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All Journal TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Jurnal Ilmiah Informatika dan Komputer
Derman Janner Lubis
Universitas Binaniaga Indonesia
Computer Science & IT Decision Sciences, Operations Research & Management Engineering

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Penerapan K-Means Untuk Pengelompokkan Beasiswa Santri di Pondok Pesantren Miftahul Huda Bogor Derman Janner Lubis; M Badru Tamam
Teknois : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 12, No 1 (2022): January
Publisher : Sekolah Tinggi Ilmu Komputer Binaniaga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v12i1.125

Abstract

Pada saat ini cerminan kualitas pendidikan terlihat dari tingginya tingkat keberhasilan dan rendahnya tingkat kegagalan santri di dunia pendidikan. Kriteria uuntuk menyeleksi santri calon penerima beasiswa salah satunya dilihat dari nilai akademik yang tinngi. Namun, yang selama ini ini terjadi tingginya nilai akademik yang tinggi, melainkan berasal dari luar nilai akademik yaitu nilai kepribadian. Hal ini dilakukan agar santri – santri dapat mendapatkan beasiswa sesuai dengan kemampuannya. Oleh karena itu, peneliti mencoba memberikan alternatif dalam proses pengelompokkan beasiswa dengan memilah variabel data nilai akademik dan data nilai kepribadian. Salah satu cara untuk menyeleksi santri untuk mendapatkan beasiswa adalah dengan melakukan segmentasi dengan mengelompokkan data berdasarkan kriteria tertentu. Algoritma K-Means Clustering adalah salah satu metode pengelompokkan yang dapat mengelompokkan objek – objek berdarkan kepmiripan sifat yang dimilikinya. Tujuan dari penelitian ini adalah untuk mengetahui penerapan metode Algoritma K-Means Clustering dalam menyeleksi santri untuk mendapatkan beasiswa di Pondok Pesantren Mifathul Huda Bogor. Penelitian ini sudah melakukan uji kelayakan pada aplikasi yang dibangun dengan nilai kelayakan sebesar 87,59%, bermakna aplikasi yang dibangun sangat layak dan juga sudah dilakukan pengukuran melalui MATLAB dengan Silhouette Index dengan nilai 0,7030 (Strong Structure). 
Penerapan Metode Naïve Bayes Untuk Rekomendasi Pemilihan Asisten Laboratorium Komputer Di Perguruan Tinggi Derman Janner Lubis; Alfia Istiari Ningtiyas
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 12, No 2 (2022): Volume 12, No 2 (2022): July
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v12i2.138

Abstract

Binaniaga Indonesia University is one of the universities in the city of Bogor, just like other university in the learning process, computer laboratory assistants are often found whose job is to assist in providing appropriate directions to students who have difficulty during learning. Based on the results of interviews that have been conducted, there are indications that students who have been selected to become computer, laboratory assistants in the previous period, namely their performance is less than optimal, seen in daily life when assisting practicum courses in the computer laboratory, namely not providing the direction needed by practitioners who experience obstacles or difficulties, and also not optimal in terms of time while working in the computer laboratory. in this study, it can provide recommendations for selection of computer laboratory assistants to minimize errors in choosing computer laboratory assistants by applying the Naive Bayes method. The variables use is based on academic fields such as attendance, GPA (Gradual Achievement Index), the value of programming fundamentals courses, the value of programming language 1 or web systems and technology courses, and semester. The percentage of accuracy test results obtained by using the confussion matrix is the accuracy of 95.31%.
Penerapan Algoritma Naïve Bayes Untuk Penentuan Balita Penerima Makanan Tambahan (PMT) Berdasarkan Status Gizi Di Pos Pelayanan Terpadu (POSYANDU) Derman Janner Lubis; Gemilang Karunia Gusti
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 1 (2023)
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i1.177

Abstract

This study aims to determine toddlers who are classified as toddlers who are eligible to receive assistance as recipients of additional food (PMT) based on the nutritional status of toddlers. A toddler does not get nutrition in a balanced amount, malnutrition can occur, and the toddler himself will have stunted growth, so the problem I raised is that toddlers who are affected by malnutrition will be assisted by the Health and Posyandu in the Supplementary Feeding program (PMT) so that the nutrition of infants affected by malnutrition can be assisted in their recovery. This research was carried out from April to June 2022, located at Posyandu Melati, Kelurahan Margatunggal, Kecamatan Jayaloka, Musi-Rawas, South Sumatra. In this research, an application is made that can provide determination of eligible toddlers as recipients of additional food (PMT) to minimize errors in choosing toddlers who deserve this assistance by applying the Naive Bayes method. The variables used were based on the nutritional status of toddlers such as gender, nutritional status, weight based on age, nutritional status, height based on age, nutritional status, weight based on height, status of toddlers receiving additional food. % and is interpreted as very feasible while the results of the user eligibility percentage are 88.48%, then related to the application made can be categorized into a very feasible interpretation. And an accuracy test has also been carried out using a confusion matrix with 96% accuracy results.
Penerapan Metode TOPSIS Untuk Menentukan Penerima Bantuan Santri Kurang Mampu Pada Lembaga Pendidikan Islam Pondok Pesantren Qoif Sahroni; Derman Janner Lubis
TeknoIS : Jurnal Ilmiah Teknologi Informasi dan Sains Vol 13, No 2 (2023): July
Publisher : Universitas Binaniaga Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36350/jbs.v13i2.211

Abstract

In The educational unit is one of the tools to achieve educational goals in Indonesia. Most educational institutions in Indonesia are still experiencing some problems in selecting candidates for assistance, because they are still evaluating in a conventional way so that it is feared that the recipients of the assistance will be students or students not fairly and appropriately. target. Therefore, it is necessary to create a Decision Support System for Recipients of Santri or Student Assistance, to determine which students or students fall within the criteria for being eligible to receive such assistance. The criteria used are 6 criteria, namely parents' income, crafts, type of floor of the house, average report card score, parents' occupation, and vehicle ownership. Making this system uses the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, which is a decision-making method with a hierarchical structure, which is indeed included in the Multi Criteria Decision Making (MCDM).
Implementasi Algoritma Random Forest Untuk Optimasi Keamanan Autentikasi One-Time Password (OTP) Derman Janner Lubis; Andri, Andri Nova Riswanto
Jurnal Ilmiah Informatika dan Komputer Vol. 1 No. 1 (2024): Juni 2024
Publisher : CV.RIZANIA MEDIA PRATAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69533/eyp7ag46

Abstract

Penelitian ini berfokus pada optimasi keamanan autentikasi One-Time Password (OTP) melalui implementasi algoritma Random Forest. Tujuan utamanya adalah mengembangkan sistem deteksi dan pencegahan penipuan OTP yang efisien dan efektif. Dengan menggunakan model 4D (Define, Design, Development, and Dissemination) dan pendekatan throwaway prototyping, penelitian ini menghasilkan sistem yang sesuai dengan kebutuhan pengguna dan berfungsi optimal dalam penggunaan nyata. Hasilnya menunjukkan bahwa integrasi algoritma Random Forest dalam mekanisme OTP meningkatkan keamanan secara signifikan.Uji akurasi klasifikasi sistem mencapai skor akurasi sebesar 98.5%, menegaskan efektivitas metode yang digunakan dalam mendeteksi dan mencegah penipuan OTP.
Co-Authors Alfia Istiari Ningtiyas Andri, Andri Nova Riswanto Gemilang Karunia Gusti M Badru Tamam Qoif Sahroni