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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Reconfigurable and Embedded Systems (IJRES) International Journal of Advances in Applied Sciences IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Lensa: Kajian Kebahasaan, Kesusastraan, dan Budaya Dinamik Jurnal Simetris Abdimas Telematika Jurnal Transformatika KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Abdimas BSI: Jurnal Pengabdian Kepada Masyarakat IJCIT (Indonesian Journal on Computer and Information Technology) Voice Of Informatics STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Jurnal Teknologi Informasi dan Multimedia Jurnal Teknologi Dan Sistem Informasi Bisnis Scientific Journal of Informatics Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Sistem Komputer dan Informatika (JSON) Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Teknologi Informasi dan Komunikasi Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) International Journal of Quantitative Research and Modeling JITSI : Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Informatika Teknologi dan Sains (Jinteks) SmartComp Tematik Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Muria Pengabdian Masyarakat Jurnal DIMASTIK
Susanto Susanto
Universitas Semarang
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences

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APLIKASI PENYEWAAN PERALATAN CAMPING DAN HIKING PADA PANDANARAN OUTDOOR BERBASIS WEB Susanto, Susanto; Anggraini, Lila; Kurniawan, Nurdin; Cahyono, Yudi
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol 15 No 1 (2024): Maret
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v15i1.830

Abstract

Pandanaran outdoor is one of the rental service companies or rental of camping and hiking equipment. However, the lack of use of technology in the process of renting equipment and conveying information about what equipment can be rented on a particular day makes it difficult for customers to carry out the rental process. Pandanaran Outdoor itself still uses manual recording in its rental process. With the advancement of technology and on the basis of the need for transaction management, data management, and information delivery, it is necessary to create a web-based camping and hiking equipment rental application at Pandanaran Outdoor, this website is designed using CodeIgniter, PHP, Visualcode, Bootstrap, Javascript, and MySQL Database. The system method used in this research is the waterfall method, the results obtained are used to describe the sequence of software development processes as a cycle in the flow of making rental applications. The presence of this application is expected to speed up and simplify the process of renting camping and hiking equipment at Pandanaran Outdoor.
PELATIHAN WEB CONTENT PRODUK UMKM PROPINSI JAWA TENGAH Nugroho, Atmoko; Susanto, Susanto; Ardi Pramono, Basworo
TEMATIK Vol. 2 No. 1 (2022): Januari
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/tmt.v2i1.3054

Abstract

Di Era Revolusi Industri 4.0 dimana internet mulai memiliki peranan   penting dalam setiap aspek kehidupan, terutama bidang usaha. Sehingga pelaku usaha berusaha untuk mengikuti perkembangan internet dan teknologinya agar tetap eksis dalam dunia usaha. Salah satunya adalah dengan pembuatan dan pengelolaan website.   Web content merupakan bagian dari pengelolaan website, oleh pengelola website, isi website (web content) akan diatur informasinya agar tidak ketinggalan. Tujuannya agar pengguna atau pelanggan mengetahui informasi terbaru dari pihak pemilik website.Usaha Mikro, Kecil, Menengah (UMKM) Propinsi Jawa Tengah tersebar di seluruh wilayah administratif Propinsi Jawa Tengah, khususnya Kota Semarang dengan beragam jenis usaha produk ataupun jasa dan dengan sebaran usaha yang beragam. Pelaku usaha, khususnya UMKM tentunya harus bisa mengikuti perkembangan teknologi agar tidak kehilangan peluang usaha, oleh sebab itu perlu pelatihan promosi melalui web content.  
Arowana cultivation water quality monitoring and prediction using autoregressive integrated moving average Daru, April Firman; Susanto, Susanto; Adhiwibowo, Whisnumurti
International Journal of Reconfigurable and Embedded Systems (IJRES) Vol 13, No 3: November 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijres.v13.i3.pp665-673

Abstract

Decorative fish is a fish that humans keep for amusement. There are many decorative fish that exist in this world, one of them is known as the Arowana fish (Scleropages Formosus). This fish is known around Asia including in Indonesia. However, to ensure the Arowana is living well is not easy. The water quality inside a farm must follow a strict balance. The pH of the water must not exceed or below 7 pH. Meanwhile, the total dissolved solid (TDS) salt must not exceed 1000 parts per million. If the balance collapsed, the Arowana fish will not grow. Thus, the owner must monitor the water to make sure that the water is ideal. There were many approaches including internet of things (IoT) solutions. However, they have weaknesses with prediction. Because of this reason, this study designed pH and TDS monitoring with autoregressive integrated moving average (ARIMA) as the algorithm. To achieve the solution, this study used experiment methodology as the research fundamental from top to bottom. According to the evaluation, this study found that the accuracy of ARIMA model is 98.12% for pH and 98.86% for TDS. On the contrary, the seasonal autoregressive integrated moving average (SARIMA) model has an accuracy of 98.52% for pH and 99.89% for TDS.
Perbandingan Metode ARAS dan MOORA dalam Seleksi Penerimaan Pegawai Baru Non ASN Susanto, Susanto; Ningrum, Setya; Cahyono, Yudi
Jurnal Sistem Komputer dan Informatika (JSON) Vol 5, No 3 (2024): Maret 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i3.7449

Abstract

The acceptance of new non-ASN candidates is a major problem in recruiting new employees, this happens because of the large number of new prospective employees who register and the number of vacancies that are inadequate, therefore research is carried out that aims to create a decision support system that can speed up the process of recruiting candidates. new employee. The methods used in this research are ARAS (Additive Ratio Assessment) and MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) methods. The selection of this method is able to filter out the most alternatives based on weighting and this method is able to choose goals based on different criteria, namely benefits and costs. The results obtained from the ARAS method are the calculation rankings from the comparison of alternative utility functions with the optimal utility function values, while the results obtained from the MOORA method are the calculation rankings of the maximum and minimum values. From this value, an alternative that meets the criteria through calculations using the ARAS and MOORA methods, the employee alternative chosen is Yuniar Pilakso Angkasa with a final result of 0.935 for the ARAS method and 0.163 for the MOORA method. The results of the Spearman Rank coefficient test obtained a value of 0.9357% for the ARAS method and 0.7428% for the MOORA method, meaning that the two methods have a strong correlation level and can be used in recruiting new non ASN employees.
Implementasi E-Marketing Berbasis Web Pada UD Semeru Jati: Implementasi E-Marketing Berbasis Web Pada UD Semeru Jati Yurista Kumkamdhani, Tirta; Cahyono, Yudi; Ardiyanto, Ilham; Susanto, Susanto
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 23 No 2 (2024): Agustus 2024
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v23i2.9610

Abstract

Sebuah perusahaan dagang bernama UD Semeru Jati memproduksi dan menjual kerajinan kayu dan mebel. dimana kayu jati asli Blora adalah jenis kayu yang digunakan. UD Semeru Jati pada awalnya mengandalkan pemasaran manual untuk model penjualan produknya atau melakukan penjualan langsung antara penjual dan pembeli. Sistem jual beli dioperasikan dengan cara yang lebih realistis saat ini. Penjual dan pembeli tidak perlu berinteraksi secara langsung, melainkan dengan sistem pemasaran ini, pembelian dan penjualan produk dapat dilakukan secara online dan pelanggan dapat menerima informasi dari sumber yang lebih luas, yang diantisipasi untuk meningkatkan penjualan barang-barang terkait furnitur. Sistem e-marketing berbasis web ini dikembangkan dengan memanfaatkan metode prototype, bahasa pemrograman PHP, database MySQL, CMS dan Visual Code sebagai text editor. User (pelanggan) merupakan fungsi prioritas utama dari sistem e-marketing ini. Setiap pengguna dapat melihat berbagai jenis produk yang ada di website dan juga dapat memesan dan melakukan pembayaran melalui transfer bank atau payment gateway. Seorang administrator yang dapat menangani data, mengawasi pesanan produk, mencetak laporan, dan mengawasi pembayaran adalah pilihan sekunder.
Detection of Plastic Bottle Waste Using YOLO Version 5 Algorithm Yasiri, Jamilatur Rizqil; Rastri Prathivi; Susanto
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14242

Abstract

Plastic bottle waste management has become one of the most pressing environmental issues, especially in countries with high plastic usage rates, such as Indonesia. This research uses the YOLOv5 (You Only Look Once version 5) algorithm to detect plastic bottle waste automatically. The YOLOv5 algorithm was chosen because it has efficient detection performance and high accuracy in small object recognition. The dataset consists of 500 images of plastic bottles obtained through cameras and internet sources. The data is processed through several stages: annotation (bounding box and labeling using Roboflow), split dataset (70% for training, 20% for testing, and 10% for validation), pre-processing (resizing images to 460x460 pixels), and augmentation (adding data variations to improve model performance). Training and evaluation of the YOLOv5 model using the precision metric of 89.8% indicates the ability of the model to accurately identify plastic bottles from the overall prediction, recall of 83.1% indicates the success of the model in detecting the majority of plastic bottles in the test data, and mean average precision (mAP) of 89.2% represents the average precision at various prediction thresholds. Test results on varied bottle image test data obtained detection accuracy between 82%-93%, indicating the model can recognize plastic bottles consistently. Sometimes, this model needs help detecting overlapping picture objects. However, this research proves the potential of the yolov5 algorithm as an automated litter detection solution that will be integrated with a system and support faster and better plastic waste management.
Prediksi Lama Masa Tunggu Alumni USM dalam Mendapatkan Pekerjaan dengan Algoritma KNN Cholil, Saifur Rohman; Vydia, Vensy; Susanto, Susanto; Cahyono, Yudi
IJCIT (Indonesian Journal on Computer and Information Technology) Vol 9, No 2 (2024): November 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/ijcit.v9i2.20705

Abstract

Pencarian informasi alumni perguruan tinggi dilakukan supaya dapat menentukan seberapa lama masa yang dibutuhkan agar mendapatkan pekerjaan. Dalam tahap peningkatan mutu sebuah perguruan tinggi, alumni mengambil peran penting, sebab kualitas pembelajaran pada perguruan tinggi dapat dikatakan sudah cukup baik apabila alumninya cepat terserap didalam dunia kerja. Pencarian informasi (tracer study) diperoleh melalui kuesioner yang dibagikan oleh pihak USM Career and graduated Class (UCAC) kepada para alumni. Informasi tersebut terdiri dari data-data para alumni pada tahun 2019-2020 dan kemudian digunakan untuk mendapatkan dan memperkirakan lama waktu tunggu yang dibutuhkan para lulusan USM hingga memperoleh pekerjaan setelah dinyatakan lulus studi sarjana. Algoritma KNN digunakan dalam penelitian ini, hal tersebut dikarenakan metode KNN mampu memprediksi masa tunggu alumni dibandingkan dengan metode lainnya. Adapun kompetensi yang berdampak terhadap masa tunggu alumni dalam mendapatkan pekerjaan dapat diperoleh melalui hasil analisis penelitian ini, seperti keterampilan dalam menggunakan komputer, manajemen pengolahan waktu, kemampuan dalam menganalisis, serta disiplin ilmu. Hasil implementasi algoritma KNN dengan mencoba nilai K dari 1-100 yang memiliki akurasi tertinggi mencapai 98,84%. A search for information on university alumni was carried out in order to determine how long it would take to get a job. In the stage of progress in the quality of a university, alumni play an important role, because the quality of learning at a university can be said to be quite good if the alumni are quickly absorbed into the world of work. The search (tracer study) was obtained through a questionnaire distributed by the USM Career and Graduate Class (UCAC) to alumni. This information consists of data from alumni in 2019-2020 and is then used to obtain examples of the length of time to employment needed for USM graduates to get a job after graduating from undergraduate studies. The KNN algorithm was used in this research, this is because the KNN method is able to predict the time to employment for alumni compared to other methods. Competencies that have an impact on the time to employment for alumni to get a job can be obtained through the results of this research analysis, such as skills in using computers, time management, analytical skills, and scientific discipline. The results of implementing the KNN algorithm by trying K values from 1-100 have the highest accuracy reaching 98.84%.
Implementasi Sistem Pendukung Keputusan Promosi Kenaikan Jabatan Dengan Metode TOPSIS Berbasis Web Putri, Nela Aulina; Susanto, Susanto; Khoirudin, Khoirudin
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 14, No 1 (2025): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v14i1.6991

Abstract

Promosi kenaikan jabatan adalah proses peningkatan posisi atau jabatan seorang karyawan dalam suatu organisasi atau perusahaan. Proses ini biasanya melibatkan perpindahan karyawan dari satu tingkat pekerjaan ke tingkat yang lebih tinggi, disertai dengan peningkatan tanggung jawab, otoritas, dan umumnya kompensasi Penelitian ini berfokus pada implementasi Sistem Pendukung Keputusan (SPK) untuk promosi kenaikan jabatan di PT. Mitra Karsa Utama dengan menggunakan metode Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). PT. Mitra Karsa Utama mengalami kesulitan dalam menentukan karyawan yang layak untuk mendapatkan promosi secara objektif dan efektif. SPK yang dibangun bertujuan untuk membantu manajemen dalam proses pengambilan keputusan dengan mempertimbangkan berbagai kriteria yang relevan seperti kinerja, pengalaman kerja, keterampilan, dan kontribusi terhadap perusahaan. Metode TOPSIS dilakukan dengan menghitung jarak kedekatan relatif untuk setiap alternatifnya. Nilai kedekatan relatif diurutkan berdasarkan peringkatnya dan kemudian digunakan oleh HRD sebagai pertimbangan atau promosi. Saat menguji hasilnya, bobot setiap kriteria diubah untuk mengetahui peringkat mana yang memiliki dampak paling besar terhadap pengambil keputusan. Hasil pengujian menunjukkan bahwa sistem ini berhasil mengimplementasikan metode TOPSIS dengan bobot yang berbeda-beda tanpa mempengaruhi hasil evaluasi karyawan yang ada
Klasifikasi Gempa Bumi Berdasarkan Magnitudo Menggunakan Metode Logistic Regression Mar’atuzzulfa, Salma; Prathivi, Rastri; Susanto, S
Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Vol 6, No 1 (2025): Edisi Januari
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/kesatria.v6i1.564

Abstract

The purpose of this study is to categorize areas in Indonesia that are potentially prone to earthquakes using the logistic regression algorithm. Variables such as latitude, longitude, depth, and magnitude are used to analyze 118 data points of natural disasters that occurred in Indonesia in 2023. As much as 40% of the data is used for testing, while 60% is used for training. The magnitudes are high, medium, and low. The logistic regression method is used to determine the level of health in the area and assess the relationship between variables. The study's findings indicate that the model has an accuracy of 93.62%, precision of 94%, recall of 93%, and F1 skor of 93% overall. In addition, the evaluation of the model's kinerja using the confusion matrix indicates that algorithms might associate a given category with a high sensitivity to error. By identifying data points and creating Logistic regression can assist in developing more effective bencana mitigation strategies by identifying data points and producing accurate predictions. As a result, it is believed that the general public can reduce the amount of dampak gempa bumi.
OPTIMASI METODE RANDOM FOREST UNTUK KLASIFIKASI RISIKO OBESITAS BERDASARKAN POLA MAKAN Rosidah, Nafiati; Prathivi, Rastri; Susanto, Susanto
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 1 (2025): EDISI 23
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i1.5065

Abstract

Pola makan tidak sehat, seperti mengonsumsi makanan cepat saji dan mengurangi asupan sayur serta buah, merupakan salah satu penyebab utama obesitas, yang menjadi masalah kesehatan global. Obesitas dapat meningkatkan risiko penyakit tidak menular seperti diabetes, hipertensi, dan penyakit jantung. Dengan menggunakan algoritma Random Forest, penelitian ini bertujuan untuk mengembangkan model prediksi risiko obesitas berbasis pola makan. Data yang digunakan terdiri dari 1.610 record dengan 15 atribut, yang diambil dari dataset publik. Tahapan penelitian meliputi pengumpulan data, preprocessing, pembagian data menjadi data latih dan uji, implementasi model, optimasi hyperparameter dengan Grid Search, dan evaluasi model. Hasil penelitian menunjukkan bahwa model Random Forest yang dioptimasi mampu mencapai akurasi sebesar 85,4%. Frekuensi mengonsumsi makanan cepat saji, jumlah makanan utama setiap hari, kebiasaan ngemil, dan konsumsi sayur adalah beberapa variabel penting yang memengaruhi prediksi. Model ini diharapkan dapat membantu pencegahan dan penanganan obesitas secara lebih efektif sekaligus memberikan wawasan tambahan untuk pengembangan sistem prediksi kesehatan berbasis data
Co-Authors Abriansah, Fausta Rizky Adellia Hilda Putri Agusto, Valien Rezky Ahmad Maulana Arif Alauddin Maulana Hirzan Albani, Hafidz Zamzam Alda Hani Meidina Anggraini, Nabela Yulian April Firman Daru Ardiyanto, Ilham Aria Hendrawan, Aria Astrid Novita Putri, Astrid Atmoko Nugroho Basworo Ardi Pramono Cahyono, Yudi Cholil, Saifur Rohman Dewanti, Tita Risa Dewi Nurdiyah, Dewi Dimas Dwi Budiarjo Edi Widodo, Edi Febrian Wahyu Christanto Ferdian, Praditya Rendi Firdaus, Azmi Maulana Handayani, Sri Harminanto, Burhan Herlambang, Mahjid Jati, Purbo Pangestu Satria Jovita Khoirudin Khoirudin, Khoirudin Kurniawan, Nanda Dwi Kurniawan, Nurdin Lila Anggraini Luna, Asyira Andhini Mar’atuzzulfa, Salma Masithoh, Mauluddiah Maulana Bahrul Alam Mojang Widhiyani Ashari Muhsinin, Muhammad Muhsinin Mukhammad Said Riza Zudi Muzzakin, Muhamad Ningrum, Setya Nurtriana Hidayati Pasha, Radhita Amelia Patmawati, Putri Pipit Aryani Pradana, Adam Prind Triajeng Pungkasanti, Prind Triajeng Pulung Nurtantio Andono Puspita Sari, Fila Putri, Nela Aulina ramadhani, jovita wayan Rangga Rahmat Prayuda Rastri Prathivi Rastri Prathivi Rati - Riana Romadhoni, Gilang Akbar Rosidah, Nafiati Saifur Rohman Cholil Siti Asmiatun, Siti Syahruli, Mauriski Titis Handayani Vensy Vydia Whisnumurti Adhiwibowo Widyandayani, Anita Galih Yasiri, Jamilatur Rizqil Yekti Adi Prasetyo Yogi Agus Setiawan Yudi Cahyono Yudi Prayoga Yuliarti, Sadna Putri Yurista Kumkamdhani, Tirta