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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknoinfo JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Sains Komputer dan Teknologi Informasi Jurnal Sistem Komputer dan Informatika (JSON) Journal of System and Computer Engineering Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) International Journal of Engineering, Science and Information Technology Insearch: Information System Research Journal Batara Wisnu : Indonesian Journal of Community Services Journal of Artificial Intelligence and Digital Business Journal Of Technology and Information System (J-TIS) Bulletin of Informatics and Data Science Advances in Community Services Research IPSIKOM Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) JURDIASRA
Tonggiroh, Mursalim
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Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Sistem Informasi Manajemen Pengelolaan Nilai Siswa pada SMK Hikmah Yapis Jayapura Nurhayati, Siti; Suharto, Emilda; Tonggiroh, Mursalim; Sah, Andrian
Journal Of Technology and Information System (J-TIS) Vol 1 No 1 (2022): Juli 2022
Publisher : Program Studi Sistem Informasi, Universitas Yapis Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70129/jtis.v1i1.236

Abstract

Pengolahan nilai siswa, seperti nilai harian, nilai penilaian tengah semester (PTS) dan nilai Penilaian Akhir Semester (PAS) pada SMK Hikmah masih menggunakan aplikasi Microsoft Excel yang memiliki kekurangan, yakni terformatnya setiap kolom ataupun baris yang ada akan menyebabkan penggabungan nilai dari penambahan materi jika struktur kurikulum berganti, belum terintegrasi dari guru ke guru lainnya membuat pemberian informasi nilai masih menggunakan flash disk sehingga waktu yang dibutuhkan untuk mengolah nilai cukup lama, presensi siswa masih menggunakan buku presensi, aplikasi tidak menyediakan proses pengolahan nilai harian. Maka diperlukan sebuah sistem informasi manajemen nilai siswa yang dapat mengolah semua nilai siswa dengan mengintegrasikan setiap alur pada proses pengolahan nilai siswa. Adapun metode yang digunakan untuk menganalisis permasalahan serta memberikan solusi dari permasalahan tersebut adalah metode PIECES, metode perancangan yang digunakan adalah UML. Dari penelitian ini dihasilkan Sistem Informasi Manajemen Pengelolaan Nilai Siswa yang mengintegrasikan nilai antar guru sehingga dapat mengefektifkan waktu dalam mengolah nilai siswa.
Sistem Informasi Penjualan Hewan Ternak pada Distrik Skanto Kabupaten Keerom Jusmawati, Jusmawati; Ali Nur Hidayat, Muhammad; Tonggiroh, Mursalim; Taher Jufri, Muhammad
Journal Of Technology and Information System (J-TIS) Vol 1 No 1 (2022): Juli 2022
Publisher : Program Studi Sistem Informasi, Universitas Yapis Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70129/jtis.v1i1.241

Abstract

Distrik Skanto merupakan sebuah Distrik yang masuk wilayah administratif dari Kabupaten Keerom, mayoritas penduduknya bekerja sebagai peternak hewan. Namun kondisi penjualan hewan ternak pada Distrik Skanto saat ini masih menggunakan cara tradisional, karena kesulitan mencari pembeli, peternak hanya dapat menjual hewan ternaknya kepada pedagang hewan lokal, yang biasanya akan membeli hewan ternak dengan harga yang rendah. Padahal disisi lain ada sebagian orang juga yang sedang mencari hewan ternak, namun tidak bisa membeli langsung kepada peternak yang ingin menjual ternaknya. Penelitian ini menggunakan metode pengumpulan data yaitu observasi, wawancara dan studi pustaka, menggunakan metode analisis PIECES yang terdiri dari (Performance, Information, Economy, Control, Efficiency, Service), sistem yang akan dibangun adalah pemrograman berorientasi objek sehingga metode perancangan yang cocok digunakan adalah pemodelan Unifield Modelling Language (UML), metode pengembangan sistem yang digunakan adalah Waterfall, pengujian sistem yang digunakan adalah Blackbox. Sistem Informasi penjualan hewan ternak yang dihasilkan dapat memudahkan pengelola dan peternak dalam memanajemen data produk dan mempromosikan hewan ternak yang dimilikinya.
SISTEM INFORMASI CUSTOMER RELATIONSHIP MANAGEMENT PADA TOKO NAHL BORDIR Dwi Saputro, Agung; Tonggiroh, Mursalim; Widiyantoro, M. Riandi; Weu, Wirda
Journal Of Technology and Information System (J-TIS) Vol 1 No 2 (2022): Desember 2022
Publisher : Program Studi Sistem Informasi, Universitas Yapis Papua

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70129/jtis.v1i2.287

Abstract

Nahl Bordir merupakan salah satu Toko pakaian di Kota Jayapura, Toko Nahl Bordir mempunyai beragam produksi seperti pembuatan kaos, kameja, seragam, jaket training dan lain-lain. Permasalahan yang terjadi yaitu pihak toko sulit memberi informasi terkait produk kepada pelanggan. Pada saat ini kondisi penggunaan sistem pemasaran pada took Nahl Bordir masih menggunakan sistem konvensional, selain itu palanggan harus menunggu lama untuk proses pemesanan, pelanggan harus datang ke toko jika ingin mengetahui promo-promo. Oleh karena itu perlu adanya sistem informasi pelayanan pelanggan berbasis Customer Relationship Management (CRM) yang dapat mengelola data Toko Nahl Bordir dan memberikan pelayanan yang optimal kepada pelanggan. Penelitian ini menghasilkan sistem informasi untuk mengelola data pelanggan, data produk dan mengirim informasi via email
Expert System for Diagnosing Learning Disorders in Children Using the Dempster-Shafer Theory Approach Nugraheni, Murien; Nuraini, Rini; Tonggiroh, Mursalim; Nurhayati, Siti
Sinkron : jurnal dan penelitian teknik informatika Vol. 7 No. 4 (2023): Article Research Volume 7 Issue 4, October 2023
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.12960

Abstract

Learning disorders can occur in children where a child experiences difficulty mastering important skills such as reading, writing, or arithmetic. Learning disorders can have an emotional impact on children, such as low self-confidence, anxiety, or frustration. Therefore, it is important for parents and educators to recognize the signs of learning disorders so that appropriate intervention can be given. The aim of this research is to develop an expert system that can diagnose learning disorders in children using the Dempster-Shafer Theory algorithm to make it easier to diagnose and produce the right diagnosis. The Dempster-Shafer Theory approach has the ability to provide probability values in evidence based on the level of belief and reasoning in accordance with logic and then combine it with information from certain events. This research produces an expert system built on a website that can diagnose based on symptoms and display diagnosis results, definitions of types of learning disorders, and treatment options. The accuracy test results show a value of 92%, which means that the system built using the Dempster-Shafer Theory approach is able to diagnose learning disorders in children well.
PENGEMBANGAN SISTEM PAKAR MENGGUNAKAN MESIN INFERENSI DEMPSTER-SHAFER THEORY UNTUK DIAGNOSA GANGGUAN SOMATOFORM Tonggiroh, Mursalim; Heriyani, Nofitri; Handayani, Nurdiana; Nugroho, Nurhasan
Jurnal Teknoinfo Vol 18, No 2 (2024): Juli 2024
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jti.v18i2.4062

Abstract

Gangguan somatoform merupakan gangguan mental dengan kondisi di mana individu mengalami gejala fisik yang menyebabkan distress signifikan atau gangguan dalam fungsi sehari-hari, namun tidak dapat dijelaskan oleh kondisi medis, penggunaan substansi, atau kondisi mental lainnya. Namun, karena kompleksitas gejala dan kesulitan dalam mendeteksi gangguan somatoform secara klinis seringkali menyebabkan keterlambatan diagnosis dan penanganan yang tidak tepat, yang dapat memperburuk kondisi pasien. Kurangnya pengetahuan tentang gangguan somatoform dan keterbatasan akses terhadap layanan kesehatan mental yang berkualitas dapat menyulitkan individu untuk mendapatkan bantuan yang dibutuhkan. Tujuannya penelitian ini dilakukan untuk membangun sistem pakar yang digunakan dalam diagnosis gangguan somatoform secara mudah dan akurat melalui penerapan metode Dempster-Shafer Theory sebagai mesin inferensinya. Pendekatan ini memiliki keunggulan dalam mengelola ketidakpastian dan informasi yang tidak lengkap, memungkinkan sistem pakar untuk membuat inferensi diagnostik berdasarkan kumpulan gejala yang diobservasi, bahkan ketika informasi tersebut tidak lengkap atau ambigu. Algoritma Dempster-Shafer Theory memanfaatkan konsep massa kepercayaan untuk menggambarkan tingkat keyakinan atau ketidakpastian tentang suatu hipotesis atau peristiwa. Sistem pakar yang dikembangkan dapat mendiagnosa berdasarkan gejalanya dan memperlihatkan hasil diagnosa, serta tindakan yang dapat dilakukan. Berdasarkan hasil pengujian dengan menggunakan sampel uji yang dipilih secara acak, didapatkan tingkat akurasi diagnosa yaitu 86,67%. Hasil tersebut mengindikasikan bahwa Dempster-Shafer Theory dapat diimplementasikan dengan baik untuk mendiagnosa gangguan somatoform.
Implementation of a Combination of Rank Reciprocal and Additive Ratio Assessment Approaches for 3D Printer Selection Fatmayati, Fryda; Soares, Teotino Gomes; Tonggiroh, Mursalim; Alexander, Allan Desi
Bulletin of Informatics and Data Science Vol 2, No 2 (2023): November 2023
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v2i2.83

Abstract

With the wide selection of 3D printers available on the market, the challenge arises for consumers and businesses to choose the device that best suits their specific needs. To determine the choice, the decision-maker must know one by one the specifications of the 3D printer to be purchased, which results in making difficult decisions and requiring a long time. This research aims to implement a combination of the Rank Reciprocal and additive ratio assessment (ARAS) approaches to make it easier to determine decisions for selecting a 3D printer. The Reciprocal Rank approach provides weight values by utilizing the reciprocal or inverse principle. Meanwhile, the ARAS approach is used to obtain the best alternative by evaluating alternative rankings based on their utility function. From the case studies that have been carried out, the highest to lowest utility values are Anycubic 4Max Pro (A2) getting a score of 0.8289, Creality Ender-3 Pro (A1) getting a score of 0.6174, Anet 3D Printer ET4 Pro (A3) getting a score of 0.5510, and Mingda Magician X2 (A4) getting a score of 0.5116. The output produced by the system in the case study carried out produces the same value as the manual calculation, meaning that the ARAS method calculation in the system is declared valid. Based on usability testing, it got a score of 90%, which shows the system is suitable for use
IDENTIFICATION OF POTATO LEAF DISEASES USING ARTIFICIAL NEURAL NETWORKS WITH EXTREME LEARNING MACHINE ALGORITHM Erkamim, Moh.; Septarini, Ri Sabti; Tonggiroh, Mursalim; Nurhayati, Siti
Jurnal Pilar Nusa Mandiri Vol. 20 No. 1 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i1.5307

Abstract

Potato plants have an important role in providing a source of carbohydrates for society. However, potato production is often threatened by various plant diseases, such as leaf disease, which can cause a decrease in yields. Identification of diseases on potato leaves is currently mostly done by farmers manually, so it is not always efficient and accurate. So the aim of this research is to identify diseases on potato leaves with artificial neural networks using the ELM (Extreme Learning Machine) approach and the GLCM (Gray Level Co-Occurrence Matrix) method for feature extraction. The GLCM approach functions to obtain texture features on objects by measuring how often certain pairs of pixel intensities appear together at various distances and directions in the image. Meanwhile, the ELM algorithm is used for image identification by adopting a one-time training method without iteration, which involves randomly determining weights and biases in hidden layers, thus allowing training to be carried out quickly and efficiently. Evaluation of the model by looking for the level of accuracy produces a value of 84.667%. The results show that the model developed is capable of accurate identification.
Optimalisasi Throughput Pada Penerapan Load Balancing Dalam Jaringan Cloud Menggunakan Round Robin dan Least Connection Erkamim, Moh.; Prihatin, Titin; Saraswati, Sandra Dewi; Tonggiroh, Mursalim
Journal of System and Computer Engineering Vol 5 No 1 (2024): JSCE: Januari 2024
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v5i1.1056

Abstract

As the complexity of cloud infrastructure increases, one of the main challenges faced is how to optimize throughput in cloud networks. Optimal throughput is crucial to guarantee the performance of applications and services hosted in the cloud. Using load balancing techniques can optimize throughput, but careful analysis and testing is needed regarding the appropriate load balancing approach to improve throughput performance. This research aims to analyze the effectiveness of load balancing strategies with Round Robin and Least Connection in increasing throughput in cloud networks. Through empirical testing, this study compares the two methods based on the resulting throughput at various connection levels, ranging from 1000/600 to 5000/1000. Test results show that both strategies provide similar performance at low connection rates, with Round Robin recording slightly higher throughput at 1000/600. However, the difference becomes almost imperceptible as the number of connections increases. At 2000/700 to 5000/1000, the throughput generated by both strategies shows marginal differences, with Least Connection slightly superior at the highest connection level. These findings indicate that both Round Robin and Least Connection can be applied effectively to increase throughput in cloud environments, with the selection of specific strategies depending on workload characteristics and service requests. This research provides valuable insights for academics and IT practitioners who want to optimize cloud networks to achieve maximum performance
Pengembangan Sistem Pakar untuk Diagnosa Gangguan Disosiatif Menggunakan Pendekatan Case-Based Reasoning Rusliyawati, Rusliyawati; Tonggiroh, Mursalim; Nurhayati, Siti; Jusmawati, Jusmawati
Insearch: Information System Research Journal Vol 4, No 02 (2024): Insearch (Information System Research) Journal
Publisher : Fakultas Sains dan Teknologi UIN Imam Bonjol Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15548/isrj.v4i02.9608

Abstract

Gangguan disosiatif merupakan kelompok gangguan mental yang ditandai oleh gangguan fungsi memori, kesadaran, identitas, atau persepsi, sering kali sebagai respons terhadap trauma berat atau tekanan psikologis yang ekstrem.Diagnosa yang akurat dan tepat waktu sangat penting untuk penanganan gangguan ini, namun kompleksitas dan tumpang tindihnya gejala dengan gangguan mental lainnya membuat proses diagnosa menjadi tantangan besar. Selain itu, kurangnya spesialisasi dan pengalaman tenaga medis dalam mengenali gangguan ini juga menghambat proses diagnosa. Penelitian ini bertujuan untuk mengembangkan sistem pakar berbasis pendekatan Case-Based Reasoning (CBR) untuk mendiagnosa gangguan disosiatif. Algoritma CBR bekerja dengan memanfaatkan pengalaman dari kasus-kasus sebelumnya, sehingga dapat memberikan diagnosa yang lebih cepat dan akurat serta membantu pengguna dalam menentukan langkah penanganan yang tepat. Teknik weighted similarity digunakan untuk menyesuaikan pengaruh setiap fitur terhadap kemiripan total. Penelitian ini menghasilkan sistem pakar yang dikembangkan berbasis web dengan memiliki fitur utama yaitu menampilkan hasil diagnosis berdasarkan gejala yang dipilih pasien, penjelasan tentang penyakit, serta solusi atau penanganannya. Hasil pengujian menunjukkan bahwa sistem ini memiliki tingkat akurasi sebesar 90%. Hal ini menunjukkan bahwa sistem pakar yang dibangun sangat andal dalam mendiagnosa gangguan disosiatif.
Pattern Recognition of Chinese Characters Using the Sokal Sneath Four Method Rasna, Rasna; Sah, Andrian; Nur Hidayat, M. Ali; Jusmawati, Jusmawati; Tonggiroh, Mursalim
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.668

Abstract

Pattern recognition is a discipline that aims to classify or describe objects based on their characteristics, quantitative measurements, or critical properties. Where a pattern is defined as an entity that is initially undefined, it can be identified and named through quantitative analysis. Pattern recognition can be applied to various fields, such as handwriting recognition, face recognition, eye recognition, skin, and image processing. One example of the application of pattern recognition is character recognition in letters used in learning. In this research, the digital image used as input comes from a two-dimensional image obtained through a digital camera. The digital image describes the light intensity in light and dark areas in the form of pixels and provides information about the object's color. To support the process of recognizing alphabet letters, which in this case are specifically Chinese alphabet letters, it will be assisted by using the Sokal Sneath Four Method. This significant mathematical approach helps create a compatible and accurate system for recognizing letter patterns through intensive data training. This method involves a series of steps, including data preprocessing, feature extraction, and classification, to train the system to recognize Chinese characters. The more training given to the system, the higher its accuracy in recognizing letter patterns, especially Chinese alphabet letters. The test results show that this Chinese alphabet letter pattern recognition system has a success rate of 65%, with a failure rate of 35%. Nevertheless, these results show room for further improvement in the algorithms used and the addition of training data to improve system performance and accuracy.
Co-Authors ., Rusliyawati Al-Hakim, Rosyid Ridlo Alexander, Allan D Ali Nur Hidayat, Muhammad Bumi, Kalbu Pandu Ciptaningrum, Wahyu Dian Pertiwi Dwi Lestari Dwi Saputro, Agung Erni Widarti Fryda Fatmayati Hakim, Jamaludin Handayani, Nurdiana Hasan, Rian Fajry Heriyani, Nofitri Hidayat, Muhammad Ali Nur Jusmawati Jusmawati Jusmawati, Jusmawati khusnul khotimah Limbong, Alfa Natasya Limbong, Josua Josen Alexander lina, Ros Matdoan, Irjii Moh. Erkamim Muhamad Taher Jufri Muhammad Riandi Widiyantoro Murien Nugraheni Ndala, Stefanus novi yona sidratul munti Nur Hidayat, M. Ali Nurhasan Nugroho Prakoso, Sukma Dwi Que, Meirina Diah Setiawati Rasna, Rasna Rini Nuraini, Rini Rumandan, Rhaishudin Jafar Sah, Andrian Sandra Dewi Saraswati Sasono, Damar Surya SEJATI, FAJAR RINA Septarini, Ri Sabti Septilia, Tiara Indah Septyana Prasetianingrum Sidiq, Sofian Siti Nurhayati Soares, Teotino Gomes Suharto, Emilda Sulaiman, Husni Tanniewa, Adam M Weu, Wirda Widiyantoro, Muh. Riandi Widiyantoro, Riandi Yakub Yanuardi Yanuardi Yendra Yuri Rahmanto Zakaria Zakaria