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All Journal Dinamik JURNAL SISTEM INFORMASI BISNIS Jurnal Simetris Telematika Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Register: Jurnal Ilmiah Teknologi Sistem Informasi E-Dimas: Jurnal Pengabdian kepada Masyarakat Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal Surya Masyarakat JSiI (Jurnal Sistem Informasi) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Aiti: Jurnal Teknologi Informasi Jurnal Surya Masyarakat Indonesian Journal of Technology, Informatics and Science (IJTIS) Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat Jurnal Abdimas Bina Bangsa SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Tematik Jurnal Informatika Polinema (JIP)

Agusta Praba Ristadi Pinem

Universitas Semarang

Author-ID : 2489343

Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Komparasi Metode ELECTRE, SMART dan ARAS Dalam Penentuan Prioritas RENAKSI Pasca Bencana Alam Agusta Praba Ristadi Pinem; Titis Handayani; Lenny Margaretta Huizen
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 1 (2020): Februari 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Each organization must collect data as a result of the use of information technology. Over time the data is processed into information. The information collected is used as a basis for decision making. But not all information can be directly used for the decision making process. Necessary methods and weighting in the process of getting information. One model in a decision support system is Multi Criteria Decision Making (MCDM). The MCDM model makes it possible to provide the best choice of information from several choices of the many criteria and alternatives used. This study compares the MCDM model, namely the ELECTRE (Elimination Et Choix Traduisant la Realite) method, SMART (Simple Multi-Attribute Rating Technique), ARAS (Additive Ratio Assessment) as a priority determination for the handling of areas affected by natural disasters which must be addressed first in the RENAKSI (Reconstruction and Rehabilitation Action Planning), in this case earthquake natural disasters. The ELECTRE method has a different algorithmic process than SMART and ARAS. The validation test method ELECTRE, SMART and ARAS against dataset occurrence of the earthquake is become the results of this research. Spearman rank correlation values for the three methods amounted to 0.96. And another correlation method value of 0.85 for the ARAS method and 0.82 for the ELECTRE and SMART methods.

Penentuan Lokasi Industri Menggunakan Metode WASPAS Dengan Data Spasial Sebagai Data Kriteria Agusta Praba Ristadi Pinem; Siti Asmiatun; Astrid Novita Putri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Today, the development of the use of spatial data is not only used for information geographic or transportation. But also can be used for site selection with integrating decision support system methods. Generated information can help in making decisions and meet the expected aspects. One method that can be used to support the decision making process is the Weighted Aggregated Sum Product Assessment (WASPAS). WASPAS is included in Multi Criteria Decision Making which can produce selected information from the data or criteria used. This study uses the WASPAS method as a determinant of strategic industrial locations by spatial data collection. In determining strategic industrial locations, WASPAS uses several different criteria and weights for each criterion. The WASPAS method can produce precise information related to the determination of strategic industrial locations. The results of the Spearman Rating trial with data on industrial locations in the city of Semarang show a strong conformity, as seen from the resulting compatibility value of 1.0. The results obtained from this study are the establishment of a system model that supports the decision to determine the location of the industry using the WASPAS method.

Pengenalan Karakter Optis untuk Pencatatan Meter Air dengan Long Short Term Memory Recurrent Neural Network Victor Utomo; Agusta Praba Ristadi Pinem; Bernadus Very Christoko
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Clean water service providers in Indonesia are still recording water meters as water usage data with manual recording by record collector. Alternative solutions for recording water meters from previous research use the Internet of Things (IoT) or image recognition that is processed on a server. The solutions rely on the Internet which is unsuitable with Indonesia’s condition. This study proposes a water meter reading system that can work on mobile devices without using the Internet. The system works by utilizing optical character recognition (OCR) using the Long Short Term Memory Recurrent Neural Network (LSTM-RNN) method. LSTM-RNN is a classification method in artificial neural network which has feedback. The results show that the water meter reading system could work without using an Internet connection. The average time it takes to perform the reading process is 2285ms even on Android device with low specification. The overall reading accuracy is 86%. Single value reading accuracy, when the digit meter displays only 1 number, is 97%, while the accuracy of double value reading, when the digit meter displays 2 numbers, is 18%.

Co-Authors Ahmad Muqoffa Aina, Mualina Nur Alif Catur Murti, Alif Catur Aria Hendrawan, Aria Astrid Novita Putri Astrid Novita Putri, Astrid Aulia Dewi, Elsa Adhista Basworo Ardi Pramono Bernadus Very Christoko Bima Aditya Mahendra Chintya, Bernika Cholil, Saifur Rohman Dewa Ramadhan Artagautama Dewi, Elsa Adhista Aulia Edi Widodo Edi Widodo, Edi Erlangga, Erwin Fadhil Naufal Mafino Novian Febrian Wahyu Christanto Firmansyah, Ariq Gita Aprinta, Gita Henny Indriyawati Huizen, Lenny Margaretta Imawan, Renvil Kholidin Kholidin Maheswara, Respati Dzaky Majid, Aldiansyah Fathul Nur Wakhidah Nurtriana Hidayati Prasetyo, Rizky Bayu Prind Triajeng Pungkasanti, Prind Triajeng Putra, Ardiansyah Cahya Putri Sinta Anggraeni Saifur Rohman Cholil Sapira, Septia Nike Bela Sari, Anggi Farika Sekar Sari, Mega Septianing, Rena Trinita Siti Asmiatun, Siti Soiful Hadi Sugiarti, Rini Susanto, Bagus Hadi Titis Handayani Vega, Jane Amalia Vensy Vydia Victor Gayuh Utomo Wicaksana, Dinar Anggit

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