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All Journal Aptisi Transactions on Technopreneurship (ATT) Brahmana : Jurnal Penerapan Kecerdasan Buatan J-SAKTI (Jurnal Sains Komputer dan Informatika) Bulletin of Information Technology (BIT)
Muhammad Ibnu Saad Saad
STMIK Widya Cipta Dharma
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Social Sciences

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Sistem Informasi Geografis (SIG) Pemetaan Kost-Kosan Menggunakan Metode Formula Haversine Muhammad Ibnu Sa’ad; Muhammad Surahmanto; Muhammad Rizki Pratono Soemari; Kusrini K; M. Syukri Mustafa
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 4, No 1 (2020): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v4i1.187

Abstract

Geographic Information System ia a geospatial software system that has the ability to build, store, manage and display geo-referenced information, for example data that is identified by location. By using GIS, it is expected that it will be easier for prospective students and students to find out the location of boarding houses that are located around the campus of Mulawarman University. The system development method uses the waterfall method. While the system design method uses UML (Unified Modelling Language) to visualize, determine, develop and document a software system. The algorithm used in this study uses the haversine formula which will later help to find the nearest boarding house location around the campus of Mulawarman University, the haversine formula will produce the shortest distance between two points, for example on a ball taken from the longitude and latitude. The result of this study will disply detailed boarding location information, besides that on this geograpihic information system the user will later be able to see the details of boarding and admin data can change, add data to the boarding owner and be technically responsible for the running of the application, while the boarding owner is only responsible on managing boarding data on their respective users.
Penerapan Metode Single Moving Average Dalam Peramalan Persediaan Bahan Pangan Kukuh Rizqi Liyadi; Heny Pratiwi; Pitrasacha Aditya; Muhammad Ibnu Sa’ad
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 4, No 1 (2022): Edisi Desember
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v4i1.136

Abstract

Forecasting is a technique that is quite widely used today and has been developed since the 19th century. In line with the development of increasingly sophisticated forecasting techniques accompanied by developments in the use of computers. Forecasting can predict or estimate what will happen in the future using certain techniques so that forecasting has received increasing attention in recent years. Web-based applications are one of the systems that support the development of computer use, therefore in this study, researchers develop web-based applications for forecasting using the Single Moving Average method. In this study, forecasting was carried out using the Single Moving Average method to find out how much food is needed in the following month based on actual data from the previous months. Based on forecasting which was carried out using actual data from December 2021 to June 2022, the results obtained in the following month, namely July 2022, were 2,901 kg.
Application of the SMARTER Method in Determining the Whitening of Study Permits and Teacher Study Tasks Rahmat Daffa Affandi; Heny Pratiwi; Azahari; Muhammad Ibnu Sa'ad
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 2 (2023): July
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i2.311

Abstract

 Study assignment programs and study permits aim to meet the need for staff with certain skills or competencies. in the context of carrying out tasks and functions as well as organizational development, reducing the gap between competency standards and or position requirements with the competencies of Teachers who will fill positions, as well as increasing the knowledge, abilities, skills, attitudes, and professional personality of Teachers, as an integral part of the development plan teacher career. This of course requires a decision support system to be able to assist the Education Office in selecting teachers to provide teacher study permits and study assignments. Decision Support Systems (DSS) or Decision Support Systems (DSS) are computer-based systems that are interactive in assisting decision-makers by utilizing data and models to solve unstructured problems. In this study, the SMARTER method was used as a multi-criteria decision making. The purpose of this research is to assist the Education Office in making decisions when providing a determination of the redemption of study permits, and teacher study assignments as well as providing uniformity and legal certainty in the implementation of study assignments and study permits, and supporting teachers within the local government so that they can improve competence and be more professional in carrying out its duties and functions. Based on research that has been done using the SMARTER method, the sum of each criterion is 0.7840. This implementation produces information that is relatively fast, precise, and feasible to use for updating study permits and teacher learning assignments, and can be carried out without being constrained by time by implementing a web-based application.
Application of the SMARTER Method in Determining the Whitening of Study Permits and Teacher Study Tasks Rahmat Daffa Affandi; Heny Pratiwi; Azahari; Muhammad Ibnu Sa'ad
Aptisi Transactions On Technopreneurship (ATT) Vol 5 No 2 (2023): July
Publisher : Pandawan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/att.v5i2.311

Abstract

 Study assignment programs and study permits aim to meet the need for staff with certain skills or competencies. in the context of carrying out tasks and functions as well as organizational development, reducing the gap between competency standards and or position requirements with the competencies of Teachers who will fill positions, as well as increasing the knowledge, abilities, skills, attitudes, and professional personality of Teachers, as an integral part of the development plan teacher career. This of course requires a decision support system to be able to assist the Education Office in selecting teachers to provide teacher study permits and study assignments. Decision Support Systems (DSS) or Decision Support Systems (DSS) are computer-based systems that are interactive in assisting decision-makers by utilizing data and models to solve unstructured problems. In this study, the SMARTER method was used as a multi-criteria decision making. The purpose of this research is to assist the Education Office in making decisions when providing a determination of the redemption of study permits, and teacher study assignments as well as providing uniformity and legal certainty in the implementation of study assignments and study permits, and supporting teachers within the local government so that they can improve competence and be more professional in carrying out its duties and functions. Based on research that has been done using the SMARTER method, the sum of each criterion is 0.7840. This implementation produces information that is relatively fast, precise, and feasible to use for updating study permits and teacher learning assignments, and can be carried out without being constrained by time by implementing a web-based application.
Perbandingan Algoritma Extreme Learning Machine dan Multilayer Perceptron Dalam Prediksi Mahasiswa Drop Out Muhammad Ibnu Saad Saad
Bulletin of Information Technology (BIT) Vol 4 No 3: September 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v4i3.890

Abstract

Determined by the university concerned. The high number of drop out students at tertiary institutions can be minimized by policies from tertiary institutions to direct and prevent students from dropping out that detecting at-risk students in the early stages of education is very important to do to keep students from dropping out. The purpose of this study is to classify and compare the Extreme Learning Machine and Multilater Perceptron algorithms in predicting student drop out. This study uses two algorithms, namely Extreme Learning Machine and Multilater Perceptron which are feedforward artificial neural network learning methods. The data used is 110 data according to the number of students from class 2012 to 2018. The data is taken from the Doctor of Education Management academic information system. In this case how to predict student drop out using the variables Gender, Working Status, Family Status, Age, Semester 3 GPA, Comprehensive Examination, Dissertation Progress, and Publications. The results of the Extreme Learning Machine classification based on a ratio of 80:20 get an accuracy of 95% with a hidden layer of 20 and a Mean Squared Error value of 0.369. Whereas the Multilater Perceptron with the same ratio gets 91% accuracy. From the two models used, it shows that the two artificial neural network algorithms can produce good performance in predicting drop out students.
Co-Authors Azahari Heny Pratiwi Heny Pratiwi Kusrini K M. Syukri Mustafa Muhammad Ibnu Sa’ad Muhammad Surahmanto Pitrasacha Adytia