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All Journal CESS (Journal of Computer Engineering, System and Science) Multitek Indonesia : Jurnal Ilmiah KOMPUTEK Journal of Computer Networks, Architecture and High Performance Computing Jurnal Ilmiah Edutic : Pendidikan dan Informatika Uranus: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Yovi Litanianda
Universitas Muhammadiyah Ponorogo
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Mechanical Engineering

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OTOMASI IRIGASI JANGGELAN BERBASIS INTERNET OF THINGS Angga Prasetyo; Arief Rahman Yusuf; Yovi Litanianda
MULTITEK INDONESIA Vol 13, No 2 (2019): Desember
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (737.057 KB) | DOI: 10.24269/mtkind.v13i2.1763

Abstract

Internet and industrial revolution 4.0 brought influence in society, especially in agriculture, the changes that occurred were in farming activities by applying appropriate technology. This activity is much in demand, especially the planting irrigation process. However, the process of irrigation or irrigation that has used appropriate technology still has some shortcomings such as pumping and control hardware systems that are still stand-alone using a timer, so the automation and monitoring process is still semi-manual. As done in the cultivation of janggelan (black grass jelly), which focuses more on irrigation governance, because the janggelan requires water intake and fertilizer nutrition which is always monitored. In order for the device to function optimally, it is made a miniature tool based on the internet of things to facilitate control and monitoring via a smartphone. In order for the miniature tool can be integrated and function in real-time with the Internet of things, then all devices (YL 69 sensors, Relay, Board NodeMCU esp 8266 are given C language coding commands, via the Arduino ID interface. synchronization between the user interface, the miniature devices, and Internet networks running normally. IoT devices and internet networks can run normally. Sensor data is able to give the pump selenoid command to turn on under humidity conditions of less than 65%, while the pump is off at 40% humidity. The success rate of data sent on Google Firebase with an average total ping of 70.28% was all successful.
PERANCANGAN APLIKASI LOKASI TAMBAL BAN DI PONOROGO BERBASIS ANDROID Irfan Khoirul Arifin; Aliyadi Aliyadi; Yovi Litanianda
KOMPUTEK Vol 1, No 1 (2017): Oktober
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (585.616 KB) | DOI: 10.24269/jkt.v1i1.113

Abstract

Jumlah kendaraan di Indonesia terus meningkat setiap tahunnya. Hal ini juga terjadi di Kabupaten Ponorogo. Hal tersebut juga akan berbanding lurus dengan banyak orang yang mengalami masalah dengan kendaraan mereka, seperti mendapati ban bocor karena tertusuk paku atau sebab lain. Dan juga akan meningkatkan kebutuhan jasa tambal ban. Bagi pengendara yang kurang mengetahui daerah sekitar ketika mengalami kerusakan ban motor, maka tentunya untuk mencari tempat tambal ban terdekat akan cukup menyulitkan. Oleh karena itu pada penelitian ini dikembangkan media informasi berupa aplikasi berbasis Android untuk memetakan lokasi – lokasi tambal ban yang ada di Ponorogo, sekaligus mencari tambal ban terdekat berdasarkan lokasi pengendara. Aplikasi ini berupa layanan berbasis lokasi (Location Based Service) kepada pengendara dengan memberitahu letak tambal ban terdekat berserta informasi terkait. Berdasarkan hasil pengujian aplikasi ini mampu membantu pengguna mencari tambal ban dalam bentuk peta lokasi – lokasi tambal ban, daftar bengkel tambal ban, dan daftar bengkel tambal ban terdekat beserta jarak dari lokasi pengguna. Aplikasi ini juga mampu menunjukkan informasi terkait sekaligus menunjukkan rute perjalanan dari lokasi pengguna dengan lokasi tambal ban yang dituju dengan memanfaatkan aplikasi google maps.
IMPLEMENTASI TENSOR FLOW LITE PADA TEACHABLE UNTUK IDENTIFIKASI TANAMAN AGLONEMA BERBASIS ANDROID Muhammad Bagus Baihaqi; Yovi Litanianda; Andy Triyanto
KOMPUTEK Vol 6, No 1 (2022): April
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v6i1.1143

Abstract

Aglonema or sri fortune has various types with various shapes, patterns and colors. Various types and more and more due to the many crossing processes carried out by owners and lovers of aglonema plants. For ordinary people who do not have insight into aglonema, it will be difficult to distinguish aglonema plants because the shapes, patterns and colors have similarities. It takes a Teachable Machine system with a complex but more sophisticated method that is able to recognize plants with a higher level of accuracy. The machine learning process is carried out on a computer to identify image data into classification results in the form of predictions. Tensorflow lite is a machine learning library specially designed for object recognition. Therefore, researchers are encouraged to create an Android-based mobile application that is able to recognize aglonema plants quickly, easily and accurately. 
PERANCANGAN SISTEM SELEKSI ATLET BOLAVOLI MENGGUNAKAN METODE SAW PADA SEKOLAH BOLAVOLI KUSUMA BHIRAWA Taufiq Abidin; Yovi Litanianda; Andy Triyanto
KOMPUTEK Vol 5, No 2 (2021): Oktober
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v5i2.828

Abstract

The basic technique of volleyball itself is one of the most important elements in the game of volleyball, without mastering good basic techniques, the game cannot be played perfectly, the basic techniques of volleyball include serving, passing, smash and block (dam). Based on an interview with Coach at SBV, Kusuma Bhirawa who coaches players at the age of U-18 teenagers, explained that the selection of athletes in participating in the event is carried out according to the coach's feelings during training. After making direct observations at the Kusuma Bhirawa volleyball school with the existing problems, a decision support system will be built for the selection of volleyball athletes using the SAW method. SAW (Simple Additive Weighting) is a method in a decision support system with a weighted summation of the performance ratings of each alternative on all attributes. The alternative that has the highest value is the best alternative proposed. The criteria needed by the SbV trainer Kusuma Bhirawa in anthropometric measurements are height, physical fitness test criteria consisting of 60 m running, 60 sec pull ups, 60 sec sit ups, vertical jump, 1200 m run. volleyball smash technique criteria, passing over, passing down, serving and blocking. From the results of the correlation test that has been tried to get the correlation of the recommendation of the core player list from the application system compared to the player list from the coach with a value of 83.3%. Therefore, these results show that the SAW method has a fairly good correlation when used to determine the selection of volleyball athletes 
Irrigation Control Using Fuzzy Logic on The Internet of Things Agriculture System Angga Prasetyo; Yovi Litanianda; Fadelan Fadelan; Arief Rahman Yusuf; Sugianti Sugianti
CESS (Journal of Computer Engineering, System and Science) Vol 7, No 2 (2022): July 2022
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v7i2.37195

Abstract

Cabai, sawi, tomat, selalu jadi tanaman favorit petani, walaupun butuh banyak air dan pekerja. Adaptasi kondisi itu dengan teknik bercocok tanam smart agriculture system (SAS) yang melibatkan teknologi seperti irigasi otomatis yang mengatur penyiraman hanya berdasarkan rutinitas tanpa memperhatikan kondisi lahan. Pengendalian seperti ini saat musim pancaroba bisa mengakibatkan kebusukan akar serta memicu penyakit fungisarium pada tanaman cabai. Solusinya, coba dihadirkan sistem yang melibatkan kecerdasan buatan seperti logika fuzzy berbentuk sebuah embedded system  dengan pantauan internet of things (IoT). Logika fuzzy secara komputasi matematis akan mengatur irigasi berdasarkan kondisi kelembapan dan suhu lahan. Dimulai dengan tahap Fuzzyfikasi untuk memetakan input nilai suhu dan kelembapan dari sensor. Dilanjut dengan pembuatan Inference engine di mikrokontroler NodeMcu 8266 untuk mengartikan pernyataan rule fuzzy berbentuk agregasi kondisi minimum dengan operator AND, kemudian dikombinasikan dengan nilai set tunggal 0 dan 1 pada fuzzy sistem menjadi respon aktuator yang sesuai. Setelah keseluruhan sistem dijadikan purwarupa, maka dilakukan testing pengujian untuk mengetahui seberapa baik kode program fuzzy dapat merespon perubahan ekosistem lahan budidaya agriculture yang disimulasikan. Penelitian ini mendapati hasil bahwa kode program loggika fuzzy yang ditanamkan pada mikrokontroler nodeMCU8266 berhasil mengatur durasi penyemprotan yang dilakukan pompa sebagai respon berbagai simulasi kondisi lingkungan dalam waktu 3,6 detik.
Sistem Pendukung Keputusan untuk Menentukan Pemilihan Guru Berprestasi menggunakan Metode Promethee pada SMAN 1 Tegalombo Kabupaten Pacitan Andy Triyanto Pujo Raharjo; Windi Eka Triatma; Yovi Litanianda
EDUTIC Vol 9, No 2: Mei 2023
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/edutic.v9i2.19715

Abstract

Sekolah Menengah Atas Negeri (SMAN) 1 Tegalombo Kabupaten Pacitan dalam meningkatkan kualitas pendidikan melalui beberapa program peningkatan mutu, diantaranya pada aspek kurikulum, sarana/prasarana serta memiliki jumlah guru yang berkualitas. Melalui sistem penilaian guru berprestasi diharapkan para guru termotivasi sehingga memiliki ketersediaan guru berkualitas dalam pengembangan diri dan kompetensinya. Survey yang diambil dari SMAN 1 Tegalombo Kabupaten Pacitan,diketahui bahwa proses penilaian guru berprestasi masih dilaksanakan menggunakan cara manual berdasarkan subyektifitas, hal ini memungkinkan guru berprestasi yang dipilih tidak sesuai dengan standart yang diharapkan dan tidak mendapatkan hasil kandidat terbaik. Dengan menggunakan Sistem Pendukung Keputusan diharapkan memberikan hasil yang terbaik dan mempermudah proses seleksi pemilihan guru berprestasi oleh Kepala Sekolah. Data pemilihan guru berprestasi yang digunakan adalah daftar penilaian pelaksanaan pekerjaan yang berisi nilai orientasi pelayanan, inisiatif kerja, komitmen, kerjasama dan ide baru. Metode yang ingin digunakan untuk mengatasi permasalahan dalam mengambil keputusan pada pemilihan guru berprestasi ini yaitu metode Prometheee. Hasil dari penelitian terdahulu menunjukan bahwa metode Prometheee memiliki keunggulan dalam proses pengambilan keputusan yaitu berupa keluaran dalam bentuk perangkingan yang valid.
Implementation of Fuzzy Logic for Chili Irrigation Integrated with Internet of Things Angga Prasetyo; Arief Rahman Yusuf; Yovi Litanianda; Sugianti; Fauzan Masykur
Journal of Computer Networks, Architecture and High Performance Computing Vol. 5 No. 2 (2023): Article Research Volume 5 Issue 2, July 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v5i2.2518

Abstract

Chili, mustard greens, and tomatoes have always been farmers' favored crops, despite their high water and labor demands. Adapt to these conditions by utilizing smart agriculture systems (SAS) agricultural techniques that involve technology such as automatic irrigation that regulates watering based solely on routine, regardless of land conditions. This type of control during the transitional season can lead to root rot and fungisarium disease on chile plants. In the form of an embedded system with internet of things (IoT) monitoring, a system incorporating artificial intelligence such as fuzzy logic is proposed as a solution. Fuzzy logic will regulate irrigation based on the land's humidity and temperature using computational mathematics. Beginning with the fuzzyification stage to map the sensor's temperature and humidity input values, fuzzy logic is applied. The creation of an inference engine in the NodeMcu 8266 microcontroller to interpret fuzzy rule statements in the form of aggregation of minimum conditions with the AND operator, followed by the combination of a single set value of 0 and 1 in the fuzzy system to produce an appropriate actuator response After the entire system has been prototyped, testing is conducted to determine the responsiveness of the fuzzy program code to changes in the simulated agricultural cultivation land ecosystem. This study found that the fuzzy logic program code embedded in the nodeMCU8266 microcontroller effectively controls the spraying duration of the pump in response to various simulated environmental conditions within 3.6 seconds.
Integration Of Open CV LBF Model To Detect Masks In Health Protocol Surveillance Systems Yovi Litanianda; Moh Bhanu Setyawan; Adi Fajaryanto C; Ismail Abdurrozzaq Z; Charisma Wahyu Aditya
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 1 (2024): Article Research Volume 6 Issue 1, January 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i1.3460

Abstract

The Corona Viruses Diseases pandemic that was rife in early 2020 and hit many countries caused discipline to be applied to health protocols. The prevention of physical contact between humans gave rise to new traditions in aspects of human life. Almost all public facilities in Indonesia require visitors to wear masks as a means of preventing exposure to viruses in the air. However, this advice is often ignored by some people. In addition to endangering many people, this condition also makes public facility managers need extra resources in the form of time, energy and costs to ensure this health protocol is implemented. The existence of these problems triggers the emergence of innovations to present a system that provides assurance and convenience in ensuring compliance with health protocols for the use of masks through creative and effective methods. This method is done by utilizing CCTV cameras or webcams at the entrance equipped with an Artificial Intelligence program designed to be able to detect the use of masks on visitors to public facilities, and without the need for other sensors. The detection system is built on the concept of facial biometrics and utilizes the OpenCV LBF model to detector landmarks on a person's face. Based on tests conducted through several scenario, it can be said that the open CV LBF model successfully identified the use of masks within 35 seconds, increasing the reading distance to 2 meters making the process longer. In addition, in indoor lighting conditions, the system experienced 1 detection error with a process time of 18 seconds, while for well-light outdoor conditions the system managed to detect all objects within 10 seconds.
Klasifikasi Jenis Buah Jeruk Menggunakan Metode Convolutional Neural Network: Deep Learning Studi Yazid Fauzan Nur Ashfani; Yovi Litanianda; Rizqy Amalia Putri
Uranus : Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Vol. 2 No. 2 (2024): Juni: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/uranus.v2i2.129

Abstract

This study analyzes the use of deep learning, primarily Convolutional Neural Networks (CNN), to categorize various types of citrus fruits. The study attempts to create an automated system that can accurately categorize citrus fruit kinds using image processing techniques. The collection contains 40 photos of four different citrus fruit types: pomelo, mandarin orange, kaffir lime, and lime. The methodology entails gathering photos, preprocessing them to improve quality, and then training a CNN model to classify the fruit varieties. The results show a high accuracy rate of 95% in classifying fruit types, demonstrating that the CNN model is effective for this task. The findings indicate that increasing the dataset and including other fruit species could significantly boost the system's accuracy.
Implementasi Metode Convolutional Neural Network (CNN) untuk Klasifikasi Jenis Ras Kucing Aliefah Syalma Ratsdea Muftti; Yovi Litanianda
Uranus : Jurnal Ilmiah Teknik Elektro, Sains dan Informatika Vol. 2 No. 2 (2024): Juni: Jurnal Ilmiah Teknik Elektro, Sains dan Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/uranus.v1i2.172

Abstract

This research implements the Convolutional Neural Network (CNN) method to classify the various types of cat breeds that are common in Indonesia. This research attempts to create an automatic system that can definitely and accurately classify and identify the types of cat breeds that exist in Indonesia using image processing techniques. The data used contains a total of 600 images with each folder containing 200 images. Using this CNN method produces a validation accuracy rate of 54% in the process of classifying cat breeds. Research shows that further developing the image processing process will increase the accuracy value of the resulting system.
Co-Authors ., Sugianti Adi Fajaryanto C Aliefah Syalma Ratsdea Muftti Aliyadi Aliyadi Andy Triyanto Andy Triyanto Pujo Raharjo Angga Prasetyo Arief Rahman Yusuf Charisma Wahyu Aditya Fadelan Fadelan Fauzan Masykur Irfan Khoirul Arifin Moh Bhanu Setyawan Moh. Bhanu Setyawan Muhammad Bagus Baihaqi Prasetyo, Angga Rizqy Amalia Putri Sumaji Sumaji Taufiq Abidin Windi Eka Triatma Yazid Fauzan Nur Ashfani Zulkarnain, Ismail Abdurrozzaq