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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) ComEngApp : Computer Engineering and Applications Journal Jurnal Pendidikan Sosiologi dan Humaniora Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal KALAM Analisis: Jurnal Studi Keislaman Jurnal Script Jurnal Fisika Unand Jurnal Informatika dan Teknik Elektro Terapan JAWI : Journal of Southeast Asia Islamic Contemporary Issues Jurnal Fisika FLUX Al-Adyan: Jurnal Studi Lintas Agama Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Reka Buana : Jurnal Ilmiah Teknik Sipil dan Teknik Kimia Jurnal Kreativitas PKM Indonesian Physical Review Jurnal Pembelajaran Pemberdayaan Masyarakat (JP2M) Community Development Journal: Jurnal Pengabdian Masyarakat Spektrum Sipil Jurnal Generic Reputasi: Jurnal Rekayasa Perangkat Lunak Al-Iftah: Journal of Islamic studies and society Innovative: Journal Of Social Science Research ABDIKOM Socio Religia
Ahmad Zarkasi
Jurnal Studi Lintas Agama
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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PENERAPAN SISTEM PENDUKUNG KEPUTUSAN METODE FUZZY TSUKAMOTO DALAM PENGOPTIMALAN PRODUKSI BARANG BERDASARKAN DATA PERSEDIAAN DAN JUMLAH PERMINTAAN DI LOVERANDLIARS CLOTH Zarkasi, Ahmad; Widyastuti, Naniek; Kumalasari, Erna
Jurnal Script Vol 3, No 1 (2015): EDISI DESEMBER 2015
Publisher : Jurnal Script

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Abstract

ABSTRACTWith the development of science and technology, the use of computer services in all aspects of life already is a necessity, especially in industry. Loverandliars engaged in the production of goods, depending on sales and demand for individual and inter-industry. This thesis discusses the application of fuzzy logic in solving optimization of production amount, in this case using Tsukamoto method and the method of Mamdani and Sugeno method as a comparison. From this method is expected to estimate the amount of production and sales is based on the number of requests that are applied in a decision support system. Enough so that in making decisions with input data required by DSS (Decision Support System), to be processed by the method Tsukamoto to be output (output) in the form of the determination of the amount of goods to be produced. The first step problem solving optimization Tsukamoto products by using the method of determining the variables that are firmly set, the second step is to convert the input into a set of fuzzy variables with fuzzification process, the third step is a data processing method Fuzzy set minimum and maximum. In the process variable input data using an application supporting the Netbeans 8.0 editor. From the analysis of direct comparison with the original data in the calculation of production at the company Loverandliars can be concluded that the method that most closely is the truth value of production obtained by processing the data using the method Tsukamoto.Keywords: DSS, Tsukamoto, Mamdani dan Sugeno, Production, Fuzzy.
A new system for underwater vehicle balancing control based on weightless neural network and fuzzy logic methods Zarkasi, Ahmad; Satria, Hadipurnawan; Primanita, Anggina; Abdurahman, Abdurahman; Afifah, Nurul; Sutarno, Sutarno
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 13, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v13.i3.pp2870-2882

Abstract

The utilization of humans to be in the water for short time, resulting in limited area underwater that can be explored, so the information obtained is very limited, plus the influence of irregular water movements, changes in waves, and changes in water pressure, indirectly also constitutes obstacle to this problem. One of the best solutions is to develop underwater vessel that can travel either autonomously or by giving control of movement and navigation systems. New system for underwater vehicle balance control through weightless neural network (WNN) and fuzzy logic methods was proposed in this study. The aim was to simplify complicated data source on stability system using WNN algorithm and determine depth level of autonomous underwater vehicle (AUV) through fuzzy logic method. Moreover, speed control of underwater vehicle was determined using fuzzy rule-based design and inference. The tests were conducted by showing convergence performance of system in the form of AUV simulator. The results showed that proposed system could produce real-time motion balance performance, faster execution time, and good level of accuracy. This study was expected to produce real-time motion balance system with better performance, faster execution time, and good level of accuracy which could be subsequently used to design simple, cheap, and efficient hardware prototype.
The Eye and Nose Identification Chip Controller-Based on Robot Vision Using Weightless Neural Network Method Zarkasi, Ahmad; Ubaya, Huda; Exaudi, Kemahyanto; Fitriyanto, Megi
Computer Engineering and Applications Journal Vol 13 No 03 (2024)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v13i03.615

Abstract

Increasingly advanced image analysis in computer vision, allowing computers to interpret, identify, and analyze pictures with accuracy comparable to humans. The availability of data sources in decimal, hexadecimal, or binary forms enables researchers to take the initiative in applying their study findings. Decimal formats are typically used on traditional computers like desktops and minicomputers, whereas hexadecimal and binary formats were utilized on single-chip controllers. Weightless Neural Network is a method that can be implemented in a single chip controller. The aim of this research is to develop a facial recognition system, for eye and mouth identification, that works in a single chip controller or also called a microcontroller. The suggested method is a Weightless Neural Network with Immediate Scan approach for processing and identifying eye and nose patterns. The data will be handled in many memory locations that are specifically designed to handle massive volumes of data. The data is made up of primary face data sheets and face input data. The data sets utilized are (x,y) pixels, and frame sizes range from 90x90 pixels to 110x110 pixels. Each face shot will be processed by selecting the region of the eyes and nose and saving it as an image file. The eye and nose will identify the face frame. Next, the photos will be converted to binary format. A magazine matrix will be used to transmit binary data from a minicomputer to a microcontroller via serial connection. Based on a known pattern, the resultant similarity accuracy is 83,08% for the eye and 84,09% for the sternum. In contrast, the similarity percentage for an eye ranges from 70% to 85% for an undefined pattern.
Sistem Deteksi Kematangan Buah Pisang Berdasarkan Warna Kulit Menggunakan Metode HSV Zarkasi, Ahmad; Y. A. P, Kadek Dwivayana; Ubaya, Huda; Afifah, Nurul; Heriyanto, Ahmad; Sazaki, Yoppy; -, Abdurahman -
Generic Vol 16 No 1 (2024): Vol 16, No 1 (2024)
Publisher : Fakultas Ilmu Komputer, Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/generic.v16i1.178

Abstract

Pengolahan citra digital merupakan teknik manipulasi citra secara digital yang khususnya menggunakan komputer menjadi citra lain yang sesuai dengan kebutuhan. Klasifikasi kematangan pisang dapat dilakukan dengan dua cara, yaitu dengan menggunakan kandungan nutrisi dan tingkat kematangan warna pisang. Penelitian ini pengusulkan pendeteksian kematangan buah pisang berdasarkan warna kulit, dengan menggunakan metode ruang warna HSV (Hue, Saturation, Value). Komponen prosesor utama menggunakan Raspberry Pi 3B sebagai pengolah data Raspberry Pi Camera V2 sebagai penangkap citra buah pisang. Hasil penelitian ini berupa sistem bisa membedakan warna dari buah pisang yang berada dalam satu frame. Hasil yang diperoleh adalah , nilai efektif HSV yang didapat dari pengujian deteksi warna kuning kulit buah pisang adalah Hmin 15, Hmax 40-60, Smin 100, Smax 255, Vmin 60, dan Vmax 255. Dengan nilai HSV tersebut didapatkan nilai rata-rata keberhasilan sebesar 55%.
An Internet of Things (IoT)-based Microclimate Parameter Measurement Tool (Temperature, Humidity, and Sunlight Intensity) for Coastal Areas Zarkasi, Ahmad; Nurhanafi, Kholis; Syahrir, Syahrir
Jurnal Fisika Flux: Jurnal Ilmiah Fisika FMIPA Universitas Lambung Mangkurat Vol 21, No 1 (2024): Jurnal Fisika Flux: Jurnal Ilmiah Fisika FMIPA Universitas Lambung Mangkurat
Publisher : Lambung Mangkurat University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/flux.v21i1.17929

Abstract

Climate parameters such as temperature, humidity, and solar light intensity can affect various things in the environment and its components such as vegetation, animals, and humans. In this research, an internet of things (IoT)-based climate parameter measurement tool has been created. The use of IoT systems offers flexibility and ease of access for observers to conduct monitoring. The designed measuring instrument has been tested and compared with a standardized measuring instrument, namely the Mastech MS6300 Environment Multitester. The test results show accuracy values of 97.1%, 95.1%, and 87.2% for temperature, humidity, and sunlight intensity measurements, respectively. The results of the measuring instrument design are implemented in coastal areas (beaches). From the results obtained, the three parameters measured tend to be stable in the morning, afternoon, and evening. Meanwhile, during the afternoon the measured climate parameters are quite fluctuating. In general, the designed measuring instrument has been able to work well and is feasible to be implemented directly.
The Role of Pesantren in Shaping the Social-Religious Identity of the Community (Studi of Pesantren Al-Amin Nusantara Bumi Nabung) Amanda, Anggun Diah; Salim, Luthfi; Zarkasi, Ahmad
Jurnal Pendidikan Sosiologi dan Humaniora Vol 16, No 1 (2025): April 2025
Publisher : Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/j-psh.v16i1.90248

Abstract

Islamic boarding scholls as educational institutions play a role in shaping the religious social identity of the community. In life, social identity is something significant and inherent to a person. This can take the form of beliefs, desires, and principles of action that distinguish him from others. Religious social identitiy is formed not only through the art of calligraphy. This research attemps to examine the process of forming the religious social identity of the community at the Al-Amin Nusantara Islamic boarding school and the implications of this religious social identity in the community"™s life. This research uses a qualitative type of study that is descriptive in nature with a sociologica approach. The data collection techniques were carried out using purposive sampling techniques by determining key informants, primary informat sources, and additional informan. In data analysis, it it carried out through three stages data production, data presentation, and data verification. From this research, it was found that traditional Islamic boarding schools in the archipelago can shape the social-religious identity of the community in terms of religious knowledge, socio-religious values, and daily practices. The social-religious identity formed form calligraphy art activities can influence community life by fostering independence. In this regard, it is hoped that Al-Amin Nusantara Islamic boarding school will continue to actively engage in activities with the community.
The Memory Efficiency in a Receptionist Robot's Face Recognition System Using LBPH Algorithm Yudi, Endang Darmawan; Yesi Novaria Kunang; Zarkasi, Ahmad
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 6 (2024): December 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i6.6048

Abstract

This research aims to develop a memory-efficient face recognition system for a receptionist robot using the Local Binary Patterns Histogram (LBPH) algorithm. Given the computational limitations of the Raspberry Pi, the system utilizes optimization techniques including grayscale conversion, noise reduction, and contrast adjustment to enhance processing efficiency. Testing demonstrates that the face recognition accuracy achieves 80.5% to 85.5% in offline mode, and 72% to 81% in real-time mode, with variations due to lighting conditions and facial expressions. The robot's servo motors exhibit a response time between 1.945 and 3.561 seconds, enabling responsive and interactive user engagement. The results suggest practical benefits for deploying face recognition in resource-constrained environments, enhancing the efficiency of robotic receptionist applications.
Performance Comparison of Feature Face Detection Algorithm on The Embedded Platform Zarkasi, Ahmad; Nurmaini, Siti; Stiawan, Deris; Suprapto, Bhakti Yudho; Ubaya, Huda; Kurniati, Rizki
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 2 (2022)
Publisher : Universitas Sriwijaya

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Abstract

The intensity of light will greatly affect every process carried out in image processing, especially facial images. It is important to analyze how the performance of each face detection method when tested at several lighting levels. In face detection, various methods can be used and have been tested. The FLP method automates the identification of the location of facial points. The Fisherface method reduces the dimensions obtained from PCA calculations. The LBPH method converts the texture of a face image into a binary value, while the WNNs method uses RAM to process image data, using the WiSARD architecture. This study proposes a technique for testing the effect of light on the performance of face detection methods, on an embedded platform. The highest accuracy was achieved by the LBPH and WNNs methods with an accuracy value of 98% at a lighting level of 400 lx. Meanwhile, at the lowest lighting level of 175 lx, all methods have a fairly good level of accuracy, which is between 75% to 83%.
Robot Vision Pattern Recognition of the Eye and Nose Using the Local Binary Pattern Histogram Method Zarkasi, Ahmad; Ubaya, Huda; Exaudi, Kemahyanto; Almuqsit, Alif; Arsalan, Osvari
Computer Engineering and Applications Journal (ComEngApp) Vol. 12 No. 3 (2023)
Publisher : Universitas Sriwijaya

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Abstract

The local binary pattern histogram (LBPH) algorithm is a computer technique that can detect a person's face based on information stored in a database (trained model). In this research, the LBPH approach is applied for face recognition combined with the embedded platform on the actuator system. This application will be incorporated into the robot's control and processing center, which consists of a Raspberry Pi and Arduino board. The robot will be equipped with a program that can identify and recognize a human's face based on information from the person's eyes and nose. Based on the results of facial feature identification testing, the eyes were recognized 131 times (87.33%), and the nose 133 times (88.67%) out of 150 image data samples. From the test results, an accuracy rate of 88%, the partition rate of 95.23%, the recall of 30%, the specificity of 99%, and the F1-Score of 57.5% were obtained.
Implementation of Weightless Neural Network in Embedded Face Recognition for Eye and Nose Pattern Mobile Identification Zarkasi, Ahmad; Exaudi, Kemahyanto; Sazaki, Yoppy; Romadhona, Londa Arrahmando
Computer Engineering and Applications Journal (ComEngApp) Vol. 14 No. 2 (2025)
Publisher : Universitas Sriwijaya

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Abstract

The pattern of the human face is a form of self-identity and also a form of originality for each individual. The development of facial recognition technology impacts its application in various computing devices, both in computer vision and on single-chip processors. One of the continuously developed implementations is in the form of robot vision by identifying facial features. This research aims to develop a facial recognition system focusing on the identification of the eye and nose areas. This research utilizes the Weightless Neural Network (WNN) method with the Immediate Scan technique. The combination of methods allows for rapid and accurate pattern recognition, even when the face changes position. The detection process is carried out using the Haar Cascade Classifier algorithm, which functions to recognize faces and divides the area into nine different zones to ensure accurate identification. The hardware implementation was carried out on a Raspberry Pi for face detection and facial pattern recognition, as well as the data processor for the robot vision sensor and actuator on the microcontroller. The results of the robot's movement testing have worked well according to the calculation of GPS data values to determine the robot's last position. Then, in the face pattern recognition process, it shows that the proposed method can achieve a maximum accuracy level of up to 98.87% in testing with the internal data set, while testing under different conditions experiences a slight decrease in accuracy to 91.38%. The highest similarity percentage to the faces of other individuals reached 75.69%, indicating that this method is quite adaptive to various facial variations. The execution time of the identification process ranges from 11 ms to 17 ms, depending on the amount of data compared during the scanning. This research is expected to serve as a foundation for further development in robotics systems and embedded system-based facial recognition.
Co-Authors -, Abdurahman - Abdurahman Abdurahman Adi Hermansyah, Adi Aditya Yoga Purnama Adrianus Inu Natalisanto Adryan Fitrayudha Agustam Agustam Ain, Hurun Almuqsit, Alif Amanda, Anggun Diah Amelia, Dinda Risky Amirin Kusmiran Andi Eka Putra Anwar Efendy Aroby, Sudhan Athalaza, Muhammad Nawar Aulia Muttaqin Bhakti Yudho Suprapto Bintar Asror Syaffutra Cahya, Serdian Eska Deris Stiawan Dhiafah Hera Darayani Duri, Ades Harafi Ellya Rosana Erna Kumalasari Erni Yustissiani Fadli Isnanto, Rahmat Fariyadin, M. Ruslin Anwar, Indradi Wijatmiko, Adiman Fitriyanto, Megi Ghofar Taufiq Hadi Purnawan Satria Hadipurnawan Satria Hamdani, Hafiz Hananda Putra, Muhammad Fauzan Hariyadi, Hariyadi Hasan, Aly Heni Pujiastuti Heriyanto, Ahmad Heru, M. Hidayat, Ahmad Taufiq Hidayatullah, Muhammad Huda Ubaya Idris Mandang, Idris Idrus Ruslan Intifadhah, Sahara Hamas Isfanari Isfanari Joni Safaat Adiansyah Kalsum, Afif Umi Kemahyanto Exaudi Kholis Nurhanafi Kurniati, Rizki Melan Susanti, Melan Mislan Muh. Deni Kurniawan Muhammad Afif Munir, Rahmawati Naniek Widyastuti Ni Nyoman Kencanawati Novianti, Intan Nugroho Budi Wibowo Nuraidha, Amalia C Nurul Hidayati Osvari Arsalan P.P Prasetyo, Aditya Primanita, Anggina Putra, Lalu Lunk Ryanata Rahayu, Rafika Ade Ramli, Azhar Jaafar Romadhona, Londa Arrahmando Salim, Luthfi Sari, Putri Winda Sarmayanta Sembiring Sasmito Setiawati, Susi Siti Nurmaini Sudarman Suhar Janti Suhendri Suhendri Sukuryadi, Sukuryadi Sutarno Sutarno Sutarno Syafrimen Syafril Syahrir Syahrir Syarif Hidayatullah Titik Wahyuningsih Ubaidillah, Aji Syailendra Wahidah Wahidah Wahyudi, Mudji winarti, dwi Wulandari, Darmawati Y. A. P, Kadek Dwivayana Yesi Novaria Kunang Yudha, Gesit Yudi, Endang Darmawan