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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Sisfokom (Sistem Informasi dan Komputer) JUSIM (Jurnal Sistem Informasi Musirawas) Jurnal Mnemonic JUSTIN (Jurnal Sistem dan Teknologi Informasi) Informatics, Electrical and Electronics Engineering Journal of Business Management and Economic Development
Slamet Riyadi, Slamet Riyadi
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Recommendation System for Determining the Best Banner Supplier Using Profile Matching and TOPSIS Methods Vitianingsih, Anik Vega; Firmansyah, Deden; Maukar, Anastasia Lidya; Kacung, Slamet; Zangana, Hewa Majeed
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 2 (2024): August 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i2.21635

Abstract

Background: Choosing a banner supplier is a significant challenge for digital printing companies due to the various advantages offered by each supplier, often leading to selections based on subjective aspects such as price and quality. Objective: This research aims to develop a system that determines the best banner supplier to minimize production inefficiencies and maximize profits by comparing two calculation methods, Profile Matching and TOPSIS. Methods: A quantitative study was conducted using transaction data from the last six months. The parameter criteria used in this system include price, quality, delivery, availability, and payment terms. The study compares the effectiveness of Profile Matching and TOPSIS methods in identifying the best supplier. Results: The study results show that the TOPSIS method is superior, yielding 100% accuracy, 84% recall, and a 92% F1-score, outperforming the Profile Matching method. This demonstrates that the correct method and algorithm effectively provide the best alternative recommendations. Conclusion: The results indicate that using the TOPSIS method leads to more accurate and objective decisions based on predetermined criteria. The findings suggest that further research should focus on refining these methods to enhance decision-making in supplier selection.
Economic Innovation for Global Food Crisis: Technology-based Sustainable Solutions Review Judijanto, Loso; Lubis, Mitra Musika; Slamet Riyadi, Slamet Riyadi; Krisprimandoyo, Denpharanto Agung; Koentjoro, Yonny
Journal of Business Management and Economic Development Том 2 № 01 (2024): January 2024
Publisher : Pt. Riset Press International

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59653/jbmed.v2i01.574

Abstract

One of the biggest problems confronting humanity in the twenty-first century is the global food crisis. Global food security is becoming more and more precarious as population growth picks up speed and climate change puts agricultural sustainability and food security in jeopardy. Technology is an important factor for increasing sustainable food systems in order to accomplish this goal. Smart Farming concept combines sensors, data analytics, artificial intelligence, Internet of Things (IoT), and information and communication technology (ICT). In this research paper, the researchers' method of gathering data is documentation studies. This research aims to review technologies that could be utilized to overcome the global food crisis, one of which is smart farming. The society is expected to contribute to collective efforts to create a world free of starvation and abundant food for all through this understanding of smart farming.
Comparative Analysis of SVM and NB Algorithms in Evaluating Public Sentiment on Supreme Court Rulings Maulidiana, Putri Dwi Rahayu; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Hermansyah, David
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol 13, No 2 (2024): JULY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v13i2.2116

Abstract

The legal events that happened to Ferdy Sambo and the Supreme Court’s decision in the cassation triggered emotional reactions and various opinions among the public, especially on social media sites such as Xapps. Some comments reflect people’s concerns about fairness in the legal system. They doubted the integrity of legal institutions or believed that decisions were unfair or in line with vested interests. This research aims to analyze public perceptions of Supreme Court decisions. The research process includes data collection, preprocessing, labeling, weighting, classification using Support Vector Machine and Naïve Bayes, and performance evaluation using a confusion matrix. A dataset of 624 was taken from X apps using the Twitter scraping technique. The lexicon method is used for data labeling, dividing the data into positive, negative, and neutral classes. The analysis results show 46 tweets categorized as positive sentiment, 133 tweets categorized as negative sentiment, and 422 tweets categorized as neutral sentiment. Based on testing with a data ratio of 80:20, both SVM and NB methods show good performance. The SVM criteria showed an accuracy of 0.84, precision of 0.61, recall of 0.78, and f1-score of 0.66, while the NB criteria showed an accuracy of 0.73, precision of 0.37, recall of 0.57, and f1-score of 0.35.
Implementasi Teknologi Leaflet JS dalam Sistem Peta Radar Hujan untuk Meningkatkan Kesiapsiagaan Bencana Gunung Semeru Khusnaini, Geovandi Gamma; Vitianingsih, Anik Vega; Kacung, Slamet; Puspitarini, Erri Wahyu; Wati , Seftin Fitri Ana
Jurnal Teknik Elektro dan Informatika Vol 4 No 1 (2024): Infotron
Publisher : Universitas Islam Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33474/infotron.v4i1.21997

Abstract

Erupsi Gunung Semeru menyebabkan dampak sosial signifikan, termasuk kerusakan infrastruktur dan korban jiwa. Akses informasi yang terbatas memperumit upaya mitigasi bencana, terutama karena erupsi sering terjadi setiap akhir tahun saat musim hujan, yang dipicu oleh lahar naik akibat air hujan di kawah. Radar hujan di wilayah Gunung Semeru sangat penting untuk mengurangi kerusakan dan korban jiwa. Penelitian ini bertujuan mengembangkan website peta radar hujan berbasis Leaflet JS untuk wilayah Gunung Semeru, menyediakan informasi radar hujan dan lokasi kantor BPBD untuk penanggulangan bencana berbasis peta digital. Teknologi yang digunakan mencakup ekstraksi data Radar Gematronik C-Band menjadi visualisasi produk CMAX yang dianalisis dan diplot menggunakan software wradlib-python. Hasil penelitian menunjukkan bahwa aplikasi mampu memantau curah hujan secara real-time dan menampilkan koordinat geografis wilayah curah hujan. Nilai reflektivitas berkisar antara 0 hingga 15 dBZ, menunjukkan intensitas curah hujan di wilayah tersebut. Pengujian aplikasi menunjukkan efektivitas dalam pemantauan real-time curah hujan dan diterima dengan baik oleh 90% responden, meskipun ada rekomendasi peningkatan akurasi radar dan pengujian lebih lanjut. Aplikasi ini bermanfaat bagi BPBD dalam sosialisasi dan masyarakat untuk kesiapsiagaan bencana, terutama saat musim hujan.
ANALISA DAN DESAIN SISTEM INFORMASI KEUANGAN STUDI KASUS PENDIDIKAN GURU RAUDHATUL ATHFAL (PGRA) Pramudita, Krisna Eka; Vitianingsih, Anik Vega; Kacung, Slamet; Maukar, Anastasia Lidya; Wati, Seftin Fitri Ana
JUSIM (Jurnal Sistem Informasi Musirawas) Vol 9 No 1 (2024): JUSIM : Jurnal Sistem Informasi Musi Rawas JUNI
Publisher : LPPM UNIVERSITAS BINA INSAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32767/jusim.v9i1.2246

Abstract

Kesulitan dalam pembuatan laporan keuangan terkait dengan pengelolaan laporan keuangan yang masih banyak dilakukan menggunakan Gmail atau WhatsApp, selanjutnya rincian laporan keuangan tersebut akan dibuat salinan untuk diarsipkan menggunakan Microsoft office Excel. Penelitian ini menghasilkan rancangan sistem informasi keuangan untuk Lembaga Pendidikan Guru Raudhatul Athfal (PGRA). Sistem akan mampu menampilkan informasi keuangan dalam bentuk laporan, mengelola dan mengelompokkan pemasukan dan pengeluaran berdasarkan sumber, tanggal, dan waktu, serta menampilkan persentase hasil analisis kondisi keuuangann antara pemasukan dan pengeluaran. Model pengembangan perangkat lunak dengan pendekatan waterfall yang mencakup langkah-langkah analisis kebutuhan, desainn spesifikasi, implementasi, pengujiann, dan pemeliharaan. Sistem ini akan membantu lembaga dalam pembuatan, pengiriman laporan keuangan, dan arus kas, Hasil penelitian ini mampu membantu dalam keberlanjutan operasional sekolah, menjaga transparansi dan keakuratan manajemen keuangan.
Sentiment Analysis of Public Responses on Social Media to Satire Joke Using Naive Bayes and KNN Putra Selian, Rasyid Ihsan; Vitianingsih, Anik Vega; Kacung, Slamet; Lidya Maukar, Anastasia; Febrian Rusdi, Jack
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13721

Abstract

This study examines the use of Satire Joke as a humorous communication style in conveying criticism of the government through social media. Satire Joke is often used to depict the government's inability to address important social issues, such as slow bureaucratic processes and unfulfilled political promises. The aim of this research is to analyze public sentiment towards Satire Joke expressed on the YouTube social media platform. The methods used in this study are Naïve Bayes and K-Nearest Neighbors (KNN) due to their effectiveness in data classification. The results of this study are expected to help gain an understanding of social issues for the community and public knowledge. This research is also expected to contribute to the development of sentiment analysis methods in the future. The analysis results show that 400 data have neutral sentiment, 850 data have negative sentiment, and 947 data have positive sentiment. Based on testing, both Naive Bayes and KNN methods show good performance. The Naive Bayes method achieved the best accuracy of 90.29%, while the KNN method achieved an accuracy of 60.75%.
PENERAPAN ALGORITMA APRIORI UNTUK PREDIKSI PENJUALAN PT. DELIMA PANDU BERJAYA Prasista, Nurcahyani; Kacung, Slamet; Ananggadipa Swastyastu, Cempaka; Vega Vitianingsih, Anik
Jurnal Mnemonic Vol 7 No 1 (2024): Mnemonic Vol. 7 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v7i1.9428

Abstract

Dalam era saat ini, penjualan produk dibidang kesehatan telah mengalami perkembangan yang cukup pesat. Pada awal pandemi COVID 2019 hingga saat ini mengalami peningkatan minat masyarakat akan penggunaan produk kesehatan. Perfect Health memiliki banyak jenis produk alat kesehatan dan salah satu produk unggulannya yaitu kursi pijat elektrik. Namun permasalahan yang dihadapi perusahaan adalah, banyaknya jenis produk kursi pijat elektrik sehingga sering terjadi penumpukan satu jenis produk dan sulit menentukan produk mana yang diminati konsumen. Berdasarkan hal tersebut, perusahaan dapat melakukan penerapan data mining menggunakan algoritma apriori yang memiliki tujuan yaitu untuk mengetahui pola asosiasi antar produk serta produk yang sering dibeli oleh konsumen, sehingga informasi tersebut berguna bagi perusahaan dan dapat dimanfaatkan sebagai prediksi stok penjualan. Hasil penerapan data mining menggunakan algoritma apriori dengan minimal support 7% dan minimal confidence 34% terdapat 2 pola asosiasi final yang terbentuk yaitu, apabila konsumen membeli perfect fit 5 maka produk selanjutnya yang akan dibeli adalah zensure 2 dengan support 8.46%, confidence 36.67%, uji lift 1.32 dan apabila konsumen melakukan pembelian perfect relaxer maka produk selanjutnya yang akan dibeli adalah BFS dengan support 7.69 confidence 35.71 dan uji lift 1.50.
ANALISIS SENTIMEN TERHADAP LAYANAN SAMSAT DIGITAL NASIONAL (SIGNAL) MENGGUNAKAN METODE SVM Kacung, Slamet; Pamungkas Putra Bagyana, Caesare; Cahyono, Dwi
Jurnal Mnemonic Vol 7 No 1 (2024): Mnemonic Vol. 7 No. 1
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v7i1.9557

Abstract

Peningkatan signifikan dalam penggunaan pelayanan publik secara digital telah terjadi dalam kurun waktu tiga tahun terakhir. Perubahan ini dipicu oleh dampak wabah Covid-19 di Indonesia, yang mendorong sektor bisnis dan pelayanan untuk berinovasi guna terus memenuhi kebutuhan masyarakat. Dalam hal ini, Korps Lalu Lintas POLRI telah meluncurkan aplikasi bernama Samsat Digital Nasional (SIGNAL) untuk memudahkan pembayaran pajak kendaraan bermotor, menunjukkan komitmen dalam memperbaiki pelayanan publik melalui platform digital. Namun, dalam prakteknya, beberapa pengguna sering mengalami kendala seperti notifikasi kesalahan ketika melakukan pendaftaran seperti verifikasi wajah, kode otp dan verifikasi KTP, kemudian bug dalam penggunaan aplikasi seperti perizinan aplikasi dalam mengakses kamera pada beberapa versi android, bahkan kegagalan transaksi pembayaran saat menggunakan aplikasi SIGNAL. Menghadapi tantangan ini, sentiment analysis digunakan untuk mengevaluasi persepsi masyarakat Selain itu, hasil prediksi dari tiga kernel yang terdapat dalam metode klasifikasi Support Vector Machine (SVM) dan kernel Linier mencapai 96.2%, RBF mencapai 94.12%, polynomial mencapai 85.5%. Namun hasil evaluasi menggunakan KFold linier mencapai 97.65%, KFold RBF mencapai 97.86%, dan KFold polynomial sebesar 69.36%.
Expert System Application for Determining Toddler Nutrition Status Using the Mamdani Fuzzy Method Kacung, Slamet; Vitianingsih, Anik Vega; Sufianto, Dani; Maukar, Anastasya Lidya; Marisa, Fitri
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 12, No 3 (2024)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v12i3.75976

Abstract

Malnutrition is still a national issue that affects many regions in Indonesia. The use of the Kartu Menuju Sehat (KMS) is considered less than optimal because of frequent recording errors due to the loss of the card, making it impossible to properly monitor the nutritional status of toddlers. In addition, people, especially parents, want to know whether their toddler's diet is adequate or not. Based on these problems, an application is needed to determine the nutritional status of toddlers. This research is important to assist medical personnel in assessing the nutritional status of toddlers and can be relied upon for accuracy through an expert system application. This research aims to develop an expert system application that utilizes the Fuzzy Mamdani method to identify the nutritional status of toddlers based on weight, age, height, and arm circumference parameters. The stages in this research include identifying parameters that affect nutritional status through sources of expertise from doctors, determining sets and rules in the fuzzy method, system implementation, system evaluation, and optimization. The results stated that the Fuzzy Mamdani method has an accuracy value of 90.2% in detecting the nutritional status of toddlers. The acceptance test of the application display assessment resulted in 92.5%, the ease of use of the application was 85.83%, and system analysis resulted in 90.83%.
Co-Authors Ananggadipa Swastyastu, Cempaka Anastasia Lidya Maukar Anik Vega Vitianingsih Denpharanto Agung Krisprimandoyo DWI CAHYONO Febrian Rusdi, Jack Firmansyah, Deden Hermansyah, David Judijanto, Loso Khusnaini, Geovandi Gamma Lidya Maukar, Anastasia Lubis, Mitra Musika MARIFANI FITRI ARISA Maukar, Anastasya Lidya Maulidiana, Putri Dwi Rahayu Pamungkas Putra Bagyana, Caesare Pramudita, Krisna Eka Prasista, Nurcahyani Puspitarini, Erri Wahyu Putra Selian, Rasyid Ihsan Sufianto, Dani Vega Vitianingsih, Anik Wati , Seftin Fitri Ana Wati, Seftin Fitri Ana Yonny Koentjoro Zangana, Hewa Majeed