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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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Implementasi Graph Clustering Algorithm Modification Maximum Standard Deviation Reduction (MMSDR) dalam Clustering Provinsi di Indonesia Menurut Indikator Kesejahteraan Rakyat Nurfidah Dwitiyanti; Septian Wulandari; Noni Selvia
Faktor Exacta Vol 13, No 2 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i2.5863

Abstract

The population of Indonesia from year to year has increased. The increase in population must also be accompanied by increased economic growth in Indonesia. The increase in economic growth in Indonesia is marked by the reduction in the number of poor people in Indonesia. In addition, the increase in economic growth is reflected in the equitable distribution of public income in the country. Even though there are still many Indonesian people who are not yet prosperous in economic terms. To overcome, it is necessary to have clustering and characteristics of 34 provinces in Indonesia by implementing the Modification Maximum Standard Deviation Reduction (MMSDR) graph clustering algorithm. The data used are indicators of public welfare in 2017 obtained from the Central Statistics Agency. There are 9 indicators of community welfare used in this research. There are four stages in the MMSDR algorithm namely the "MST", "Subdivide", "Biggest Stepping" and "Create Clusters" processes. The results of this study can be seen from the distance between the nodes or between one province and another province produced 22 clusters. From the cluster results obtained using the MMSDR algorithm on welfare data, there are many clusters formed with cluster members formed at most two nodes (province). Keywords: MMSDR, Clustering, Welfare of People
EVALUASI KUALITAS APLIKASI SISTEM INFORMASI MANAJEMEN KEIMIGRASIAN (SIMKIM) VERSI 2.0 BERBASIS WEB MENGGUNAKAN METODE HUMAN ORGANIZATION TECHNOLOGY FIT (Studi Kasus pada Kantor Imigrasi) Arham Bakri; Anggraeni Ridwan
Faktor Exacta Vol 14, No 1 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i1.8630

Abstract

Immigration office one of the organization implementing information system integration and automation called the immigration management information system (SIMKIM) Version 2.0 for passport services. An evaluation need to find how the system is implemented, the level of success, as far as to which the system contributes to the organizations that use it. SIMKIM Version 2.0 application have three main component namely human organization and technology. The result of the evaluation indicate technology component include system quality getting value 3,24 (good), information quality getting value 3,09 (good), and service quality getting value 3,21 (good). Human component including system user getting value 3,18 (good), user satisfaction getting value 3,07 (good), and the benefits getting value 3,15 (good), and organization structure getting value 3,22 (good). The overall component SIMKIM Version 2.0 implementation obtained value of 3,16 good interpretation based on HOT Fit method.
PROTOTYPE SISTEM KENDALI ROBOT ARM GRIPPER MANIPULATOR MENGGUNAKAN FLEX SENSOR DAN MPU6050 BERBASIS INTERNET OF THINGS Habib Nurfaizal; Makhsun Makhsun; Yan Mitha Djaksana
Faktor Exacta Vol 13, No 4 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i4.6598

Abstract

In this sophisticated era a lot of human work that has begun to be done by robots. Robots are used to facilitate work that can not be done by humans, such as moving an item in a dangerous place. One of the robots created to facilitate human work is a robot that has a shape like a human arm called the arm gripper manipulator. Arm gripper manipulator is a robot that has the ability to move like a human arm. The manipulator arm consists of joint, link, and end-effector. This research designed a control system of the robot arm gripper manipulator with 2 modes, gesture mode and IoT mode. The microcontroller used is Arduino Mega 2560 with flex sensor control and MPU 6050 inertia measurement unit sensor in gesture mode and IoT control mode with time average errors in 5 movements is 2.08%. The overall test results of the robot arm gripper manipulator can be controlled with gesture mode and IoT mode.Abstract. In this sophisticated era a lot of human work that has begun to be done by robots. Robots are used to facilitate work that can not be done by humans, such as moving an item in a dangerous place. One of the robots created to facilitate human work is a robot that has a shape like a human arm called the arm gripper manipulator. Arm gripper manipulator is a robot that has the ability to move like a human arm. The manipulator arm consists of joint, link, and end-effector. This research designed a control system of the robot arm gripper manipulator with 2 modes, gesture mode and IoT mode. The microcontroller used is Arduino Mega 2560 with flex sensor control and MPU 6050 inertia measurement unit sensor in gesture mode and IoT control mode with time average errors in 5 movements is 2.08%. The overall test results of the robot arm gripper manipulator can be controlled with gesture mode and IoT mode.
Pengembangan Alat Deteksi Dini Asap Dan Kebocoran Gas Pada Tabung Lpg, Pencegah Kebakaran Skala Rumah Tangga Agung Wahyudi Biantoro; Rini Anggraini; Subekti Subekti
Faktor Exacta Vol 13, No 2 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i2.6587

Abstract

Saat penggunaan bahan bakar gas dinilai lebih efisien daripada bahan bakar dari fosil.  Namun, demikian, penggunaan bahan bakar gas dapat berdampak negatif terhadap keselamatan manusia bahkan menimbulkan kerugian yang cukup besar apabila tidak digunakan dengan hati-hati, terutama bila tidak diketahui telah terjadi adanya asap dan kebocoran dari tabung dan menyebabkan kebakaran, khususnya pada skala industri kecil dan skala rumah tangga.  Bila anggota rumah tangga tidak ada di ruangan tersebut maka sulit untuk mendeteksi kebocoran gas yang ada di dapur.  Gas  BBG terkenal dengan sifatnya yang mudah terbakar sehingga kebocoran peralatan BBG beresiko tinggi terhadap kebakaran. Tujuan dari penelitian ini adalah untuk merancang pembuatan dan alat pendeteksi asap dan gas untuk mendeteksi kebocoran gas pada skala rumah tangga.  Metode yang digunakan adalah pembuatan alat sistem pendeteksi asap dan kebocoran gas otomatis, dengan menggunakan mikrokontroller, Arduino Uno. Perlunya dibuatkan sistem yang mendukung mekanisme monitoring real time dan dapat memberikan peringatan dan notifikasi berbasis media suara (alarm) dan lampu led.  Kesimpulan adalah bahwa alat pendeteksi kebocoran gas ini  dapat bekerja dengan baik, ini ditunjukkan dengan berfungsinya alat saat diberikan percobaan asap dalam berbagai konsentrasi dan jarak. Buzzer berbunyi, lampu LED hijau menyala dan menampilkan data grafik pada android. Selanjutnya sensor akan mendeteksi adanya asap dan apabila di sekitar ruang misalnya ruangan dapur terdapat kandungan asap.  Konsentrasi dimulai dari 0 ppm, lalu pada konsentrasi 600 ppm yang kemudian meningkat menjadi 650, 700 dan 900 ppm.  Pada konsentrasi asap 600 ppm alat berfungsi dengan baik, dengan aktifnya alarm buzzer dan lampu led.   Alat deteksi Asap ini dapat juga digunakan untuk deteksi gas seperti gas Butane dan dapat ditaruh di ruangan yang rawan kebakaran misalnya ruangan dapur, sedangkan layar led dapat ditaruh di lokasi di ruang yang sering dilalui oleh anggota rumah tangga.
Pendekatan HOT-Fit dalam Evaluasi Sistem Informasi Manajemen Penyelesaian Laporan (SIMPeL) pada Lembaga Ombudsman Republik Indonesia Andriyani, Meilianti; Umniati, Naeli
Faktor Exacta Vol 13, No 4 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i4.7715

Abstract

SIMPeL is a system owned by ORI to facilitate the process of completing reports and improving public services. The increasing number of incoming public service maladministration reports is a challenge for ORI, especially how to monitor the number of incoming reports quickly and make the handling of reporting (complaints) integrated. This research uses the HOT-FIT analysis method to determine influence of Human components, Organization, and Technology influences on the utilization (Net Benefit) of SIMPeL in ORI office. The number of respondents in this study was 79 respondents SIMPeL users who are staff or assistants at representative offices and ORI headquarters. The data in this study were analyzed with the help of the SmartPLS program. The results of the study show that simultaneously humans, organizations, and technology are components that affect the utilization (Net Benefit) of SIMPeL in ORI. The effect of human, organizational, and technological components on SIMPeL utilization was 37.8% while the remaining 62.2% variance in SIMPeL utilization was influenced by other factors outside the three components. Partially, human and technology can also affect the utilization (Net Benefit) of SIMPeL in ORI, while organizational components are not an influential factor in the utilization of SIMPeL in ORI.
Orkestrasi Cloud Dengan Chef, Menuju Keselarasan Sistem Otomasi Teknologi Informasi Suryo Bramasto; Melani Indriasari; Endang Ratnawati D.
Faktor Exacta Vol 13, No 3 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i3.6426

Abstract

Abstrak. Penelitian pada artikel ini mengimplementasikan orkestrasi dari otomasi layanan-layanan teknologi informasi berbasis cloud,  yang mana dari sisi pengguna merupakan solusi-solusi bisnis. Orkestrasi dilakukan dengan salah satu mesin orkestrasi yakni Chef. Layanan-layanan teknologi informasi yang otomasi pembangunan dan pengelolaannya pada cloud diorkestrasi dengan Chef dibangun dengan web server Apache, database server MySQL, dan load balancer Nginx. Orkestrasi dilakukan dengan membangun arsitektur mesin orkestrasi spesifik yakni Chef pada layanan cloud AWS (Amazon Web Services), kemudian membuat recipes dan cookbooks pada Chef yang berisi perintah-perintah otomasi dan orkestrasi layanan-layanan teknologi informasi. Orkestrasi memungkinkan sebagian besar pekerjaan dari system administrator untuk dilakukan secara otomatis bahkan pada layanan-layanan IT berbasis Cloud yang kompleks, dengan tetap memungkinkan untuk dilakukan pengelolaan layanan sebagaimana yang biasa dilakukan oleh system administrator pada sub-sub sistem dari layanan-layanan IT. Selain itu orkestrasi pada implementasinya akan sangat mendukung pendekatan DevOps pada rancang bangun piranti lunak sebagai sub sistem utama dari layanan IT. Kata Kunci: Chef, cloud, DevOps, orkestrasi, otomasi
Perbandingan Metode Average Linkage, Complete Linkage, dan Ward’S pada Pengelompokan Kabupaten/Kota di Provinsi Jawa Tengah Berdasarkan Indikator Indeks Pembangunan Manusia Edy Widodo; Syinta Nuri Mashita; Yosi Ghea Prasetyowati
Faktor Exacta Vol 13, No 2 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i2.6581

Abstract

Provinsi Jawa Tengah merupakan salah satu provinsi yang mempunyai prestasi kinerja yang signifikan. Hal tersebut dapat diketahui berdasarkan nilai pertumbuhan ekonomi Provinsi Jawa Tengah sebesar 5,28%. Pertumbuhan ekonomi di Jawa Tengah belum mencapai nilai yang maksimal hal ini dikarenakan belum meratanya tingkat perekonomian di beberapa wilayah di Provinsi Jawa Tengah. Indeks Pembanguan Manusia (IPM) adalah pengukuran perbandingan dari harapan hidup, melek huruf, pendidikan dan standar hidup untuk semua negara di seluruh dunia. IPM  juga merupakan  suatu  tolak  ukur maju  atau  tidaknya  suatu  wilayah ataupun  daerah,  karena  dengan  tingkat  IPM  yang  tinggi  suatu  daerah  akan dikatakan berhasil dalam program pembangunannya. Analisis pengelompokkan adalah suatu metode untuk mengelompokan n objek berdasarkan p variat yang memiliki kesamaan karakteristik diantara objek-objek. Penelitian ini membandingkan 3 metode pengelompokkan yaitu average linkage, complete linkage,  dan ward’s yang bertujuan untuk mengelompokkan kabupaten/kota di provinsi Jawa Tengah berdasarkan data indikator IPM tahun 2018. Hasil dari penelitian menunjukkan metode pengelompokkan Average Linkage adalah yang terbaik dengan nilai korelasi cophenetic sebesar 0.865. Jumlah kelompok optimum didapatkan 3 kelompok dengan nilai indeks Calinzki Harabas sebesar 117.213. Metode cluster hierarki average linkage menghasilkan 3 kelompok, yaitu kelompok dengan kategori rendah sebanyak 20 kabupaten/kota, kelompok dengan kategori sedang sebanyak 12 kabupaten/kota dan kelompok dengan kategori tinggi sebanyak 3 kabupaten/kota. Hasil pengelompokan divisualisasikan dengan pemetaan pengelompokan kabupaten/kota di provinsi Jawa Tengah berdasarkan indikator IPM tahun 2018.
ANALISIS KLASIFIKASI POPULASI TERNAK KAMBING DAN DOMBA DENGAN MODEL CONVOLUTIONAL NEURAL NETWORK Alusyanti Primawati; Intan Mutia; Dwi Marlina
Faktor Exacta Vol 14, No 1 (2021)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v14i1.8734

Abstract

The number of goat populations is increasing all over the world. Sheep and goats are economically potential for business development because they do not require large areas of land, relatively small investment in business capital, and are easy to market. However, the similarities between goats and sheep can make small breeders who are just starting out in business nervous. Therefore, in goats and sheep, an intensive and efficient Precision Livestock Farming system is required. To answer this problem, goat and sheep objects was studied out using the collaboration software programming R and Python which executed in RStudio editor and Anaconda3 with the Tensor flow package. The sample data of 40 images. The model obtained from the classification results uses 20 pictures of goats and 20 pictures of sheep for training and testing. The accuracy produced shows that the prediction of training data at epoch 70 and 100 has the right accuracy with the actual data. This reinforces that the model used is good (fit) to the training dataset, but when it is applied to the testing dataset, the prediction results are still close to perfect. Epoch 70 identifies there is 1 image of a Goat which is recognized as Lamb.
Analisis Sentimen Pengguna Marketplace Bukalapak dan Tokopedia di Twitter Menggunakan Machine Learning Irwansyah Saputra; RAHMAD SINGGIH AJI PAMBUDI; HANAFI EKO DARONO; FACHRI AMSURY; MUHAMMAD RIZKI FAHDIA; BENNI RAMADHAN; ANGGIE ARDIANSYAH
Faktor Exacta Vol 13, No 4 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i4.7074

Abstract

      A collection of tweets from Twitter users about Marketplace Bukalapak and Tokopedia can be used as a sentiment analysis. The data obtained is processed using data mining techniques, in which there is a process of mining the text, tokenize, transformation, classification, stem, etc. Then calculated into three different algorithms to be compared, the algorithm used is the Decision Tree, K-NN, and Naïve Bayes Classifier with the aim of finding the best accuracy. Rapidminer application is also used to facilitate writers in processing data. The highest results from this study are Decision Tree algorithm with 82% accuracy, 81.95% precision and 86% recall.
Penerapan Teknik Clustering Data Mining untuk Memprediksi Kesesuaian Jurusan Siswa (Studi Kasus SMA PGRI 1 Subang) Tubagus Riko Rivanthio; Mardhiya Ramdhani; Ahmad Sahi
Faktor Exacta Vol 13, No 2 (2020)
Publisher : LPPM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/faktorexacta.v13i2.6588

Abstract

SMA PGRI 1 Subang is a private school that has several missions, one of which is the establishment of academic and non-academic achievements. In an effort to achieve the mission must supervise student achievement. The effort he did was to provide understanding in the selection of majors in accordance with the interests and talents of students. But in the activity of providing understanding, the school does not yet have a model that can evaluate the interests and talents of students to choose majors. The model can be obtained using student data processing. Data processing can be done using data mining, namely data mining clustering techniques. The technique will produce a model in the selection of majors. This clustering process is the process of grouping similar data based on the similarity of data held by students. The research method used is the CRISP-DM method which has 6 stages consisting of: Business Understanding, Data Understanding, Data Processing, Modeling, Evaluation, and Dissemination. The data that is processed is 620 data consisting of class of students in 2014, 2015, 2016. The results of processing using clustering obtained 6 clusters that have different models for each cluster. The results of this study can be used by schools in recommending courses chosen by students according to students' interests and talents, so students can learn optimally.Key words: clustering, dataMining, suitability, majors, students

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