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All Journal IPTEK The Journal of Engineering JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer POSITIF JAIS (Journal of Applied Intelligent System) Register: Jurnal Ilmiah Teknologi Sistem Informasi JOIV : International Journal on Informatics Visualization Journal of Information Technology and Computer Science (JOINTECS) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Generation Journal Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Jurnal Jaringan Telekomunikasi Jurnal Pengabdian Polinema Kepada Masyarakat Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Polinema (JIP) Jurnal Pengabdian Kepada Masyarakat
Mustika Mentari
Politeknik Negeri Malang
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PENERIMAAN MAHASISWA BARU JALUR BIDIKMISI MENGGUNAKAN METODE TOPSIS (STUDI KASUS : POLITEKNIK NEGERI MALANG) Dwi Puspitasari; Mustika Mentari; Fitrah Arif Gunawan
Jurnal Informatika Polinema Vol. 4 No. 1 (2017): Vol 4 No 1 (2017)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v4i1.146

Abstract

Program Bantuan Biaya Pendidikan Bidikmisi yaitu bantuan biaya pendidikan bagi calon mahasiswa tidak mampu secara ekonomi dan memiliki potensi akademik baik untuk menempuh pendidikan di perguruan tinggi pada program studi unggulan sampai lulus waktu. Selama ini proses penyeleksian mahasiswa baru jalur bidikmisi di Politeknik Negeri Malang masih dilakukan secara manual dengan menggunakan Microsoft Excel yang kemudian dilakukan proses sorting dengan satu persatu melihat persyaratan dan kriteria penilaian calon mahasiswa baru jalur bidikmisi, terdapat beberapa permasalahan dalam melakukan proses penyeleksian penentuan penerimaan mahasiswa baru bidikmisi, diantaranya membutuhkan ketelitian dan waktu yang sangat lama. Pada penelitian ini dibuat suatu sistem yang dapat membantu proses seleksi penentuan penerimaan mahasiswa baru jalur bidikmisi berdasarkan persyaratan dan kriteria yang telah ditentukan. Sistem ini menggunakan Metode Technique for Order Performance by Similarity to Ideal Solution (TOPSIS), ada 5 tahapan dalam metode TOPSIS yaitu matriks keputusan normalisasi, matriks keputusan normalisasi terbobot, matriks solusi ideal positif (A+) dan solusi ideal negatif (A-), menentukan jarak antara nilai setiap alternatif dengan matriks solusi ideal positif (D+) dan matriks solusi ideal negatif (D-), menghitung nilai preferensi. Sistem Pendukung Keputusan ini telah diuji dengan membandingkan pengambilan keputusan dengan SPK dan No-SPK. Berdasarkan hasil pengujian tersebut, dari kedua proses dan hasil yang dilakukan secara bersamaan secara real time dapat menghasilkan peningkatan pengambilan keputusan dengan selisih waktu yang lebih cepat dengan menggunakan SPK.
BUKU KAS BERBASIS WEBSITE PADA USAHA KATERING DI PANTI ASUHAN PUTRI AISYIYAH MALANG Dimas Wahyu Wibowo; Eka Larasati Amalia; Mustika Mentari; Ahmadi Yuli Ananta; Muhammad Shulhan Khairy; Farida Ulfa; Meuti Zari Annisa; Ivan Abdurrafie; Irsyadha Alfyrdhousi Redhysyahputra
Jurnal Pengabdian kepada Masyarakat Vol. 8 No. 2 (2021): JURNAL PENGABDIAN KEPADA MASYARAKAT 2021
Publisher : P3M Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Community Service, which becomes the main discussion in this article, shows the real role of the world of information technology in helping community service partners. Aisyiyah Putri Orphanage (PAP'A) Malang, as the community service partner, has a catering business and many customers from universities, or hospitals, as well as other communities. The growing number of PAP'A's catering business customers require special handling of the documentation of the expenditure and income, to this point, the recording of the cash book and the preparation of financial reports are still done manually on paper, books or using excel. This has the impact of data inaccuracy due to human error, difficulty in data tracing, or receipts and bills for data recap are sometimes missing and making it difficult to find detailed information about orders in PAP'A catering business. To overcome this problem, developing a website-based cash book to assist and facilitate information on the expenditure and income in PAP'A's catering business is required. Making a web-based digital cash book application can make it easier and make cash flow information and financial reports neater and easier to trace. The partner of this community service activity will benefit from increasing the quality of knowledge and mastery of human resources in the field of digitizing digital ledgers. This will be a provision for the orphanage manager to be able to make income and expenditure reports
An Experimental Study on Deep Learning Technique Implemented on Low Specification OpenMV Cam H7 Device Asmara, Rosa Andrie; Rosiani, Ulla Delfana; Mentari, Mustika; Syulistyo, Arie Rachmad; Shoumi, Milyun Ni'ma; Astiningrum, Mungki
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.2299

Abstract

This research aims to identify and recognize the OpenMV Camera H7. In this research, all tests were carried out using Deep Machine Learning and applied to several functions, including Face Recognition, Facial Expression Recognition, Detection and Calculation of the Number of Objects, and Object Depth Estimation. Face Expression Recognition was used in the Convolutional Neural Network to recognize five facial expressions: angry, happy, neutral, sad, and surprised. This allowed the use of a primary dataset with a 48MP resolution camera. Some scenarios are prepared to meet environment variability in the implementation, such as indoor and outdoor environments, with different lighting and distance. Most pre-trained models in each identification or recognition used mobileNetV2 since this model allows low computation cost and matches with low hardware specifications. The object detection and counting module compared two methods: the conventional Haar Cascade and the Deep Learning MobileNetV2 model. The training and validation process is not recommended to be carried out on OpenMV devices but on computers with high specifications. This research was trained and validated using selected primary and secondary data, with 1500 image data. The computing time required is around 5 minutes for ten epochs. On average, recognition results on OpenMV devices take around 0.3 - 2 seconds for each frame. The accuracy of the recognition results varies depending on the pre-trained model and the dataset used, but overall, the accuracy levels achieved tend to be very high, exceeding 96.6%.
Pengenalan Jenis Tanaman Mangga Berdasarkan Bentuk dan Tekstur Daun Menggunakan Kecerdasan Artifisial K-NearestNeighbor (KNN) dan Fusi Informasi Sumari, Arwin Datumaya Wahyudi; Syahbana, Muhammad Rifky; Mentari, Mustika
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 4: Agustus 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021844392

Abstract

Memilih tanaman mangga yang sesuai dengan yang diinginkan menjadi sebuah tantangan dihadapkan pada tanaman marga Mangifera yang ada saat ini. Kesalahan pemilihan jenis tanaman mangga dapat menyebabkan kekecewaan pada pembeli dan menurunkan kepercayaan kepada penjual tanaman mangga karena dapat dianggap memberikan jenis tanaman yang salah. Permasalahannya adalah jenis tanaman mangga dapat diketahui setelah tanaman tersebut berbuah. Oleh karena itu, dalam upaya mereduksi kesalahan dalam pemilihan sebelum melakukan pembelian tanaman mangga, maka dirancang  dan dibangun sebuah sistem pencitraan digital untuk pengenalan jenis tanaman mangga berdasarkan bentuk dan tekstur daun menggunakan metode Kecerdasan Artifisial K-Nearest Neighbor (KNN) yang digabungkan dengan Fusi Informasi guna memperoleh hasil klasifikasi dengan akurasi yang lebih baik. Data citra daun empat macam daun tanaman mangga yakni jenis Gadung, Lalijiwo, Golek dan Irwin, diproses menggunakan metode Local Binary Pattern (LBP) dan Entropy untuk ekstraksi fitur tekstur, dan metode Rectangularity untuk ekstraksi fitur bentuk. Kedua macam fitur tersebut difusikan menjadi masukan bagi pengklasifikasi KNN. Berdasarkan dari hasil-hasil pengujian, K-NN berhasil mengenali keempat jenis tanaman mangga tersebut dengan akurasi tertinggi sebesar 70% pada nilai K = 5, K = 9, K = 10 dan K = 11. Dari hasil pengujian juga diperoleh hasil bahwa fusi informasi mampu mempercepat sistem mengenali jenis tanaman mangga sebesar 0,11 detik. AbstractChoosing the right desired Mango plant is a challenge faced with various types of the existing Mangifera clan plants. The wrong choice of Mango plant species can end up with buyer disappointment and reduce the trust to the seller because it can be considered as providing the wrong type of plant. This happened because the type of Mango plant can only be identified after it bears fruit. In the effort to reduce such error, a digital imaging system was designed and built for recognizing the  types of Mango plants based on the leaf shape and texture using Artificial Intelligence’s K-Nearest Neighbor (KNN) combined with Information Fusion to accelerate the classification with a consistent classification results. The image data consists of four kinds of Mango plant leaves, namely Gadung, Lalijiwo, Golek and Irwin. The leaf texture feature was extracted using the Local Binary Pattern (LBP) and Entropy methods, while the leaf shape feature was extracted using the Rectangularity method. The two features are fused as the input for the KNN classifier. Based on the test results, KNN was able to identify the four types of the Mango plant with the highest accuracy of 70% at values of K = 5, K = 9, K = 10, and K = 11. Besides that, it is also obtained a result that, the information fusion is able to speed up the recognition the types of Mango by 0.11 seconds.
Detecting Objects Using Haar Cascade for Human Counting Implemented in OpenMV Mentari, Mustika; Andrie Asmara, Rosa; Arai, Kohei; Sakti Oktafiansyah, Haidar
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 9 No 2 (2023): July
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v9i2.3175

Abstract

Sight is a fundamental sense for humans, and individuals with visual impairments often rely on assistance from others or tools that promote independence in performing various tasks. One crucial aspect of aiding visually impaired individuals involves the detection and counting of objects. This paper aims to develop a simulation tool designed to assist visually impaired individuals in detecting and counting human objects. The tool's implementation necessitates a synergy of both hardware and software components, with OpenMV serving as a central hardware device in this study. The research software was developed using the Haar Cascade Classifier algorithm. The research process commences with the acquisition of image data through the OpenMV camera. Subsequently, the image data undergoes several stages of processing, including the utilization of the Haar Cascade classifier method within the OpenMV framework. The resulting output consists of bounding boxes delineating the detection areas and the tally of identified human objects. The results of human object detection and counting using OpenMV exhibit an accuracy rate of 71%. Moreover, when applied to video footage, the OpenMV system yields a correct detection rate of 73% for counting human objects. In summary, this study presents a valuable tool that aids visually impaired individuals in the detection and counting of human objects, achieving commendable accuracy rates through the implementation of OpenMV and the Haar Cascade Classifier algorithm.
PEMBUATAN SISTEM INFORMASI BRANDING DAN MARKETING KAWASAN USAHA MIKRO KECIL MENENGAH YANG BERSINERGI DENGAN KEGIATAN WISATA, PENDIDIKAN KELUARGA (DEWI PELAGA) DI CEMOROKANDANG MALANG Mentari, Mustika; Asmara, Rosa Andrie; Amalia, Eka Larasati; Lestari, Vivin Ayu; Ulfa, Farida; Rahman, Mochamad Faisal; Sabita, Almira Rahma; Ardiansyah, Muhammad Rizqi; Fitriana, Aliza Rizqi
Jurnal Pengabdian kepada Masyarakat Vol. 11 No. 1 (2024): JURNAL PENGABDIAN KEPADA MASYARAKAT 2024
Publisher : P3M Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/abdimas.v11i1.4756

Abstract

The geographical area of Cemorokandang village in Malang has a set of potential Small and Medium Enterprises (SMEs) that have been running for a long time but require technological support in branding and marketing. Currently, most SME groups in Cemorokandang village use the traditional method by entrusting the goods produced to shops around the area. The SMEs are in Dewi Pelaga (Desa Wisata Pendidikan Keluarga). Other potentials owned by Cemorokandang village that need to be managed are the potential for sports, tourism, and education potential. This potential needs to be promoted so that many people know it better. Therefore, it is necessary to have a branding and marketing information system that contains pages describing the potential of SMEs and other support such as sports, education, and tourism tracking places. The website that has been created has been tested, and results were obtained on the point that "The community services activities carried out really provide solutions to the problems faced by partners." Some 75% of partners gave a strongly agreed response, while the other 25% gave an agreeing response. From these results, it can be said that this information system is effective in branding and marketing products owned by SMEs in the Dewi Pelaga area.
Application of Up-Event Applications in Multi Vendor Activity Management Nurhasan, Usman; Mentari, Mustika; Hartati, Kirana; Ningtyas, Noviana
Generation Journal Vol 4 No 2 (2020): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v4i2.14291

Abstract

Event organizer dapat didefinisikan sebagai pengorganisasian sebuah kegiatan yang dikelola secara profesional, sistematis, efisien dan efektif. Kegiatannya meliputi konsep (perencanaan), pelaksanaan hingga pengawasan. Saat ini sistem penyebaran informasi event dilakukan dengan cara mempromosikan eventmelalui website, social media dan juga masih banyak event organizer yang melakukan penjualan tiket event secara offline dengan membuka stand di event lain maupun di daerah tertentu. Pendistribusian tiket dengan cara ini menimbulkan beberapa masalah yaitu terjadinya antrian panjang yang akan menghabiskan banyak waktu dan adanya biaya tambahan untuk mendirikan stand tersebut. Peluang untuk penyebaran informasi event dan penjualan tiket secara online mulai dilirik oleh event organizer sebagai lahan yang menjanjikan karena menyediakan informasi yang akurat serta menghemat waktu dan juga biaya saat promosi. Dari permasalahan tersebut, kami merancang sebuah aplikasi “Up-Event” sistem ini berguna untuk membantu event organizer dalam penjualan tiket event. Sistem ini selain berbasis website juga berbasis android. Di sistem ini dilengkapi fitur absensi peserta event menggunakan teknologi QR Code. Selain untuk mengurangi penggunaan kertas yang terlalu banyak dan antrian yang panjang saat absensi peserta, QR Code juga menjamin keamanan event karena dapat diketahui keaslian tiket yang digunakan sebagai syarat masuk peserta kedalam tempat acara.
Co-Authors Abdallah Darussalam Chandra Abidatul Izzah Aldi Surya Pranata Amin Anis Kuddah Ananta, Ahmadi Yuli Andrie Asmara, Rosa Ardiansyah, Muhammad Rizqi Arie Rachmad Syulistyo Arwin Datumaya Wahyudi Sumari Astiningrum, Mungki Budi Harijanto, Budi Chastine Fatichah Chintya Puspa Dewi Chintya Puspa Dewi Dimas Shella Charlinawati Dimas Wahyu Wibowo Dwi Puspitasari DWI PUSPITASARI Efendi, Muhamammad Elfan Eka Larasati Amalia Ermi Pristiyaningrum Farida Ulfa Farida Ulfa Fathur Romadhon Fitrah Arif Gunawan Fitriana, Aliza Rizqi Ginardi, R.V. Hari Gunawan, Fitrah Arif Hartati, Kirana Imam Fahrur Rozi Indra Dharma Wijaya Irsyadha Alfyrdhousi Redhysyahputra Ivan Abdurrafie Kohei Arai Lia Agustina Maria Puji Rahayu Meuti Zari Annisa Muhamammad Elfan Efendi Muhammad Shulhan Khairy Nabilah Argyanti Ardyningrum Nadia Layra Aziza Naufal Yukafi Ridlo Ningtyas, Noviana Nobuo Funabiki Nur Hayatin Pranata, Aldi Surya Putra Prima Arhandi, Putra Prima R.V Hari Ginardi Rahardhiyan Wahyu Putra Rahman, Mochamad Faisal Ratih Kartika Dewi Romadhon, Fathur Rosa Andrie Asmara Rosa Andrie Asmara Rosiani, Ulla Delfiana Sabita, Almira Rahma Sakti Oktafiansyah, Haidar Shoumi, Milyun Ni’ma Syahbana, Muhammad Rifky Tita Wijayanti Ulfa, Farida Ulla Delfana Rosiani Ulla Delfiana Rosiani Usman Nurhasan Vivi Nur Wijayaningrum Vivin Ayu Lestari Widiareta Safitri Yan Watequlis Syaifudin Yuita Arum Sari