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INDONESIA
EXPLORER
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27744647     DOI : https://doi.org/10.47065/explorer.v2i1.148
Core Subject : Science,
Computer Science & IT
EXPLORER Journal of Computer Science and Information Technology is a scientific journal published by the FKPT (Forum Kerjasama Pendidikan Tinggi). This journal contains scientific papers from Academics, Researchers, and Practitioners about research on Computer Science and Information Technology. EXPLORER Journal of Computer Science and Information Technology is published twice a year in January and July. The paper is an original script and has a research base on Computer Science and Information Technology. The scope of the paper includes several studies but is not limited to the study Artificial Intelligence, Computer Graphics and Animation, Image Processing, Cryptography, Computer Network Security, Modelling and Simulation, Multimedia, Computer Architecture Design, Computer Vision and Robotics, Parallel and Distributed Computing, Operating System, Information System, Mobile Computing, Natural Language Processing, Data Mining, Machine Learning, Expert System and Geographical Information System. Thus, we invite Academics, Researchers, and Practitioners to participate in submitting their work to this journal.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 8 Documents
 1 
Search results for , issue "Vol 3 No 2 (2023): July 2023" : 8 Documents clear
Analytical Hierarchy Process (AHP) sebagai Sistem Penunjang Keputusan Penerimaan Dosen Hamsiah Hamsiah
Explorer Vol 3 No 2 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v3i2.686

Abstract

The selection of new lecturers for a tertiary institution is very important, because it forms the basis for the tertiary institution to have the best quality lecturers, so that they are able to transfer knowledge to students properly, so that the quality of the students produced is also better. In selecting lecturers according to the criteria, disagreements often occur between policy makers so that the results obtained are not in accordance with the goals that have been set. To overcome this, one way that can be applied is to apply a method, namely a decision support system using the Analytical Hierarchy Process (AHP). Education, TKDA, Microteaching, and interviews. The output of this study is a system that can provide alternative recommendations for lecturer acceptance with a consistency index, so that the hierarchy formed is acceptable. Implementation and testing of the system using the super decision application version 2.10. From the four alternative data tested, the best recommendation was Iin Syofia Yandra with a score of 0.37704818, followed by Dori H Putra with a score of 0.23819528
Aplikasi Ujian Tryout Berbasis Client Server Menggunakan Linier Congruent Method (LCM) Pada Sekolah Menengah Kejuruan Haida Dafitri; Rachmat Aulia; Ari Usman; Jihan Nabila Fathia
Explorer Vol 3 No 2 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v3i2.694

Abstract

Tryout in the scope of education in Indonesia is a trial that is usually carried out before facing the actual exam, or among students refers to a trial before facing a computer-based national exam (UNBK). The problem that has been identified is the implementation of the exam is still applying a traditional system that uses exam paper and fills in the answers themselves using pencils and pens. Therefore, this research focuses on designing a tryout exam application applying the linear congruent method held in schools, especially vocational high schools (SMK). This method is an algorithm used to generate random numbers. The function is to randomize questions, which can be defined as a mechanism for randomizing questions to create new questions that are different from the last. Hopefully, this application can help schools in terms of making, multiplying and distributing questions being tested. In addition, the results can be printed directly using a computer
Design of Postgraduate Thesis Exam Registration and Scheduling Information System For IAIN Palangka Raya Sapto Pamungkas; Suparno Suparno; Abdul Qodir; Pujiati Astuti; Mualimin Mualimin
Explorer Vol 3 No 2 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v3i2.695

Abstract

The design of an information system for registration and scheduling of postgraduate thesis exams at IAIN Palangka Raya is a system that will be built to make it easier for users to operate the system in managing thesis exams. This information system provides facilities to users who can interact in accordance with standard operating procedures according to user needs. As for the users involved in it, such as: students, academics, study programs and directors. This information system will contain activities starting from submitting a thesis title, determining a supervisor, making a supervisor's decision, thesis guidance, registration and scheduling of thesis proposal seminars as well as thesis examination seminars along with attached documents for each activity. The research method used is a structured method (waterfall model). This information system is designed and built usingCSS, Html, PHP, Auto Generate, Boostrrap and Mysql. The result of this research is the achievement of creating a web system that is expected to facilitate the management of registration and scheduling of quality thesis examinations at the Postgraduate IAIN Palangka Raya. Researchers also suggest that this research can be developed according to user needs
Pengamanan Kunci Pintu Brankas Menggunakan Kriptografi One Time Pad (OTP) Berbasis Android Munjiat Setiani Asih; Ade Zulkarnain Hasibuan
Explorer Vol 3 No 2 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v3i2.738

Abstract

A safe is a place used to store valuable items. Generally, safes use buttons to open the door. However, using buttons that only require entering a password is considered less secure. Therefore, a device has been created to enhance the security of the entered password. The device utilizes Arduino as the central data processing unit for user input and an Android smartphone as the device for entering the password. The security is implemented using the cryptographic technique known as One Time Pad, where the user is prompted to input the password to be used. During the password storage process, the password is encrypted before being stored. To use it, the user simply enters the stored password into the system. If the device is forcefully tampered with, a thief attempting to retrieve the password will be unable to understand the stored password within the device, as it has undergone encryption. With this dual security measure in place, it is expected that the safe will be even more secure.
Penggunaan Algoritma Naïve Bayes Untuk Menentukan Pemberian Kredit Pada Koperasi Desa Ika Nurjanah; Jamilah Karaman; Ida Widaningrum; Dyah Mustikasari; Sucipto Sucipto
Explorer Vol 3 No 2 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v3i2.766

Abstract

Giving credit to customers is a routine activity carried out by a cooperative, as happened in the Subur Sari Forest Village Community Institution Cooperative (LMDH) in Pudak Wetan Village, Ponorogo Regency. Non-performing or bad loans often occur due to a lack of thorough analysis in the credit granting process. This happens because the management is less careful in determining which applicants are eligible for loans. Therefore, customer eligibility analysis is fundamental in determining whether a customer is eligible or not to get a loan. One way to determine creditworthiness is to use the Naïve Bayes algorithm. This study aims to apply data mining methods to classify eligible, and ineligible customers based on historical customer data in the past then used to predict the feasibility of future customers using the Naïve Bayes algorithm. The results of testing the credit classification system using the black box stated that the system was able to run according to the algorithm and could determine whether or not the customer deserved credit.
Pengelompokan Bidang Usaha Terhadap Bantuan Produktif Usaha Mikro (BPUM) Berdasarkan Wilayah Deli Serdang Menggunakan Metode Clustering K-Means (Studi Kasus: Dinas Koperasi Dan UMKM Kabupaten Deli Serdang) Tiara Jelita; Relita Buaton; Magdalena Simanjuntak
Explorer Vol 3 No 2 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v3i2.783

Abstract

Micro Business Productive Assistance is a program that is assistance from the government to MSME workers throughout Indonesia. Every year, MSMEs can receive this assistance, without exception for those who have received it in previous years. The Office of Cooperatives and MSMEs of Deli Serdang Regency is a regional apparatus in North Sumatra Province which has the main task of carrying out government affairs in the field of cooperatives and small businesses including saving and loan business permits, empowerment and development of small businesses. Micro, Small and Medium Enterprises (MSMEs) are individual business entities which contributed significantly to increasing exports, increasing and equalizing income, forming national products and expanding employment opportunities. Based on these conditions, the authors provide a solution that needs to be built a clustering that can classify fields in each business owned by the community, because not all types of business fields in the community will receive this assistance, including agriculture and animal husbandry. Grouping data can apply the data mining process with the K-Means Algorithm clustering method which is a process of processing very large amounts of data using statistical methods, mathematics, and utilizing Artificial Intelligence technology to produce a group of data. By utilizing the data mining process using the clustering method, it is hoped that clustering can solve the problem of grouping business fields owned by the community. From the test results with 1004 data, which was carried out with MATLAB, it was found that group 1 had 383 data, group 2 had 261 data and group 3 had 360 data. Meanwhile, based on the results of the trial with RapidMiner, it was found that group 1 had 371 data, group 2 had 281 data and group 3 had 352 data.
Pengelompokan Data Mining Penerimaan Bantuan Pangan Non Tunai (BPNT) Menggunakan Metode Clustering (Studi Kasus : Kantor Desa Payabakung Hamparan Perak) Fany Juliawati; Relita Buaton; Rusmin Saragih
Explorer Vol 3 No 2 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v3i2.793

Abstract

Poverty is a problem that is often faced by various countries in the world, including Indonesia. In an effort to overcome poverty and increase people's access to food, in 2017 the Government gradually created a program that was formed to reduce the burden on the community in meeting basic needs, with the Non-Cash Food Assistance Program (BPNT). The problem is that the assistance provided has not been distributed on target / the distribution of assistance has not been objective, due to limited data and information obtained regarding families receiving BPNT assistance, so that families who should be entitled to receive assistance cannot receive assistance due to limited data available. Therefore, the village office is required to record again the families who are entitled to receive BPNT assistance with the existing criteria. The solution offered is to create a system of k-means that displays the clustering results of recipients of Non-Cash Food Assistance, by utilizing a number of data owned by the agency, it can be grouped using data mining technology. The benefit is that data mining can help agencies gain knowledge. by processing existing BPNT beneficiary data. The use of data mining techniques in grouping BPNT recipients is expected to be useful in facilitating the process of searching system data, which was previously still manual. The data group for recipients of Non-Cash Food Assistance (BPNT) in the work group (X) are private employees, for the income group (Y) are 1,400,001 – 1,700,000 and in the home status group (Z) are self-owned homes, and Centroid 2 ( 1,552,861.44), the data group for recipients of Non-Cash Food Assistance (BPNT) in the occupation group (X) is Plantation, for the income group (Y) is 800,001 – 1,100,000 and in the house status group (Z) is Owned house, and Centroid3 (4,592,351.64) data group for recipients of Non-Cash Food Assistance (BPNT) in the occupation group (X) is Labor, for the income group (Y) is 500,001 – 800,000 and in the house status group (Z) is Rent house.
Klasifikasi Data Penduduk Pada Pemilihan Umum Di Kota Binjai Menggunakan Algoritma K-Means (Studi Kasus : KPU Kota Binjai) Windy Indah Sary Sinaga; Relita Buaton; Hermansyah Sembiring
Explorer Vol 3 No 2 (2023): July 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v3i2.794

Abstract

Population growth is something that continues in an environment both in rural and urban areas. The rapidly increasing number of residents must be re-recorded in a government agency. Likewise, the Binjai City KPU Office must re-record population data, especially residents in the city of Binjai who have the right to carry out the General Election in 2024 by involving the community that has been previously recorded. Problems were also found with data on residents who had moved domiciles but their personal data had already been recorded for general elections in 2024. With that, data collection had to be re-done to select population data so as to produce a new population data status so that data was not found that did not match what it should be. By observing the problems above Data Mining with the Clustering method is very appropriate to be used to generate knowledge of new population data groups to carry out general elections at the KPU Binjai, using the MATLAB application is also very appropriate to choose in this problem so that it can produce output from data mining that can be used in future decision making. This study aims to process data to produce population data in the city of Binjai in the implementation of general elections, implement a system so that it can classify new population data in the middle of old population data and design data grouping in determining population data groups based on criteria conditions at the KPU Office in Binjai city. By using the clustering method that has been used to process population data at general elections in the city of Binjai, it can produce new information from 1000 data that has been tested. From 1000 population data for general elections in Binjai City, 3 clusters are obtained with the results of 7 tests where cluster 1 totals 225 data, cluster 2 has 436 data and cluster 3 has 339 data.

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