Garuda - Garba Rujukan Digital

MODEL SEM-PLS TERBAIK UNTUK EVALUASI PEMBELAJARAN MATEMATIKA DISKRIT DENGAN LMS Mardiana, Novi; Faqih, Ahmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 13 No 3 (2019): BAREKENG: Jurnal Ilmu Matematika dan Terapan
Publisher : MATHEMATIC DEPARTMENT, FACULTY OF MATHEMATICS AND NATURAL SCIENCES, UNIVERSITY OF PATTIMURA

Research on the use of Structural Equation Modelling-Partial Least Square (PLS-SEM) related to Learning Management System LMS has developed very rapidly. However, in these studies, it was not explained how to choose the best model used to evaluate the relationship among latent variables in the model. This study aims to select the best SEM-PLS model related to evaluating the use of LMS in Discrete Mathematics learning based on the criteria of Q2, AIC, AICu, AICc, BIC, HQ, and HQc. Data obtained from a survey of 109 3rd semester students who took Discrete Mathematics courses at STMIK IKMI Cirebon using 5 latent variables. The Main Model is formed based on all research latent variables and evaluated by stages 1) PLS-Algorithm, 2) Bootstrapping and 3) Blindfolding. Based on the Main Model, 16 alternative models are created with the same manifest variables as the Main Model. The best model is determined based on the highest Q2 value, and the least AIC, AICu, AICc, BIC, HQ and HQc values. The results of the study show that the Main Model is better based on the Q2 value compared to other models in this study. Different results are obtained if the AIC, AICu, AICc, BIC, HQ and HQc criteria are used, where Model C2 and B2 are the best models based on these criteria

PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS PERMAINAN EDUKASI DAN INTERAKTIF PADA MATAKULIAH AKUNTANSI KEUANGAN Edi Tohidi; Ahmad Faqih; Riri Narasati
Jurnal Edukasi (Ekonomi, Pendidikan dan Akuntansi) Vol 9, No 2 (2021): November
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/je.v9i2.6275

Matakuliah akuntansi keuangan dianggap oleh sebagian besar mahasiswa program studi komputerisasi akuntansi sebagai matakuliah yang membosankan dan sulit. Apalagi proses pembelajarannya masih menggunakan media ppt saja. Hal ini jelas semakin menyudutkan matakuliah akuntansi keuangan. Oleh karena itu, perlu adanya pembaharuan media pembelajaran yang up to date. Media pembelajaran berbasis permainan edukasi dan interaktif dirasa dapat mengatasi kendala pada pembelajaran akuntansi keuangan. Penelitian ini bertujuan untuk mengembangkan media pembelajaran berbasis permainan edukasi dan interaktif pada matakuliah akuntansi keuangan dengan pendekatan four D model yang dimodifikasi. Modifikasi yang dilakukan adalah penyederhanaan model dari empat tahap menjadi tiga tahap, yaitu pendefinisian, perancangan, dan pengembangan.. Media pembelajaran berbasis permainan edukasi dan interaktif, desainnya merujuk pada permasalahan serta kendala yang diperoleh dari hasil pendefinisian. Deskripsi hasil validasi pada tahap pengembangan, menunjukkan bahwa hasil validasi dari ahli media dalam kategori valid dan validasi ahli materi dalam kategori valid.Most students of computerized accounting courses consider financial accounting courses as tedious and challenging courses. Moreover, the learning process still uses ppt media only. This is increasingly cornering the study of financial accounting. Therefore, it is necessary to update learning media that is up to date. Learning media based on educational and interactive games is considered to overcome obstacles in learning financial accounting. This study develops academic and interactive game-based learning media in financial accounting courses with a modified four D model approach. The modification made simplifies the model from four stages into three stages, namely defining, designing, and developing. Learning media based on educational and interactive games, the design refers to the problems and constraints obtained from the definition results. The description of the validation results at the development stage shows that the validation results from media experts are in the correct category and material expert validation is in the correct category.

Thermoeconomic Optimization of Cascade Refrigeration System Using Mixed Carbon Dioxide and Hydrocarbons at Low Temperature Circuit Nasruddin, Nasruddin; Arnas, Arnas; Faqih, Ahmad; Giannetti, Niccolo
Makara Journal of Technology Vol. 20, No. 3
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Many applications and industrial processes require very low cooling temperature, such as cold storage in the biomedical field, requiring temperature below -80 °C. However, single-cycle refrigeration systems can only achieve the effective cooling temperature of -40 °C and, also, the performance of the cycle will decrease drastically for cooling temperatures lower than -35°C. Currently, most of cascade refrigeration systems use refrigerants that have ozone depletion potential (ODP) and global warming potential (GWP), therefore, in this study, a cascade system is simulated using a mixture of environmentally friendly refrigerants, namely, carbon dioxide and a hydrocarbon (propane, ethane or ethylene) as the refrigerant of the low temperature circuit. A thermodynamic analysis is performed to determine the optimal composition of the mixture of carbon dioxide and hydrocarbons in the scope of certain operating parameters. In addition, an economic analysis was also performed to determine the annual cost to be incurred from the cascade refrigeration system. The multi-objective/thermoeconomic optimization points out optimal operating parameter values of the system, to addressing both exergy efficiency and its relation to the costs to be incurred.

IMPLEMENTASI DATA MINING PADA KETEPATAN PENGIRIMAN BARANG DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS Arif Rinaldi Dikananda; Nurjana Adi Wijaya; Mulyawan Mulyawan; Ahmad Faqih
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 3 (2022): Jursima Vol.10 No.3 Desember 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.472

Abstract The development of digital technology E-commers is increasing, online shop goods delivery services are needed to support daily needs. The delivery man is in charge of sending goods to customers, with the delivery of goods applications can monitor delays in delivery of goods to customers so as to obtain data on delays in delivery of goods or called Over SLA. However, in processing the data, they still use manuals with Microsoft Excel so that they are lacking in providing more accurate information such as the accuracy of the accuracy of the delivery of goods, grouping of data on delays in the delivery of goods. The method used in this study by utilizing data mining using the K-Nearest Neighbors or KNN algorithm to classify or group data on delays in shipping goods. This method is used in data mining using Rapidminer machine learning applications. This study aims to classify data on delivery of goods and grouping data on timeliness of delivery so that data can be processed properly so as to produce information about the accuracy of delivery of goods by delivery man, to be more effective and faster in presenting data and classifying data. Keywords: Data mining, Classification, K-Nearest Neighbor (KNN).

UJI DAYA KONSEPSI EKSTRAK METANOL DAUN TAPAK DARA (Catharantus roseus) TERHADAP MENCIT (Mus musculus) ICR JANTAN Muharram Muharram; Adnan Adnan; Ahmad Faqih; Ahmad Jihadi
Indonesian Journal of Fundamental Sciences Vol 5, No 1 (2019)
Publisher : Universitas Negeri Makassar

Telah dilakukan penelitian tentang uji daya konsepsi ekstrak metanol daun tapak dara (catharantus roseus) pada mencit (mus musculus) ICR jantan. Penelitian ini bertujuan untuk mengetahuai apakah Ekstrak Metanol Daun Catharantus roseus Berpengaruh Secara Signifikan Terhadap daya konsepsi Mencit (Mus musculus) ICR jantan. Penelitian ini dilaksanakan di laboratorium kebun percobaan biologi FMIPA UNM pada bulan april hingga September 2018. Penelitian ini dilaksanakan dengan menggunakan rancangan acak lengkap. Hasil penelitian ditemukan bahwa ekstrak methanol daun tapak dara berpengaruh nyata terhadap daya konsepsi mencit jantan. Berdasarkan hasil penelitian ini disimpulkan bahwa ekstrak methanol daun tapak dara memiliki aktivitas sebagai antifertilitas pada mencit jantan.

CLUSTERING KELOMPOK BELAJAR SISWA BERDASARKAN HASIL UJIAN SEKOLAH MENGGUNAKAN ALGORITMA K-MEANS Mohammad Syaefudulloh; Ahmad Faqih; Fadhil Muhammad Basysyar
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 1 (2022): Jursima Vol. 10 No. 1, April Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i1.397

Introduction: The government has the responsibility of determining national education quality policies and standards and has a role to evaluate the implementation of education in the framework of national education quality control. One way to evaluate the standards of primary and secondary education nationally is the results of the achievement of the National Examination (UN). The quality of students in learning in schools has a lot of diversity this makes students have different levels of understanding this can be seen from the variety of school test scores obtained, this needs to be a concern for the school, especially teachers. One of them is by forming an effective study group so that every student has the opportunity to excel. To find out how to cluster the quality of Astanajapura State High School education based on the results of school test scores. Method: Research conducted using machine learning with K-Means algorithm with sample datasets or secondary data from State High School 1 Astanajapura Class XII which will be used as the material of this study. Method: Research conducted using machine learning with K-Means algorithm with sample datasets or secondary data from State High School 1 Astanajapura Class XII which will be used as the material of this study. Results: The results in this study get a cluster of students, namely students are very prestigious, prestigious and less prestigious. The clustering obtained in this study k = 4 is that there are 145 students categorized into cluster 0 with a DBi value of 0.763. The evaluation results of the K-Means algorithm resulted in a cluster with excellent and good grades, the results of this study can be used as a guideline for teaching teachers in decision making on the formation of student learning groups in Class XII. Discussion: The use of the K-Means method to group is one of the appropriate methods when viewed from the variables to be used, namely school test scores

PENERAPAN METODE ALGORITMA K-MEANS DALAM PEMETAAN PESERTA DIKLAT KETERAMPILAN PELAUT DI SMKN 1 MUNDU Sigit Rusmayana; Ahmad Faqih; Agus Bahtiar
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.404

Abstract Smkn 1 Mundu Cirebon Sailor Skills Training is the only training organizer who is in vocational high school that can conduct BST (Basic Safety Training) training for sailors of IMO (International Maritime Organization) standards. This research aims to identify the origin of the participants of the training, to apply when the time of the training is held, to find out the needs of the certificate of the participants of the training. This research sample was obtained from the data sheet of Smkn 1 Mundu Cirebon Sailor Skills Training where everyone who will work at sea must have a BST (Basic Safety Training) certificate. The research method done by machine learning using the K-Means Algorithm is the simplest and most common clustering method. This is because K-Means has the ability to group large amounts of data with relatively fast and efficient computing times. With the research can be useful for the Institute of Seafaring Skills Training SMKN 1 Mundu Cirebon So that it can be to identify the Origin of The Training Participants from the cirebon, Indramayu, Majalengka, Kuningan, Brebes, Tegal Pemalang, Purwokerto which dominates the participants of the training, as well as the implementation of the most widely carried out training in the period of August, September and December after students are declared first of school and most certificates are taken to work abroad especially on fishing vessels, commercial vessels and cruise ships as well as at offshore drilling refineries. The result of the application of this k-means clustering algorithm results in k = 3 with DBi = 0.547 model clusters produced cluster 0 = 465 items, cluster 1 = 608 items and cluster 2 = 462 items Keywords of at least 3-5 keywords: Sailor Skills Training, BST (Basic Safety Training), K-Means Algorithm

IMPLEMENTASI ALGORITMA K-NEAREST NEIGHBOUR UNTUK PREDIKSI KETEPATAN KELULUSAN Manarul Hidayat; Ahmad Faqih; Tati Suprapti
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.420

In an education system, students are an important asset of a college and therefore, it is important to pay attention to the percentage of students who graduate on time. However, there is an imbalance between the inputs and outputs of the completed students. Students who enroll in large numbers, but students who graduate on time compared to those who are late according to regulations are fewer. In this study, the author aims to apply the K-NN method using cross validation to predict student graduation rates at STMIK IKMI. The results of this study are in the form of models and evaluations of student graduation predictions, whether they graduate on time or not on time. Based on the results of the design, implementation, testing using the RapidMiner program for predicting student graduation using the k-NN method with Cross Validation resulting in an accuracy of 70.28%, an error of 29.78%, and AUC of 0.739 Keywords: Graduation, Student, K-NN, Cross Validation

CLUSTERING KELOMPOK BELAJAR SISWA BERDASARKAN HASIL UJIAN SEKOLAH MENGGUNAKAN ALGORITMA K-MEANS Mohammad Syaefudulloh; Ahmad Faqih; Fadhil Muhammad Basysyar
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 1 (2022): Jursima Vol. 10 No. 1, April Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i1.397

Introduction: The government has the responsibility of determining national education quality policies and standards and has a role to evaluate the implementation of education in the framework of national education quality control. One way to evaluate the standards of primary and secondary education nationally is the results of the achievement of the National Examination (UN). The quality of students in learning in schools has a lot of diversity this makes students have different levels of understanding this can be seen from the variety of school test scores obtained, this needs to be a concern for the school, especially teachers. One of them is by forming an effective study group so that every student has the opportunity to excel. To find out how to cluster the quality of Astanajapura State High School education based on the results of school test scores. Method: Research conducted using machine learning with K-Means algorithm with sample datasets or secondary data from State High School 1 Astanajapura Class XII which will be used as the material of this study. Method: Research conducted using machine learning with K-Means algorithm with sample datasets or secondary data from State High School 1 Astanajapura Class XII which will be used as the material of this study. Results: The results in this study get a cluster of students, namely students are very prestigious, prestigious and less prestigious. The clustering obtained in this study k = 4 is that there are 145 students categorized into cluster 0 with a DBi value of 0.763. The evaluation results of the K-Means algorithm resulted in a cluster with excellent and good grades, the results of this study can be used as a guideline for teaching teachers in decision making on the formation of student learning groups in Class XII. Discussion: The use of the K-Means method to group is one of the appropriate methods when viewed from the variables to be used, namely school test scores

PENERAPAN METODE ALGORITMA K-MEANS DALAM PEMETAAN PESERTA DIKLAT KETERAMPILAN PELAUT DI SMKN 1 MUNDU Sigit Rusmayana; Ahmad Faqih; Agus Bahtiar
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.404

Abstract Smkn 1 Mundu Cirebon Sailor Skills Training is the only training organizer who is in vocational high school that can conduct BST (Basic Safety Training) training for sailors of IMO (International Maritime Organization) standards. This research aims to identify the origin of the participants of the training, to apply when the time of the training is held, to find out the needs of the certificate of the participants of the training. This research sample was obtained from the data sheet of Smkn 1 Mundu Cirebon Sailor Skills Training where everyone who will work at sea must have a BST (Basic Safety Training) certificate. The research method done by machine learning using the K-Means Algorithm is the simplest and most common clustering method. This is because K-Means has the ability to group large amounts of data with relatively fast and efficient computing times. With the research can be useful for the Institute of Seafaring Skills Training SMKN 1 Mundu Cirebon So that it can be to identify the Origin of The Training Participants from the cirebon, Indramayu, Majalengka, Kuningan, Brebes, Tegal Pemalang, Purwokerto which dominates the participants of the training, as well as the implementation of the most widely carried out training in the period of August, September and December after students are declared first of school and most certificates are taken to work abroad especially on fishing vessels, commercial vessels and cruise ships as well as at offshore drilling refineries. The result of the application of this k-means clustering algorithm results in k = 3 with DBi = 0.547 model clusters produced cluster 0 = 465 items, cluster 1 = 608 items and cluster 2 = 462 items Keywords of at least 3-5 keywords: Sailor Skills Training, BST (Basic Safety Training), K-Means Algorithm

Title

Found 18 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 18 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 18 Documents
Search