analisis chaid untuk segmentasi pelanggan kredit motor (Studi Kasus di PT. FIF Cabang Kepanjen) Wicaksono, Moch. Raharjo; Abadyo, Abadyo
Jurnal MIPA dan Pembelajarannya Vol. 2 No. 12 (2022): Desember
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um067v2i122022p6

Abstract

Kasus kredit macet merupakan masalah klasik pada bidang kredit. Banyak faktor yang dapat menyebabkan suatu kegiatan kredit itu menjadi bermasalah atau kredit macet. Solusi untuk mengurangi banyaknya kredit yang bermasalah pada permasalahan kredit macet ini yaitu diperlukan segmentasi calon kreditur yang tepat, mengingat bahwa kreditur merupakan kunci utama dalam kegiatan pengkreditan. Pada kasus kredit macet di PT. FIF Cabang Kepanjen, analisis CHAID digunakan untuk menentukan segmentasi pelanggan kredit motor berdasarkan status kredit pelanggan sebagai variabel terikat dan profil pelanggan sebagai variabel bebas. Segmentasi pelanggan dengan analisa CHAID dilakukan untuk mengidentifikasi segmen pelanggan yang memiliki rasio kredit macet yang paling rendah. Berdasarkan hasil analisa CHAID didapatkan tiga segmen yang berbeda. Segmen pelanggan dengan karakteristik status pelanggan baru atau pelanggan baik yang menempati rumah pribadi adalah segmen yang memiliki rasio kredit macet yang paling rendah.
Estimation of ability and item parameters in mathematics testing by using the combination of 3PLM/ GRM and MCM/ GPCM scoring model Abadyo, Abadyo; Bastari, Bastari
REID (Research and Evaluation in Education) Vol. 1 No. 1 (2015): June
Publisher : Graduate School of Universitas Negeri Yogyakarta & Himpunan Evaluasi Pendidikan Indonesia (HEPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/reid.v1i1.4898

Abstract

The main purpose of the study was to investigate the superiority of scoring by utilizing the combination of MCM/GPCM model in comparison to 3PLM/GRM model within a mixed-item format of Mathematics tests. To achieve the purpose, the impact of two scoring models was investigated based on the test length, the sample size, and the M-C item proportion within the mixed-item format test and the investigation was conducted on the aspects of: (1) estimation of ability and item parameters, (2) optimalization of TIF, (3) standard error rates, and (4) model fitness on the data. The investigation made use of simulated data that was generated based on fixed effects factorial design 2 x 3 x 3 x 3 and 5 replications resulting in 270 data sets. The data were analyzed by means of fixed effect MANOVA on Root Mean Square Error (RMSE) of the ability and RMSE and Root Mean Square Deviation (RNSD) of the itemparameters in order to identify the significant main effects at level of a = .05; on the other hand, the interaction effects were incorporated into the error term for statistical testing. The -2LL statistics were also used in order to evaluate the moel fitness on the data set. The results of the study show that the combination of MCM/GPCM model provide higher accurate estimation than that of 3PLM/GRM model. In addition, the test information given by the combination of MCM/GPCM model is three times hhigher than that of 3PLM/GRM model although the test information cannot offer a solid conclusion in relation to the sample size and the M-C item proportion on each test length which provides the optimal score of thest information. Finally, the differences of fit statistics between the two models of scoring determine the position of MCM/GPCM model rather than that of 3PLM/GRM model.
Co-Authors Bastari Bastari, Bastari Pitaluka, Erza Wicaksono, Moch. Raharjo