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All Journal Jupiter Techno.Com: Jurnal Teknologi Informasi Jurnal TIMES Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) IJCIT (Indonesian Journal on Computer and Information Technology) Jurnal Ilmiah FIFO Jurnal Sisfokom (Sistem Informasi dan Komputer) Jiko (Jurnal Informatika dan komputer) JSiI (Jurnal Sistem Informasi) Jurnal ICT : Information Communication & Technology SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Pendidikan dan Teknologi Indonesia Jurnal Abdimas Sangkabira Jurnal Mahasiswa Sistem Informasi (JMSI) Kresna: Jurnal Riset dan Pengabdian Masyarakat Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Eduvest - Journal of Universal Studies OKTAL : Jurnal Ilmu Komputer dan Sains Artinara Radiant : Journal of Applied, Social, and Education Studies Jurnal Ilmu Komputer Journal of Computer Science Advancements

Ruwirohi, Jan Everhard

Universitas Budi Luhur

Author-ID : 2490827

Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Neuroscience Social Sciences Other

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Sistem Pendukung Keputusan Penerima Bantuan Stimulan Perumahan Swadaya Dengan Metode AHP Dan Topsis Tobias Duha; Jan Everhard Ruwirohi
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 6, No 1 (2021): IJCIT - Mei 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Penentuan penerimaan bantuan stimulan perumahan swadaya (BSPS) yang dilakukan oleh Dinas Perumahan Rakyat dan Kawasan Permukiman Kabupaten Nias Selatan masih menggunakan random sampling sehingga penentuannya seringkali tidak objektif. Penulis mengusulkan metode pemilihan menggunakan sistem pendukung keputusandengan metode AHP (Analytical Hierarchy Process) dan TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). Metode AHP dan TOPSIS merupakan salah satu metode pengambilan keputusan multi kriteria dengan menerapkan bobot nilai pada setiap kriterianya. Tujuan penelitian ini untuk mempermudah Kepala Dinas Perumahan Rakyat dan Kawasan Permukiman Kabupaten Nias Selatan dan fasilitator dalam menentukan penerima bantuan rumah layak huni secara objektif. Metode AHP dan TOPSIS diaplikasikan dengan menyesuaikan hasil obeservasi dan kebutuhan Dinas Perumahan Rakyat dan Kawasan Permukiman Kabupaten Nias Selatan. Hasil penelitian ini menunjukkan penerapan metode AHP dan TOPSIS pada sistem pendukung keputusan penentuan penerima bantuan stimulan perumahan swadaya di dinas perumahan rakyat dan kawasan pemukiman Kabupaten Nias Selatan dengan nilai rata-rata 91,01%. Determination of the acceptance of self-help housing stimulant assistance (BSPS) carried out by the public housing and settlement areas of South Nias regency still uses random sampling so that the determination is often not objective. The authors propose a selection method using Decision Support System (DSS) with AHP (Analytical Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. AHP and TOPSIS methods a multi-criteria decision-making method by applying a weighted value to each criterion. The purpose of this research is to make it easier for the Head of the Department of Public Housing and Settlement Areas of South Nias Regency and facilitators in determining the recipients of housing assistance objectively. The AHP and Topsis methods are applied by adjusting on the results of observations and the needs of the Public Housing and Residential Areas of South Nias Regency. The results of this study indicate the application of the AHP and TOPSIS methods to the decision support system for determining the recipients of self-help housing stimulant assistance in the public housing service and residential areas of South Nias Regency with an average value of 91.01%.

Sistem Pendukung Keputusan Kinerja Karyawan Tenaga Kependidikan Terbaik Dengan Metode Simple Additive Weighting (SAW) Dan Metode Kano Studi Kasus Universitas Mercu Buana Namin Namin; Jan Everhard
Jurnal Ilmiah FIFO Vol 12, No 1 (2020)
Publisher : Fakultas Ilmu Komputer

Abstract Selection of the best performance education staff employees in tertiary institutions whose results are beneficial for advancing academic and institutional quality improvement. The selection of employees performing the best performance at Mercu Buana University is conducted every academic year. In the assessment process still uses the Excel application so it is less effective and accurate. Based on this in this study built a decision support system that is used for the selection process for selecting the best employee performance. Processing these values requires a Decission Support System (DSS) application to help process these values and make ranking and weighting so that leaders are faster and easier in making the best employee performance selection decisions. Decision support system that is used by the Simple Additive Weighting (SAW) and Kano method. absolute optimal requirements for orientation of the process of developing academic and institutional quality activities. The Decission Support System (DSS) application is expected to be able to assist the Information Technology (IT) division in selecting the best employee performance education staff that truly meets the required criteria and solving problems in selecting the best employee performance.Keywords: The selection of the best educational staff employee performance using the SAW and Kano methods Abstrak Pemilihan karyawan tenaga kependidikan kinerja terbaik di perguruan tinggi yang hasilnya bermanfaat bagi kemajuan peningkatan kualitas akademik dan kelembagaan. Pemilihan karyawan tenaga kependidkan kinerja terbaik di Universitas Mercu Buana dilakukan setiap tahunn akademik. Dalam proses penilaian masih menggunakan aplikasi excel sehingga kurang efektif dan akurat. Berdasarkan hal tersebut pada penelitian ini dibangun sistem pendukung keputusan yang digunakan untuk proses seleksi pemilihan kinerja karyawan tenaga kependidikan terbaik. Pengolahan nilai-nilai tersebut diperlukan sebuah aplikasi Decission Support System (DSS) untuk membantu mengolah nilai tersebut dan melakukan perankingan dan bobot sehingga pimpinan lebih cepat dan mudah dalam pengambilan keputusan seleksi kinerja karyawan tenaga kependidikan terbaik. Sistem pendukung keputusan yang digunakan dengan metode Simple Additive Weighting (SAW) dan Kano., Metode SAW ini digunakan untuk menentukan nilai kriteria, yang kemudian dilakukan proses bobot dan perangkingan untuk menentukan alternatif terbaik dan metode Kano untuk menentukan nilai secara individu untuk kepuasan karyawan dan menciptakan syarat mutlak yang optimal untuk orientasi proses aktivitas pengembangan kualitas akademik dan kelembagaan. Aplikasi Decission Support System (DSS) diharapkan dapat membantu divisi Information Technology ( IT ) dalam memilih karyawan tenaga kependidikan kinerja karyawan terbaik yang benar-benar sesuai dengan kriteria yang dibutuhkan dan memecahkan masalah dalam seleksi kinerja karyawan terbaikKata kunci: Pemilihan kinerja karyawan tenaga kependidikan terbaik dengan metode SAW dan Kano

Quality Test of Flexible Flat Cable (FFC) with Short Open Test Using Law Ohm Approach through Embedded Fuzzy Logic Based on Open Source Arduino Data Logger Ajar Rohmanu; Yan Everhard
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 3: EECSI 2016
Publisher : IAES Indonesia Section

A technological development, especially in the field of electronics is very fast. One of the developments in the electronics hardware device is Flexible Flat Cable (FFC), which serves as a media liaison between the main boards with other hardware parts. The production of Flexible Flat Cable (FFC) will go through the process of testing and measuring of the quality Flexible Flat Cable (FFC). Currently, the testing and measurement is still done manually by observing the Light Emitting Diode (LED) by the operator, so there were many problems. This study will be made of test quality Flexible Flat Cable (FFC) computationally utilize Open Source Embedded System. The method used is the measurement with Short Open Test method using Ohm's Law approach to 4-wire (Kelvin) and fuzzy logic as a decision maker measurement results based on Open Source Arduino Data Logger. This system uses a sensor current INA219 as a sensor to read the voltage value thus obtained resistance value Flexible Flat Cable (FFC). To get a good system we will do the Black-box testing as well as testing the accuracy and precision with the standard deviation method. In testing the system using three models samples were obtained the test results in the form of standard deviation for the first model of 1.921 second model of 4.567 and 6.300 for the third model. While the value of the Standard Error of Mean (SEM) for the first model of the model 0.304 second at 0.736 and 0.996 of the third model. In testing this system, we will also obtain the average value of the measurement tolerance resistance values for the first model of - 3.50% 4.45% second model and the third model of 5.18% with the standard measurement of prisoners and improve productivity becomes 118.33%. From the results of the testing system is expected to improve the quality and productivity in the process of testing Flexible Flat Cable (FFC).

Prediction of Water Levels on Peatland using Deep Learning Namora; Jan Everhard Riwurohi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 2 (2022): April 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The water level on peatlands is one of the causes of peatland fires, so water levels must be maintained at a safe standard value. Government Regulation No. 71/2014 stipulates water level standard value is 0.4 meters. The forest and land fires in 2015 caused huge losses of 220 trillion Rupiah. However, fires still occur frequently. BRGM (Peatland and Mangrove Restoration Agency) installed sensors measuring peatland water levels to obtain real-time data. These data can be used to predict water levels. Several previous studies used drought indices, regression models, and artificial neural networks to predict water levels. In this study, it is proposed to use deep learning Long Short-Term Memory (LSTM), and apply the CRISP-DM methodology. The dataset in this study contains water level data from 15 measurement stations in Central Kalimantan from 2018 through 2021. It was concluded that the LSTM model could predict water level well, as indicated by the average RMSE of 0.07 m, the average R2 of 0.85, and the average MAE of 0.04 m. The optimal LSTM model parameters are 50 epochs, a 70%:30% ratio of training data to testing data, and two hidden layers.

PREDIKSI JUMLAH PENDAFTAR HAJI LANJUT USIA MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION nurhanudin nurhanudin; Jan Everhard Riwurohi
JIKO (Jurnal Informatika dan Komputer) Vol 4, No 2 (2021)
Publisher : Journal Of Informatics and Computer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/jiko.v4i2.3138

Tingginya animo masyarakat muslim Indonesia untuk mendaftar haji ditandai dengan meningkatnya jumlah pendaftar haji dari tahun ke tahun. Hal ini menyebabkan antrian keberangkatan haji semakin panjang termasuk bagi Jemaah Haji lanjut usia. Undang-Undang Nomor 8 Tahun 2019 tentang Penyelenggaraan Ibadah Haji dan Umrah mengamanatkan memberikan prioritas kuota persentase tertentu bagi Jemaah Haji lanjut usia untuk berangkat haji. Permasalahan yang terjadi adalah belum adanya data prediksi pendaftar haji lanjut usia setiap tahun yang digunakan sebagai salah satu pertimbangan penetapan kuota bagi Jemaah Haji lanjut usia agar tidak terlalu lama menunggu. Penelitian ini bertujuan mengetahui model jaringan syaraf tiruan backpropagation yang tepat untuk memprediksi jumlah pendaftar haji lanjut usia. Penelitian dilakukan dengan mengubah jumlah node hidden layer untuk mendapatkan model terbaik, penelitian menggunakan data pendaftar haji lanjut usia periode tahun 2004 sampai dengan 2019. Data dibagi menjadi 2 bagian yaitu data latih (2004 sampai dengan 2014) dan data uji (2009 sampai dengan 2019). Berdasarkan hasil pelatihan, model yang terbaik adalah 10-7-1 dengan nilai MSE sebesar 0,000998514, nilai MAPE sebesar 9,8% dan akurasi sebesar 90,20%. Hasil prediksi pendaftar haji lanjut usia tahun 2020 dengan menggunakan model 10-7-1 adalah 5.124 pendaftar haji lanjut usia. Dengan dibangunnya model prediksi pendaftar haji lanjut usia maka pengambil kebijakan mudah mendapatkan data prediksi jumlah pendaftar haji lanjut usia setiap tahun dan hasil prediksi dapat digunakan untuk menetapkan kuota bagi Jemaah Haji lanjut usia sehingga antrian keberangkatan bagi Jemaah Haji lanjut usia tidak terlalu lama.

SISTEM KONTROL DAN MONITORING MENGGUNAKAN ARDUINO Diana Juwi Megatarini; Yan Everhard
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 1 No 2 (2018): Jurnal SKANIKA Mei 2018
Publisher : Fakultas Teknologi Informasi, Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.953 KB)

Berdasarkan judul diatas, karya tulis ini bertujuan untuk membuat sistem kontrol dan monitoring mobil yang dikontrol mengunakan perangkat android dan dimonitor menggunakan komputer yang sudah terhubung pada jaringan wifi. Permasalahan kendaraan yang sering ada pada keadaan berbahaya, lokasi real time kendaraan, penerapan Bluetooth dan WiFi sebagai koneksi penghubung antara sistem dan perangkat lainnya, dan penggunaan wearable device seperti android menjadi dasar dari projek ini. Alat yang dibuat ini bertujuan untuk melakukan perintah berupa gerak mobil beserta ubah arah, dan melakukan pengereman otomatis jika di depan atau samping kanan kiri kendaran didapati keadaan berbahaya seperti kendaran yang rem mendadak di depannya atau objek lain pada kanan dan kiri mobil, adapun sensor yang digunakan pada alat ini adalah ultrasonik sebagai sensor jarak, perangkat android sebagai controller dari sistem ini dengan Bluetooth sebagai koneksi antara android dengan mobil, dan juga ESP WiFi sebagai koneksi antara mobil dan juga komputer yang berfungsi untuk memonitoring pergerakan dari mobil. Pada perancangan sistem ini terbagi menjadi dua bagian yaitu perancangan perangkat keras dan perangkat lunak. Perangkat keras dari alat ini terdiri dari mikrokontroller, rangkaian relay, wifi, Bluetooth, motor Servo dan ultrasonik. Sedangkan perangkat lunak didesain menggunakan bahasa C Arduino IDE untuk memberikan intruksi intruksi pada Mikrokontroller ATMega2560 (Arduino Mega 2560) untuk mengoperasikan sistem kerja alat.

Aplikasi Pengecekan Suhu Dan Penyemprotan Disinfektan Secara Otomatis Berbasis Nodemcu Dengan Telegram Maulana Malik Ibrahim; Yani Prabowo; Wisjnuadji TW; Yan Everhard; M Anif; Siswanto Siswanto
Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Vol 18, No 1 (2021): APRIL 2021
Publisher : Universitas Budi Luhur

During the current covid-19 pandemic, maintaining health and hygiene is very important for human life, in order to avoid various diseases, such as corona covid-19. One of the protocols imposed by the government is for people who are active in public spaces or open facilities by wearing masks, checking their body temperatures and spraying disinfectants. The problem so far is that there is no automatic disinfectant spraying tool that is very useful for the community during the covid-19 pandemic, in order to reduce appropriate and economical human interaction. detects the presence of humans or objects that are in front of them to become a condition of opening and closing the bars based on the NodeMCU microcontroller with notification and control via telegram messages. Body temperature data will also be displayed on the LCD contained in this tool and sent via telegram to the supervisory officer. Prevention efforts by monitoring body temperature and spraying alcohol-based disinfectants can be applied. The test results of the DS18B20 temperature sensor application can measure human temperature between 370C–390C and the infrared sensor can detect the presence of humans or objects in front of them to open the bars and spray disinfectant

PENGENALAN DAN PELATIHAN LAPORAN KEUANGAN PADA RT.06 RW.10 MERUYA UTARA, KECAMATAN KEMBANGAN Triana Anggraini; Devit Setiono; Rusdah Rusdah; Dewi Kusumaningsih; Ahmad Pudoli; Jan Everhard Riwurohi
Jurnal Abdimas Sangkabira Vol. 3 No. 1 (2022): Jurnal Abdimas Sangkabira, Desember 2022
Publisher : Program Studi Diploma III Akuntansi Fakultas Ekonomi dan Bisnis Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/abdimassangkabira.v3i1.290

Prilaku manajemen merupakan salah prilaku penting dalam mencapai kesejatheraan finansial, tidak hanya secara individu tetapi juga dalam suatu organisasi. Dengan hadirnya teknologi, pencatatan keuangan menjadi lebih mudah, namun jika tidak diimbangi dengan pengetahuan dan keterampilan yang cukup maka akan menjadi kendala tersendiri. Setiap bulan RT.06 RW.10, Meruya Utara mendapatkan pemasukan untuk kas RT yang nantinya akan digunakan sebagai dana operasional dan penunjang disetiap kegiatan. Dalam prakteknya, pencatatan pemasukan dan pengeluran di lingkungan RT. 10 dilakukan hanya sebatas pencatatan pada buku kecil dan tidak terstruktur, hal ini menyebabkan seringnya tercadi kesalahan pada saat pembuatan laporan bulanan. Hasil dari pelatihan pembuatan laporan keuangan ini adalah peserta dapat pengelompokan secara terstruktur dan rapi terkait dengan pemasukan dan pengeluran kas setiap bulanya. Manfaat lain yang diperoleh oleh peserta pelatihan adalah peserta dapat meilhat aliran alokasi dana per pos kegiatan disetiap bulanya.

PERBANDINGAN OPTIMIZER, BATCH SIZE DAN EPOCH PADA METODE CONVOLUTION NEURAL NETWORK Ramadhan, Ferry Muhamad; Riwurohi, Jan Everhard; Gunawan, Hendry
Jurnal Sistem Informasi Vol 11 No 2 (2024)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsii.v11i2.9249

Buffalo meat and beef are two types of red meat that are widely consumed by the public. The demand for meat increases every year. However, not all types of meat can be eaten by Indonesians, such as pork, so the price of pork in Indonesia is lower than the price of beef and buffalo. In general, the texture and colour of pork, beef and buffalo are almost the same. In the introduction of meat, it is only done directly from the colour, texture, and fibre of the type of meat. However, meat circulating in the community is often mixed between beef, buffalo meat and pork. Distinguishing beef, buffalo and pork must first recognise the characteristics of each type of meat, because there are limitations to the human sense of sight in distinguishing between them. In the use of technology with the help of digital images to determine the most optimal optimizer, batch size and epoch in meat classification, using the Convolutional Neural Network (CNN) method with NasNetmobil Architecture. The data set used is 3000 images divided into three classes, with a division of 2400 training data images, 300 testing data images, 300 validation data images. The results showed that the Adam optimiser, batch size 62 and epoch 20 produced an accuracy of 99.00% and a loss value of 0.0243. Keywords: Convolutional Neural Network, Buffalo and Beef Classification,

Forecasting the Electricity Consumptions of PLN UP3 Cengkareng using Deep Learning Dewi, Novia; Riwurohi, Jan Everhard
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 1 (2024): MARET
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i1.1849

The consumption of electrical energy for the community every year has increased including the electricity consumption of PLN UP3 Cengkareng customers. Therefore, PLN UP3 Cengkareng must supply electricity to customers in all categories such as Social Category, Household Category, Business Category, Industry Category and Government Category. With customer needs that continue to increase, it is necessary to forecast future electricity needs, so that PLN UP3 Cengkareng can provide the required electrical power. For this reason, it is necessary to predict the electricity demand. This research was conducted to forecast the electricity demand of UP3 Cengkareng by using the Deep Learning Model Long Short-Term Memory (LSTM). The data set used in this study was taken from the PLN UP3 Cengkareng information system, for 10 years, the period from 2012 to 2021. The data used is divided into 2 categories, namely 70% training data and 30% testing data. The results obtained from this prediction are 96,689, with an average neuron value of 32 and an epoch value of 10.

Co-Authors Adelin, Adelin Ady Wisma Putra Wardana Agnes Aryasanti Ajar Rohmanu Akbar, Victor Ansor, Mohamad Zakaria Arachman, Setyo Arief Ari Kusuma, Dyah Topan Arsanto Narendro Aryasanti, Agnes Bagus T Prabawa Bima Cahya Putra Bonie Wijaya Budiarto, Despiyan Dwi Daffa Putra David Jefri Aruan Devit Setiono Dhamma Nagara Dian Anubhakti Diana Juwi Megatarini Eka Hartati Fuad Hasan Hambali, Yusuf Hardjianto, Mardi Hastomo, Mursid Dwi Hendarin, Hendarin Hendra Effendi Hendry Gunawan, Hendry Jeremy Jonathan K, Irvan K, Johanes H Kusumaningsih, Dewi M. Anif Maria Veronica Masad, Muhamad Masruin Maulana Malik Ibrahim Miftahudin . Mohamad Ridwan Mohammad Syafrullah Muhammad Fahrizal Muhrodi Namin Namin Namora Novia Dewi Nugraha Abdullah, Indra nurhanudin nurhanudin Oktora, Andre Prasasti Alam, Raden Gesit Presdianto, Eko Pudoli, Ahmad Purwanto Purwanto Putri Hayati Ramadhan, Ferry Muhamad Ratna Kusumawardani, Ratna Roeswidiah, Ririt Rohmanu, Ajar Rusdah Rusdah Samidi Samidi Samsinar Samsinar Siswanto, Siswanto Sriyeni, Yesi Sudija, Ija Suwasti Broto Tatang Wirawan Wisjhnuadji Tatang Wirawan Wisnuadji Tobias Duha Triana Anggraini Triana Anggraini Tutik Sri Susilowati Windihastuti, Wiwin Wisjnuadji TW Yani Prabowo Yulianawati

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