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All Journal Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik J-SAKTI (Jurnal Sains Komputer dan Informatika) JURTEKSI JOISIE (Journal Of Information Systems And Informatics Engineering) JATI (Jurnal Mahasiswa Teknik Informatika) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Manajemen Informatika Jayakarta J-SAKTI (Jurnal Sains Komputer dan Informatika) Edu Sociata : Jurnal Pendidikan Sosiologi Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Pengabdian Pada Masyarakat METHABDI Majalah Ilmiah METHODA

Safii, M.

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Author-ID : 1702995

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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PERBANDINGAN ALGORITMA C4.5 DAN NAIVE BAYES UNTUK MEGUKUR MINAT PENJUALAN SEPATU Lubis, Nur Azizah; Safii, M.; Alfina, Ommi
Majalah Ilmiah METHODA Vol. 13 No. 3 (2023): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol13No3.pp337-345

The Second Gangbrand shoe shop is one that sells second-hand shoes or what you could also call quality and original second-hand shoes that have certain brands at affordable prices that are cheaper than the original price. This research aims to measure the level of customer interest by comparing the C4.5 algorithm method and the Naive Bayes algorithm. The data source was obtained from second gangbrand stores which were taken based on customer interest. So it is necessary to carry out data analysis to classify customer interest data using the C4.5 and Naive Bayes algorithms to compare accuracy and precision which are the benchmarks in this research. Calculations in this research were carried out manually using Microsoft Excel according to the C4.5 and Naive Bayes algorithm calculation models and then evaluated using the Rapidminer 10.3 tool which was used to help determine accurate values. After conducting research testing, the C4.5 algorithm received an accuracy value of 60.00% and a precision of 50.00%, while the Naive Bayes algorithm received an accuracy value of 60% and a precision of 33.33%. So it can be concluded that the two algorithms have the same accurate accuracy value, but in terms of precision value the C4.5 algorithm is superior in determining customer interest recommendations. It is hoped that the results of this research can provide input and information for future researchers.

Prediksi Jumlah Produksi Kelapa Sawit di Indonesia Menggunakan Algoritma Backpropagation Safii, M.; Alfina, Ommi
Majalah Ilmiah METHODA Vol. 14 No. 2 (2024): Majalah Ilmiah METHODA
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methoda.Vol14No2.pp166-174

Indonesia is a country that has advantages in the agricultural sector which has the largest plantation and agricultural areas in ASEAN, one of which is oil palm plantations. Indonesia is one of the largest crude palm oil (CPO) business players in the world. More and more palm oil mills and oil palm land are being converted to oil palm cultivation, because oil palm plantations are more beneficial for farmers and palm oil processors. Palm oil plantations are still trying in several ways to maintain stable market demand, one of which is by increasing palm oil production, because palm oil is the main source of other product derivatives. Palm oil production fluctuates every month, but the ups and downs are caused by many factors, namely climate, rainfall, soil fertility, selling prices, and others. Reduced production has a direct impact on the income of farmers and workers in the sector, which in turn can cause economic instability. Actions are needed to ensure the continuity of this industry, one of which is by making predictions. One prediction technique is the Backpropagation artificial neural network. The prediction model can provide very accurate estimates of palm oil production at the provincial level. By analyzing historical data, this research can identify patterns that can help predict future palm oil production. The urgency lies in the strategic role of palm oil in the Indonesian economy.

PENERAPAN ALGORITMA BACKPROPAGATION DALAM MEMPREDIKSI JUMLAH JAMAAH HAJI PEMATANG SIANTAR Hambali, Humaidi; Safii, M.
JOISIE (Journal Of Information Systems And Informatics Engineering) Vol 8 No 1 (2024)
Publisher : Institut Bisnis dan Teknologi Pelita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35145/joisie.v8i1.3882

Salah satu pilar utama agama Islam adalah melaksanakan ibadah haji bagi mereka yang mampu. Setiap tahun, jumlah jamaah pendaftar haji di Pematang Siantar mengalami kenaikan dan penurunan yang signifikan sehingga cukup kesulitan untuk merencanakan dan mengalokasikan sumber daya, akomodasi, transportasi, dan layanan pendukung lainnya dengan lebih efektif. Untuk menyelesaikan masalah diatas, diperlukan suatu cara untuk menganalisis jumlah jamaah pendaftar haji di Pematang Siantar. Salah satu metode yang dapat digunakan adalah metode Backpropagation dengan data pelatihan dari tahun 2018 hingga 2021 dan data pengujian dari tahun 2019 hingga 2022. Hasil yang dihasilkan menggunakan Aplikasi Matlab R2011a menunjukkan 3-11-1 sebagai arsitektur terbaik dengan tingkat akurasi 100%. Penelitian ini menunjukan bahwa pada tahun berikutnya akan ada 33 jamaah pendaftar haji di Pematang Siantar. Dapat disimpulkan bahwa algoritma backpropagation dapat digunakan sebagai metode yang mempermudah pencarian prediksi, dan tingkat akurasi yang diperoleh bergantung pada arsitektur yang digunakan.

PELATIHAN PENGINPUTAN DATA SECARA OTOMATIS DI MICROSOFT EXCEL MENGGUNAKAN DATA FORM DAN MACRO VBA (BASIC FOR APLICATION) DI SMA IT UNGGUL AL-MUNADI MEDAN Siregar, Elida Tuti; Alfina, Ommi; Puspita, Dahlia; Safii, M.
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 3 No 2 (2023): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/methabdi.Vol3No2.pp150-154

Automatic data input using Microsoft Excel as a number processor or application for automatically processing data such as numerical values, mathematical formulas and making financial reports hone students' skills in knowledge of the use of computer technology, which is a basic need nowadays to operate a computer, a skill that students must master in the future world of work. because computer operating skills are really needed by companies, especially the Microsoft Excel application to process technology-based company data in determining decision makers in a company. This training will produce graduates who can operate computers and input data automatically. This activity provides skills and knowledge to students at SMA IT Unggul Al Munadi Medan using Microsoft Excel to process and input data automatically with Visual Basic forms and macros (VBA)

Implementasi Algoritma C4.5 Untuk Mengukur Tingkat Kepuasan Mahasiswa yang Berlangganan Wifi Indihome Kiswara, Qodrat; Safii, M.; Andani, Sundari Retno; Lubis, Muhammad Ridwan; Renaldi, Renaldi
TIN: Terapan Informatika Nusantara Vol 4 No 9 (2024): February 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i9.4918

The urgency of research on satisfaction levels is closely related to the success and desires of a business or organization. Without a good understanding of customer satisfaction, a company or organization may lose market share, face declining sales, or even face failure. Therefore, this research must be carried out regularly and continuously. The purpose of this research is to determine the level of customer satisfaction and to determine the dominant service quality that influences the quality of service provided by PT Telkom Indihome to customers. In this research, researchers used the C4.5 Algorithm data mining technique. The research data source used was by making observations and distributing questionnaires to customers of PT Telkom Pematangsiantar City. In this case, researchers used assessment attributes, namely service quality, accessibility and product quality. This research is expected to provide information and input to PT Telkom Indihome in the form of evaluations in improving network quality. The results of the research conducted by the author obtained the following conclusion, namely that Data Mining with the C4.5 Algorithm can classify the measurement of satisfaction levels of STIKOM Tunas Bangsa students who subscribe to Indihome WiFi. The accuracy results obtained by this research were 75.00% with the average student who subscribed to Indihome WiFi stating that they were satisfied.

Implementation of K-Means Clustering on High School Students Management Kartina, Anggriani Dwi; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

The quality of national education and teaching needs to be monitored continuously in every stage and step of educational activities. The monitoring is intended as an effort to control the quality of education and furthermore as a guarantee of the quality of education. Therefore, a method is needed to facilitate the grouping of high school student data. With the k-means clustering approach, the division of student groups can be done based on the national final exam scores. In this study, students were clustered using the K-Means algorithm. By using K-Means, it aims to facilitate the grouping of the highest and lowest Pemtangssiantar High School students. The result is a picture that shows the grouping of students based on national final exam scores.

K-Medoids Algorithm Analysis in Grouping Students' Level of Understanding of Subjects Butarbutar, Ehrlich F.T; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Analysis of the teaching and learning process needs to be done as feedback on the understanding of the material for students. One of the obstacles faced by schools is that there is no method of how this feedback can be done so that student achievement is uneven. Student achievement in subjects can be seen from the results of the scores on the report cards obtained by students after taking the final semester exam. Due to the uneven achievement of students, it is necessary to make a method so that feedback analysis can be carried out on the level of student understanding of the subject. Is data mining with clustering techniques using the K-Medoids algorithm. With this algorithm, students' understanding of subjects with high potential can be grouped with high brightness average results

Implementation Data Mining of Employement Contract Exten-sion at Indosat Using Naïve Bayes Sari, Andini Fadila; Safii, M.; Suhendro, Dedi; Damanik, Irfan Sudahri
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Contract employees are company resources in carrying out oprasional activities for a certain time based on an agreement or contract. Every company that uses a work contrak system every year, there must be employees who are extended and not renewed. Employees will get additional contracts if they have good performance. In this case to determine whether an employee is extended or not extended his work contract, there is difficulty in determining it and requires a long time and process. Therefore, this research was conducted to help guarantee the extension of the employee’s work contract by classifier it into the labes “Eligble” and “Not Feasible” which has 4 variables for the process of employees who will be extended or not. The four variables are age, years of service, aspects of delay, achievement. In this study, the alternatives used as samples were employees at PT. Indosat Ooredoo. The number of data tested is 5 employees with two classes. From the results of the calculation of the Naïve Bayes Algorithm, it is obtained classification with 3 employees eligible class and 2 employees not eligible class. The results of this study found that the level of accuracy of 100.00%.

Grouping of Toddlers with Malnutrition Based on Provinces in Indonesia Using K-Medoids Algorithm Siallagan, Sri Anita; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Malnutrition is a poor health condition in infants and toddlers caused by a lack of nutritional intake. Babies and toddlers who suffer from malnutrition will experience conditions of slowness in development, slowness in thinking, underweight and so on. Malnutrition can be prevented by complete immunization from birth, providing good nutrition for their development, and so on. The purpose of this study was to determine the results of the grouping of provinces with the highest malnutrition sufferers using the K-Medoids method which is part of Data Mining. The K-Medoids method is a clustering method that can break the dataset into several groups. In this study, the data used were sourced from the Central Statistics Agency in 2016 – 2018. The results of this clustering will later show the province which is the toddler with the highest malnutrition. This research is expected to provide information for the government regarding the grouping of children under five with malnutrition in Indonesia.

Application of the C4.5 Algorithm in Teaching Teachers' Skills on Learning Effectiveness Sari, Feby Widya; Safii, M.
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 1 (2021): October 2021
Publisher : Yayasan Kita Menulis

Teachers as educators and education personnel have a very important role in improving the quality of education in schools. In an effective teaching and learning process, teacher skills in teaching are very important. This study aims to classify the skills of teachers in SMA Yayasan Pendidikan Keluarga using the Decision Tree method with the application of the C4.5 Algorithm in order to improve the teaching system in an effort to increase students' understanding of the learning process. In determining the teaching skills of teachers, classification is carried out into the labels "Relevant" and "Not Relevant" which has 5 variables, namely Age, Length of Work, Number of Teaching Hours, Students, and Learning Media. Sources of data used in this study obtained by conducting observations and interviews.

Co-Authors Alfina, Ommi Ardilla, Ririn Arfika, Retno Belli Nasution Butarbutar, Ehrlich F.T Cut Irna Liyana Dewi, Rafiqa Eka Irawan Fitri Anggraini, Fitri Hambali, Humaidi Hartama, Dedy Irfan Sudahri Damanik Kartina, Anggriani Dwi Khusnul Khatimah Kiswara, Qodrat Lahilote, Abqoriy Hisan Lubis, Nur Azizah Muhammad Ridwan Lubis Napitupulu, Pretty Natalia Nasution, Mhd Aditia Puspita, Dahlia Rafai, Muhammad Ramadani, Saputra Rawinda Fitrotul Mualafina, Rawinda Fitrotul Renaldi Renaldi Rizki, Fahrizal RUSTAM, MUHAMMAD TAUFIQ Sari, Andini Fadila Sari, Feby Widya Siallagan, Sri Anita SIREGAR, ELIDA TUTI Solikhun Solikhun, Solikhun Suhendro, Dedi Sundari Retno Andani Syahputri, Nita Syaputri, Vera Trisno, Agus Wanto, Anjar

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