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INDONESIA
Faktor Exacta
Published by Universitas Indraprasta PGRI
ISSN : 1979276X     EISSN : 2502339X     DOI : -
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Industrial & Manufacturing Engineering
Faktor Exacta is a peer review journal in the field of informatics. This journal was published in March (March, June, September, December) by Institute for Research and Community Service, University of Indraprasta PGRI, Indonesia. All newspapers will be read blind. Accepted papers will be available online (free access) and print version.
Arjuna Subject : -
Articles 523 Documents
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KLASIFIKASI SENTIMEN MASYARAKAT TERHADAP KEBIJAKAN KARTU PEKERJA DI INDONESIA Winda Putri Anggraini; Manda Syari Utami
Faktor Exacta Vol 13, No 4 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i4.7964

Abstract

Masalah pengangguran merupakan salah satu masalah makro ekonomi yang menjadi penghambat dalam pembangunan suatu negara atau daerah. Tingkat Pengangguran Terbuka (TPT) sejak tahun 2011 dan awal tahun 2020 mengalami penurunan tetapi cenderung melambat. Padahal, pemerintah Indonesia melalui Badan Perencanaan Pembangunan Nasional (Bappenas) menargetkan tingkat pengangguran bisa makin mengecil menjadi di bawah 4% pada tahun 2024. Salah satu program pemerintah, yang dicanangkan sejak awal pemerintahan 2019, untuk mengurangi tingkat pengangguran adalah dengan menerbitkan kartu prakerja. Selain itu juga menjadi salah satu solusi untuk menstimulasi para pekerja yang di-PHK, ataupun orang-orang yang mengalami kesulitan mencari pekerjaan pada masa pandemi. Pro dan kontra mengenai kartu prakerja terus bergulir dalam berbagai macam media. Twitter menjadi salah satu media sosial yang digemari oleh banyak masyarakat dunia termasuk di Indonesia dalam menyampaikan aspirasi, kegemaran, dan pendapatnya. Pro kontra yang hangat dibincangkan di twitter mengenai kartu prakerja menjadi hal yang perlu diperhatikan untuk penyempurnaan kebijakan tersebut. Untuk menganalisis respon masyarakat dengan menggunakan data Twitter, dapat dilakukan dengan analisis sentiment menggunakan metode pengklasifikasian Naïve Bayes. Dari model pengklasifikasian data original, training ataupun testing diperoleh hasil persentase respon berupa sentimen negatif terkait kartu prakerja adalah 52.87% lebih besar dibandingkan persentase sentiment positif sebesar 47.13%. Dan juga didapatkan nilai akurasi sebesar 91.06% dari keseluruhan tweet yang diuji.
Membangun Pythagoras Sebagai Visualisasi Random Forest Untuk Pemodelan Pohon Keputusan Erlin Windia Ambarsari; Herlinda Herlinda
Faktor Exacta Vol 13, No 3 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i3.6513

Abstract

Students observed Pythagoras for using a plane Geometry and 3D Geometry. However, Pythagoras can also be built for decision trees. Our research regarding Instagram Usage Habit with construct Pythagoras for a single decision tree. The study's results obtained are ambiguous attribute values. Therefore, it is continued with research to build Pythagoras for Random Forest. The purpose of the study is to facilitate the tracking of ambiguous data contained in the attributes. The results obtained that the relationship between characteristics of the target class, thus resulting in misclassification. This error caused invalid data; for example, there are three times the separation of data on the same attribute for age's target for a group of 20. However, although there are misclassifications caused by invalid data, based on the Pythagorean construction for Random Forest, the data is more easily traced to errors, which cannot be done by a single decision tree.
Pengaruh Ukuran Partikel Dan Kristalit Terhadap Konduktivitas Listrik Bahan Bulk Ba(2-X)La(X)Fe2o5 (X = 0, 0.1, 0.3, Dan 0.5) Pada Suhu Kamar Sumaryo Sumaryo; Yosef Sarwanto
Faktor Exacta Vol 13, No 2 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i2.6583

Abstract

PENGARUH UKURAN PARTIKEL DAN KRISTALIT TERHADAP KONDUKTIVITAS LISTRIK BAHAN BULK Ba(2-x)La(x)Fe2O5 (x = 0, 0.1, 0.3, DAN 0.5) PADA SUHU KAMAR. Sintesis bulk Ba(2-x)La(x)Fe2O5 telah dilakukan melalui metode metalurgi serbuk. Bulk Ba(2-x)La(x)Fe2O5 dibuat dengan komposisi BaCO3, La2O3 dan Fe2O3 dengan perbandingan komposisi berat tertentu. Ketiga bahan tersebut dicampur dengan menggunakan alat high energy milling kemudian dicetak dalam bentuk pellet (bulk), selanjutnya dilakukan proses pemanasan pada suhu 950 oC selama 5 jam. Karakterisasi sample secara makroskopik diamati dengan mikroskop optic untuk melihat perubahan ukuran partikel terhadap perubahan komposisi. Analisa fasa dilakukan menggunakan XRD (Difraksi Sinar-X) untuk menentukan fasa yang terbentuk, ukuran grain dan microstrain. Sedangkan konduktivitas listrik dilakukan dengan menggunakan LCR meter. Hasil pengamatan makroskopik terlihat adanya perubahan ukuran partikel dengan perubahan komposisi bahan. Hasil analisis XRD menunjukkan bahwa terbentuk fasa dominan Ba2Fe2O5 dengan fasa minor La(OH)3. Ukuran kristalit dan microstrain bulk juga berubah terhadap perubahan komposisi. Hasil pengukuran sifat listrik berubah mengikuti perubahan ukuran partikel dan kristalit dari bahan bulk Ba(2-x)La(x)Fe2O5.Kata kunci: Bulk, Ba(2-x)La(x)Fe2O5, mikroskop optik, difraksi sinar-X, ukuran partikel, ukuran kristalit, dan konduktivitas listrik.
IMPLEMENTASI DEEP LEARNING MENGGUNAKAN CNN UNTUK SISTEM PENGENALAN WAJAH Noviana Dewi; Fiqih Ismawan
Faktor Exacta Vol 14, No 1 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i1.8989

Abstract

Face recognition system is generally divided into two stages, face detection system, which is a pre-processing step followed by a facial recognition system. This step will quickly be done by humans but it takes a long time for the computer. This ability of humans is what researchers want to duplicate in the last few years as biometric technology in computer vision to create a model of face recognition in computer. Deep learning becomes a spotlight in developing machine learning, the reason because deep learning has reached an extraordinary result in computer vision. Based on that, the author came up with an idea to create a face recognition system by implementing deep learning using the CNN method and applying library open face. The result of this research is applying deep learning with the CNN method to classification process that resulting percentage of precision of 96%, recall percentage of 100%, and accuracy percentage of 99.8%.
Analisis Dan Perancangan Simulasi Algoritma Paillier Cryptosystem Pada Pesan Text Dengan Presentation Format Binary, Octal, Hexadecimal dan Base64 Muhamad Femy Mulya; Nofita Rismawati; Dedy Trisanto
Faktor Exacta Vol 13, No 4 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i4.7429

Abstract

Abstrak. Setiap hari ratusan ribu orang yang berinteraksi secara elektronik, melalui media e-mail, e-commerce, mesin ATM ataupun telepon seluler. Peningkatan penyebaran informasi secara elektronik telah mengakibatkan ketergantungan yang meningkat terhadap kriptografi. Salah satu peranan dari kriptografi adalah untuk melakukan pengamanan data yaitu dengan menggunakan algoritma kriptografi. Algoritma paillier cryptosystem merupakan sebuah algoritma asimetris probabilistic untuk kriptografi kunci publik, algoritma paillier cryptosystem digunakan karena komputasi enkripsi dan dekripsi pada algoritma paillier cryptosystem cukup rumit, karena diperlukan dua kali operasi perpangkatan, satu kali operasi perkalian, dan satu kali operasi modulo. Dengan demikian tingkat keamanan algoritma paillier cryptosystem cukup baik. Tujuan dari penelitian ini adalah untuk menganalisa, merancang serta mengimplementasikan simulasi enkripsi dan dekripsi dari pesan text (berupa text writing maupun text file) menggunakan algoritma paillier cryptosystem dengan presentation format sebanyak 4 (empat) format yaitu, binary, octal, hexadecimal dan base64. Dengan demikian pesan text (berupa text writing maupun text file) akan lebih aman pada saat dikirimkan melalui email, sms maupun chatting dari pengirim ke penerima pesan. Adapun perangkat lunak (software) yang akan digunakan untuk membuat simulasi algoritma paillier cryptosystem ini menggunakan Cryptool2. Hasil penelitian menunjukkan bahwa presentation format binary menjadi yang tercepat untuk waktu (ms) proses enkripsi dan dekripsi, sedangkan Presentation format base64 menjadi yang terlama untuk waktu (ms) untuk proses enkripsi dan dekripsi. Kata Kunci: Kriptografi, Paillier Cryptosystem, Cryptool2  Abstract. Every day hundreds of thousands of people interact electronically, through e-mail, e-commerce, ATM machines or cell phones. The increase in the dissemination of information electronically has resulted in an increasing dependence on cryptography. One of the roles of cryptography is to secure data by using cryptographic algorithms. The paillier cryptosystem algorithm is an asymmetric probabilistic algorithm for public key cryptography, the paillier cryptosystem algorithm is used because the computation of encryption and decryption in the paillier cryptosystem algorithm is quite complicated, because it requires two power operations, one multiplication operation, and one modulo operation. Thus, the security level of the paillier cryptosystem algorithm is quite good. The purpose of this research is to analyze, design and implement simulation of encryption and decryption of text messages (in the form of text writing or text files) using the paillier cryptosystem algorithm with 4 (four) presentation formats, namely, binary, octal, hexadecimal and base64. Thus text messages (in the form of text writing or text files) will be safer when sent via email, sms or chat from sender to message recipient. The software that will be used to simulate the paillier cryptosystem algorithm uses Cryptool2. The results showed that the binary presentation format is the fastest for the encryption and decryption process time (ms), while the base64 presentation format is the longest for the time (ms) for the encryption and decryption process. Key words: Cryptography, Paillier Cryptosystem, Cryptool2
Processing The Ground Motion Signal Recording Using Correction Instrument Method Erna Kusuma Wati
Faktor Exacta Vol 14, No 2 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i2.8482

Abstract

The instrument correction method is a way to eliminate interference with the signal from the recording instrument response. Signal processing by the instrument correction method using the inverse filter method created using the MATLAB program. In this research using Honshu earthquake data, Japan with Mw 7.4 (dated September 5, 2004) recorded by the MERAMEX seismometer type L4C-3D type short seismometer and Japan Tohoku-Oki earthquake with a strength of Mw 9.0 (March 11, 2011) the data from four seismic stations in Padang, West Sumatra with a DS-4A type short-period seismometer. From the research known, the signal can clearly show the phase of the P and S waves. This can help to determine the parameters of the hypocenter, receiver function, moment tensors, studies of .  The surface wave phase can be reconstructed well. This is very useful for studies using surface wave data, moment tensor solutions, seismic wave dispersion studies. Based on the amplitude of the instrument correction results compared with theoretical data, the gain or amplification .
Implementasi Algoritma Naive Bayes, Support Vector Machine, dan K-Nearest Neighbors untuk Analisa Sentimen Aplikasi Halodoc Elly Indrayuni; Acmad Nurhadi; Dinar Ajeng Kristiyanti
Faktor Exacta Vol 14, No 2 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i2.9697

Abstract

During the Covid-19 pandemic, many people access information and even consult health problems online with the best doctors via smartphones. The Halodoc application is considered the most popular with 18 million users in 2020. So that many people have reviewed the application on the Google Play Store application provider. It may take a while to read the full review. However, if only a few comments are read, they are biased. For that, a platform is needed which can automatically identify positive or negative opinions. Sentiment analysis is a solution for the technique of classifying texts or sentiments into positive or negative opinion categories. The method used in this research is an experiment using the Naive Bayes algorithm, Support Vector Machine, and K-Nearest Neighbors. Evaluation is carried out using 10 Fold Cross-Validation. The results showed that K-Nearest Neighbors (KNN) had the best and most accurate performance in the sentiment classification because it produced the highest accuracy value of 95.00% and the largest AUC value of 0.985 compared to the Naive Bayes and Support Vector Machine algorithm.
Penerapan Digitalisasi Alur Bisnis Menggunakan Digital Signature Pada Salah Satu Bank di Indonesia Menggunakan Metode Scrum Elvan Mahardika Purnomo; Fenni Agustina
Faktor Exacta Vol 14, No 2 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i2.9330

Abstract

Technological developments have led the Bank to always develop innovations that can help customers and employees to be faster in all matters, including the validation of the User ID registration form. Form validation using an ordinary signature is what has been known so far. After that, the signed registration form is sent using the Tracking System and will be processed by the User ID Management Team by reprinting it and then being signed again by Hello, the Supervisor, and the Back Office from the User ID Management Team as a sign that the application is approved. This manual method can no longer be used during this pandemic due to limited work time, the workplace, and the possibility of contracting the virus through paper. The implementation of digitizing business process flows using a digital signature is one way that activities continue to run. The application for submitting the flow of forms to digital was developed for this, as well as the change of ordinary signatures to digital signatures. This study uses a system development method using the Scrum Model. The result of developing this system is the application of a digital signature and a role application so that each role has a different function and task in the application in the process of digitizing the User ID registration form.
Implementasi Metode K-Medoids Untuk Masalah Intrusion Detection System Menggunakan Bahasa Pemrograman Matlab Octaviani Hutapea; Aini Suri Talita
Faktor Exacta Vol 14, No 2 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i2.9429

Abstract

Based on data from the National Cyber And Crypto Agency (BSSN) of the Republic of Indonesia from 2018 to 2021, the threat of cyber attacks continues to experience a significant increase. In 2021, a significant change that is likely to be faced is with the emergence of new smart devices, which are more than just end-users and remotely connected networked devices. Surely, gives it the attention of all parties. There are many types of cyberattacks including Malware, Phishing, Ransomeware, etc. IDS (Intrusion Detection System) is a method that can detect suspicious activity in a system or network. Implementation of the Fuzzy K-Medoids method by using the Matlab programming language that retrieves data from KDDCUP’99 which has been normalized. The data used are normal data and anomaly attack data which are categorized as DoS, Probe, R2L, and U2R. From the research conducted the accuracy percentage is around 60-89% with three types of data preprocessing
Penerapan Metode Machine Learning untuk Prediksi Nasabah Potensial menggunakan Algoritma Klasifikasi Naïve Bayes Devi Fitrianah; Saruni Dwiasnati; Hanny Hikmayanti H; Kiki Ahmad Baihaqi
Faktor Exacta Vol 14, No 2 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i2.9297

Abstract

Customers are people who trust the management of their money in a bank or other financial service party to be used in banking business operations, thereby expecting a return in the form of money for their savings. To reach information to increase company profits, a method is needed to be able to provide knowledge in supporting the data that the company has. The model can be obtained by using predictive data processing of customer data that is categorized as potential or not potential. Data processing can be done using Machine Learning, namely classification techniques. This technique will produce a churn prediction model for determining the category of customers who fall into the Potential or Not Potential category and find out what accuracy value will be generated by applying the classification technique using the Naïve Bayes Algorithm. The parameters used in this study are Gender, Age, Marital Status, Dependent, Occupation, Region, Information. The data used are 150 data from customers who have participated in the savings program to find out whether the customer is in the Potential or Non-Potential category. The accuracy results generated using this data are 86.17% of the tools used by Rapidminner.

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