Article Per Year (5 Year)
p-Index From 2021 - 2026
1.325
P-Index
This Author published in this journals
All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika JTIKOM: Jurnal Teknik dan Sistem Komputer Journal Social Science And Technology For Community Service Paradigma Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Informatika dan Rekayasa Perangkat Lunak
Tri Widodo
Universitas Teknokrat Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media

Published : 8 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 8 Documents
Search

 1 
Sistem Sirkulasi Air Pada Teknik Budidaya Bioflok Menggunakan Mikrokontroler Arduino UNO R3 Tri Widodo; Bambang Irawan; Agung Tri Prastowo; Ade Surahman
Jurnal Teknik dan Sistem Komputer Vol 1, No 2 (2020): Jurnal Teknik dan Sistem Komputer
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtikom.v1i2.12

Abstract

Teknologi bioflok merupakan teknologi budidaya yang didasarkan pada prinsip asimilasi nitrogen anorganik (amonia, nitrit dan nitrat) oleh komunita mikroba (bakteri heterotrof) dalam media budidaya yang kemudian dapat dimanfaatkan oleh organisme budidaya sebagai sumber makanan. Pada budidaya sirkulasi bioflok, biasanya pembudidaya akan menghidupkan mesin aerator sebagai penyuplay oksigen selama 24 jam. Karena tidak  adanya  mesin  pompa  air  untuk melakukan  sirkulasi  dan  pembersihan kotoran pada kolam maka hal ini mengakibatkan pembudidaya harus melakukan pembuangan air kolam secara manual. Dengan adanya sensor dan mikrokontroler, mempermudah peneliti untuk membuat  alat  sirkulasi air otomatis. Dengan  menggunakan sensor turbility sebagai indicator kekeruhan air dan Pompa air yang berfungsi untuk mengaliri sirkulasi air akan bekerja sesuai dengan tingkat kekeruhan air.
PELATIHAN CUSTOMER SERVICE UNTUK TENAGA KEPENDIDIKAN SMKN 2 KALIANDA Andi Nurkholis; Damayanti Damayanti; Selamet Samsugi; Muhammad Fitratullah; Berlintina Permatasari; Tri Widodo; Leny Meilisa
Journal of Social Sciences and Technology for Community Service (JSSTCS) Vol 2, No 2 (2021): Vol 2, No 2 (2021): September 2021
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jsstcs.v2i2.1379

Abstract

Customer service merupakan pelayanan terhadap kepuasan pelanggan, memberikan informasi dan menyelesaikan keluhan yang dialami oleh tamu/konsumen. Berdasarkan wawancara kepada Kepala Sekolah SMKN 2 Kalianda menjelaskan bahwa saat ini customer service sudah cukup memadai. Namun pihak sekolah masih menginginkan adanya peningkatan pada proses pelayanan customer service yang prima bagi tenaga kependidikan. Pelatihan customer service bertujuan meningkatkan kualitas pelayanan oleh tenaga kependidikan kepada masyarakat, khususnya para orangtua dari calon siswa yang hendak bersekolah di SMKN 2 Kalianda. Kegiatan pelatihan dilakukan dengan memberikan materi terlebih dahulu yang dilanjutkan dengan praktik secara langsung. Materi yang diberikan berupa pelatihan marketing, pelatihan teknik pendekatan kepada konsumen dan pelatihan komunikasi dan bahasa. Berdasarkan hasil yang diperoleh, pelatihan berhasil meningkatkan kualitas tenaga kependidikan dalam pelayanan terhadap pelanggan yang dibuktikan dari pelayanan yang diberikan secara baik, ramah, dan jelas dalam memberi informasi kepada pelanggan. Peningkatan kualitas dari tenaga kependidikan secara tidak langsung meningkatkan kualitas dari manajemen dan organisasi sekolah, sehingga mampu lebih berkembang, khsususnya dalam merekrut calon siswa baru.
Sistem Kendali Proporsional Kualitas Air berupa Ph dan Suhu pada Budidaya Ikan Lele Berbasis IoT Tri Widodo; Angga Bayu Santoso; Sahrial Ihsani Ishak; Ramli Rumeon
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 9, No 1 (2023): Volume 9 No 1
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v9i1.59607

Abstract

Banyaknya kematian bibit yang masih kecil dalam pemeliharaan disebabkan oleh kurangnya perhatian dari media dan pemeliharaan kondisi air. Kegagalan budidaya ikan dapat disebabkan oleh air dengan keasaman (pH) yang terlalu asam atau basa, dan suhu yang tidak sesuai akan mempengaruhi angka kematian. Tingkat keasaman (pH) air yang baik untuk ikan lele adalah 6,5 – 8,5. Tingkat pH 9 ke atas akan menyebabkan nafsu makan ikan lele menurun dan tingkat pH air di bawah 5 akan menyebabkan penggumpalan lendir di insang ikan lele dan mudah berkembang biaknya jamur atau bakteri patogen. Suhu air yang baik untuk pertumbuhan ikan adalah antara 20-30°C. Perubahan cuaca yang sewaktu-waktu berubah secara ekstrem, hujan yang terus menerus dan kemudian panas yang tinggi akan membuat suhu dan pH air berubah drastis sehingga menyebabkan ikan lele mengalami stress dan kematian. Berdasarkan pengamatan tersebut, diperlukan suatu alat yang mampu menjaga kualitas air berupa suhu dan pH air. Sistem Pengendalian Kualitas Air berupa pH dan suhu air dengan kontrol proporsional dapat mengontrol keasaman pH dan suhu air pada budidaya ikan lele. Sistem ini terbukti berhasil meningkatkan pertumbuhan pada kolam A dengan sistem. pertumbuhan ikan lele dari 4 cm ke ukuran 5 – 6 cm meningkat 7.7% lebih tinggi dari kolam B tanpa sistem. Pertumbuhan ikan lele ke ukuran 7 – 8 cm pada kolam A 3.5% lebih tinggi daripada kolam B. Pertumbuhan ikan lele ke ukuran 9 cm pada kolam A 4% lebih tinggi dan angka kematian pada kolam A dengan sistem 16% lebih rendah dibandingkan dengan kolam B tanpa sistem. Sistem kendali kualitas air berupa pH dan suhu air ini terbukti mampu meningkatkan pertumbuhan dan menekan kematian ikan lele  dengan menjaga kestabilan suhu dan pH air kolam pada nilai setpoint dan aplikasi android yang dibuat berhasil menampilkan nilai dari pembacaan dari sensor pH dan suhu yang telah ditampung di dalam cloud firebase sehingga memonitoring kualitas air berupa suhu dan pH air dapat dilakukan dari jarak jauh.
Explorasi Pola Batik Baru dengan Deep Convolutional Algorithme Generative Adversarial Networks (DCGANs) Sahrial Ihsani Ishak; Toto Haryanto; Tri Widodo; Angga Bayu Santoso
Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer Vol 18, No 1 (2023): Informatika Mulawarman : Jurnal Ilmiah Ilmu Komputer
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jim.v18i1.9531

Abstract

Batik merupakan kesenian tradisional yang berasal dari Indonesia yang memadukan seni, budaya dan teknologi dalam membuatnya. Keanekaragaman motif batik di Indonesia diperoleh dari nilai- nilai simbol, budaya berdasarkan setiap daerah yang terkait erat dengan kehidupan masyarakat itu sendiri. Pengembangan dalam teknologi mendorong untuk membuat terobosan inovasi dalam memaksimalkan jenis – jenis batik dengan pola terbaru. Inovasi dengan machine learning yaitu Deep Convolutional Algorithme Generative Adversarial Networks (DC-GAN) merupakan bentuk terobosan inovasi pengembangan lanjutan Generative Adversarial Networks (GAN) dalam membuat pola – pola terbaru untuk batik. Pengembangan ini akan menggunakan sembilan jenis batik daerah dengan total data gambar sebanyak tiga ribu tiga ratus sembilan puluh tujuh dan dilakukan proses iterasi sebanyak lima ribu kali.
Development of a Portable Smart Feeder Based on Scheduling and Precision Dosing for Fish Feeding in Aquaculture Arif Dwi Kuncoro; Tri Widodo; Yuri Rahmanto; Sahrial Ihsani Ishak
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 2 (2026): MALCOM April 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i2.2559

Abstract

Freshwater and marine fish farming is the backbone of the fisheries economy, especially for small to medium-scale farmers. Feed contributes approximately 60–70% of operational costs, so inaccurate feed scheduling and dosing can increase production costs, reduce feed efficiency, and increase waste. This research developed a Portable Smart Feeder based on precision scheduling and dosing, equipped with gradual feeding (sub-doses with intervals) and a spreader for even feed distribution. Development was carried out using a prototype method, then the system performance was tested through experiments in two ponds for 14 days (one sorting cycle): Pond A (conventional) and Pond B (using the system). Evaluation included feed consumption, mortality, and growth measured through a sorting process (grading) on ??the 14th day. The results showed that Pond B produced 70.90 kg of harvested biomass with 28.00 kg of feed and 13 fish mortality, while Pond A produced 68.17 kg of biomass with 33.80 kg of feed and 250 fish mortality. The FCR value of Pond B is 0.91:1, better than Pond A 1.20:1, so the system shows increased feed efficiency and maintenance stability.
Modification of Additive Ratio Assessment Method through Distance-Based Weighting Approach for Optimizing Assessment Accuracy Rakhmat Dedi Gunawan; Muhammad Waqas Arshad; Agung Deni Wahyudi; Ryan Randy Suryono; Tri Widodo; Faruk Ulum
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 2 (2025): September 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i2.8810

Abstract

The Additive Ratio Assessment (ARAS) method is one of the approaches in multi-criteria decision making (MCDM) used to determine the best alternative based on a number of predetermined criteria. The drawback of this method is its heavy reliance on the accuracy of the criterion weighting determination; non-objective weights can lead to biased results. This study aims to improve the accuracy of ranking in multicriteria decision-making through the modification of the ARAS method with a distance-based weighting approach called ARAS-D. The ARAS method, known for its simplicity in calculation, was modified to be more responsive to the distribution of alternative data on each criterion. This distance-based weighting approach objectively determines the weight of the criteria based on variations in data performance, thereby reducing subjectivity in the weighting process. A case study was conducted on the selection of a new store location with six main criteria: rental cost, building area, accessibility, consumer traffic, parking availability, and infrastructure. The results of the evaluation show that the ARAS-D method is able to produce more precise ratings than the standard approach. Store locations with the highest utility value are recommended as the best choice, proving the effectiveness of the method in supporting strategic decisions. The results of the New Store Location 5 alternative rating obtained the highest score with a value of 0.9083, indicating that this location is the most optimal choice overall. This is followed by New Store Location 3 with a value of 0.8617 and New Store Location 1 with a value of 0.8415, which also shows excellent performance against the criteria that have been set. This research contributes to the development of more adaptive and data-based decision-making methods.
Clustering of Provincial Health Vulnerability Levels in Indonesia Using the K-Means Method Okma Arnilia; Sahrial Ihsani Ishak; Tri Widodo; I Gusti Nyoman Agung Bisma Tatwa
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol. 7 No. 1 (2026): Volume 7 Number 1 March 2026
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jatika.v7i1.1469

Abstract

This study aims to classify the health vulnerability levels of 38 provinces in Indonesia based on health and socio-economic indicators in 2024, including the number of hospitals, access to adequate sanitation, access to safe drinking water, stunting prevalence, number of health facilities, population size, and the percentage of poor population. The analysis began with data normalization using the z-score method to standardize variable scales and prevent dominance by indicators with larger value ranges. Following normalization, the optimal number of clusters was determined using the Elbow method by examining the decrease in inertia across different k-values. Based on the inertia pattern and cluster stability, the optimal number of clusters was identified as K=4, which adequately represents the variation in health vulnerability. The clustering results were subsequently visualized in a spatial map using Indonesia’s provincial administrative boundaries. The visualization revealed clear geographical variation across regions, with Cluster 1 representing provinces with very good health conditions, Cluster 2 good conditions, Cluster 3 moderate conditions, and Cluster 4 provinces requiring special attention regarding health indicators. These findings provide a comprehensive overview of health vulnerability distribution in Indonesia and are expected to inform policymakers and stakeholders in prioritizing region-based health interventions, strengthening health development strategies, and promoting more equitable national health services.
Image-Based Food Classification for Nutritional Information Estimation Using Deep Learning Sahrial Ihsani Ishak; Sri Dianing Asri; Bias Yulisa Geni; Okma Arnilia; Tri Widodo; Diva Maulana Ilham
Sinkron : jurnal dan penelitian teknik informatika Vol. 10 No. 3 (2026): Article Research July 2026
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v10i3.16170

Abstract

This study aims to develop an image-based food classification application integrated with nutritional information retrieval using a deep learning approach. The proposed system is designed to recognize food types from images and provide nutritional information based on an Indonesian food nutrition database. The method involves collecting a dataset of 8,248 images representing 38 categories of Indonesian traditional foods, performing image preprocessing and data augmentation, and developing a Convolutional Neural Network (CNN) model based on the MobileNetV2 architecture through transfer learning. Model performance was evaluated using a 3-fold stratified cross-validation strategy and measured using accuracy, precision, recall, and F1-score metrics. Experimental results showed that the proposed model achieved average accuracy, precision, recall, and F1-score values of 98.85%, 98.88%, 98.85%, and 98.85%, respectively, demonstrating robust and consistent classification performance across the validation folds. The trained model was subsequently deployed into a mobile application using TensorFlow Lite to support real-time food classification and nutritional information presentation. The main contribution of this study is the development of an end-to-end mobile system that integrates deep learning-based food classification with an Indonesian food nutrition database, enabling users to obtain calorie, protein, fat, and carbohydrate information quickly and conveniently for dietary monitoring and health awareness.  
Co-Authors Ade Surahman Andi Nurkholis Angga Bayu Santoso Arif Dwi Kuncoro Bambang Irawan Berlintina Permatasari Bias Yulisa Geni Damayanti, Damayanti Diva Maulana Ilham Gunawan, Rakhmat Dedi I Gusti Nyoman Agung Bisma Tatwa Leny Meilisa Muhammad Fitratullah Muhammad Waqas Arshad Okma Arnilia Prastowo, Agung Tri Ramli Rumeon Ryan Randy Suryono S. Samsugi Sahrial Ihsani Ishak Sahrial Ihsani Ishak Sahrial Ihsani Ishak Sri Dianing Asri Toto Haryanto Ulum, Faruk Wahyudi, Agung Deni Yuri Rahmanto