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All Journal International Journal of Electrical and Computer Engineering TEKNIK INFORMATIKA Jurnal Ilmiah Teknologi dan Rekayasa TELKOMNIKA (Telecommunication Computing Electronics and Control) CommIT (Communication & Information Technology) ComTech: Computer, Mathematics and Engineering Applications Jurnal Optimalisasi Indonesian Journal of Electrical Engineering and Computer Science Jurnal Ilmu Komputer dan Informatika

Suharjito Suharjito, Suharjito

Bina Nusantara University

Author-ID : 488965

Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics

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Mobile Decision Support System to Determine Toddler's Nutrition Using Fuzzy Sugeno Suharjito Suharjito; Jimmy Jimmy; Abba Suganda Girsang
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Determination of nutritional status is closely related to the determination of dietary patterns should be given to infants. Nutrition is very important role in mental, physical development, and human productivity. In this study, the system based on android is developed to determine the nutritional status of infants by using Fuzzy Sugeno. Indicator variables are age, height, circle head, and body weight according to the male or female. In this study, the results of measurements of nutritional status of children with Fuzzy Sugenoare tested by comparing the nutritional quality of the data Posyandu toddler by using anthropometric tables. The results of the evaluation measurement accuracy in this application are compared with the results of manual calculation based infant growth charts according to WHO standards. Therefore, these applications can be used to help the community in monitoring the nutritional status of children so that the growth of children is more appropriate in line with expectations.

Family Relationship Identification by Using Extract Feature of Gray Level Co-occurrence Matrix (GLCM) Based on Parents and Children Fingerprint Suharjito Suharjito; Bahtiar Imran; Abba Suganda Girsang
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

This study aims to find out the relations correspondence by using Gray Level Co-occurrence Matrix (GLCM) feature on parents and children finger print. The analysis is conducted by using the finger print of parents and family in one family There are 30 families used as sample with 3 finger print consists of mothers, fathers, and children finger print. Fingerprints data were taken by fingerprint digital persona u are u 4500 SDK. Data analysis is conducted by finding the correlation value between parents and children fingerprint by using correlation coefficient that gained from extract feature GLCM, both for similar family and different family. The study shows that the use of GLCM Extract Feature, normality data, and Correlation Coefficient could identify the correspondence relations between parents and children fingerprint on similar and different family. GLCM with four features (correlation, homogeneity, energy and contrast) are used to give good result. The four sides (0o, 45o, 90o and 135o) are used. It shows that side 0o gives the higher accurate identification compared to other sides.

Failure prediction of e-banking application system using adaptive neuro fuzzy inference system (ANFIS) Yuwono Abdillah; Suharjito Suharjito
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 1: February 2019
Publisher : Institute of Advanced Engineering and Science

Problems often faced by IT operation unit is the difficulty in determining the cause of the failure of an incident such as slowing access to the internet banking url, non-functioning of some features of m-banking or even the cessation of the entire e-banking service. The proposed method to modify ANFIS with Fuzzy C-Means Clustering (FCM) approach is applied to detect four typical kinds of faults that may happen in the e-banking system, which are application response times, transaction per second, server utilization and network performance. Input data is obtained from the e-banking monitoring results throughout 2017 that become data training and data testing. The study shows that an ANFIS modeling with FCM optimized input has a RMSE 0.006 and increased accuracy by 1.27% compared to ANFIS without FCM optimization.

Smart agriculture for optimizing photosynthesis using internet of things and fuzzy logic Abdul Latief Qohar; Suharjito Suharjito
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5467-5480

Photosynthesis is a process that plants need. Plant growth requires sunlight to carry out photosynthesis. At night photosynthesis cannot be carried out by plants. This research proposes an internet of things (IoT) model that can work intelligently to maximize photosynthesis and plant growth using fuzzy logic. The plants used in this research are mustard plants because mustard plants are plants that have broad leaves and require more photosynthesis. The outputs of this proposed model are the activation of light emitting diodes (LED) lights and automatic watering based on input sensors such as soil moisture, temperature, and light intensity which are processed with fuzzy logic. The results show that the use of the IoT model that has been proposed can provide faster and better growth of mustard plants compared with mustard plants without an IoT system and fuzzy logic. This result is also strengthened by comparing the t-test between the two groups, with a significant 95% confidence level. The proposed model in this research is also compared with similar research models carried out previously. This research resulted in a plant height difference of 30.43% higher than the previous research. So, it can conclude that the proposed model can accelerate the growth of mustard plants.

Co-Authors Abba Suganda Girsang, Abba Suganda Abdul Latief Qohar Abimanyu Dharma Poernomo Andika, Rizky Andriyansyah, Andriyansyah Arta, Mikhael Chandra Asroll, Muhammad Astrid Lestari Tungadi Aulia, Yunita Demi Adidrana Dian Puspita Tedjosurya, Dian Puspita Halim, Marwa Ida Ratna, Ida Imran, Bahtiar Indra Alfredo Ishartati Jimmy Jimmy Josef Bernadi, Josef Leonardus Hardjo, Leonardus Maulivia, Vivia Surya Muhammad Rifqi Nensi, Sri Wahyu Nico Surantha, Nico Nur Anwar, Nur Perdana, Panji Arief Putri, Yulia Aneke Raymond Raymond Rian Rassetiadi Stefani Agusta Tinambunan, Gusmariani Widodo, Bambang Yundari, Yundari Yuwono Abdillah

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