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All Journal Jurnal Informatika Upgris JURNAL MEDIA INFORMATIKA BUDIDARMA JURIKOM (Jurnal Riset Komputer) JSAI (Journal Scientific and Applied Informatics) Jurnal Manajemen Informatika dan Sistem Informasi Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) KLIK: Kajian Ilmiah Informatika dan Komputer Dikmas: Jurnal Pendidikan Masyarakat dan Pengabdian International Journal Software Engineering and Computer Science (IJSECS)
Utiarahman, Siti Andini
Universitas Ichsan Gorontalo
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering

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APLIKASI TOUR GUIDE MENGGUNAKAN TEKNOLOGI QR CODE BERBASIS ANDROID PADA MUSEUM PROVINSI GORONTALO Misrawati Aprilyana Puspa; Sulistiawati Ahmad; Siti Andini Utiarahman
JSAI (Journal Scientific and Applied Informatics) Vol. 5 No. 2 (2022): Juni 2022
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v5i2.3362

Abstract

Museum Provinsi Gorontalo yang disebut juga dengan Museum Popa Eyato merupakan museum yang dibangun oleh Provinsi Gorontalo. Fakta saat ini menunjukkan bahwa sekarang ini minat untuk mendatangi museum khususnya museum Popa Eyato masih sangat kurang dikarenakan dengan perkembangan zaman saat ini yang lebih memilih mengunjungi tempat atau lokasi yang modern seperti pusat perbelanjaan, Mall dan Café. Namun kondisi Negara yang saat ini masih mengalami pandemi Covid 19 sangat tidak memungkinkan juga untuk masyarakat atau wisatawan untuk dapat mengunjungi lokasi wisata khususnya museum. Selain itu kendala lainnya yaitu pelayanan yang ada di museum juga mempengaruhi minat wisatawan untuk mengunjungi museum. Pelayanan yang dimaksud adalah memberikan informasi yang bermanfaat dengan memanfaatkan teknologi tentunya. Informasi yang diinginkan oleh wisatawan harus diberikan oleh tour guide (pemandu) yang tentunya memahami tentang info sejarah dari benda/artefak yang terdapat dimuseum. Tujuan penelitian ini adalah merancang aplikasi tour guide museum berbasis android untuk meningkatkan efektifitas dan efisiensi pelayanan Museum Popa Eyato Provinsi Gorontalo serta memperkecil peluang pengerusakan dan pencurian data. Selain itu posisi SDM dapat digantikan dengan teknologi virtual sebagai tour guide agar masyarakat atau wisatawan dapat melihat informasi dari obyek sejarah melalui platform mobile
SISTEM INFORMASI USULAN MUSRENBANG DESA BERBASIS WEB Zufrianto K. Dunggio; Nur Oktavin Idris; Fitriyanti Suleman; Siti Andini Utiarahman
Jurnal Manajemen Informatika dan Sistem Informasi Vol. 5 No. 2 (2022): MISI Juni 2022
Publisher : LPPM STMIK Lombok

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

Abstract

Musyawarah Perencanaan Pembangunan Desa merupakan musyawarah antar warga desa dan pihak terkait untuk membahas permasalahan dan potensi desa dalam daftar usulan rencana pembangunan desa berdasarkan skala prioritas. Data Musrenbang desa di Kabupaten Gorontalo Utara masih direkap dengan menggunakan Microsoft Excel, kemudian dicetak dan berkas tersebut disimpan di lemari arsip, apabila berkas dibutuhkan akan sulit diperoleh karena semakin banyaknya berkas yang menumpuk setiap tahun. Sehingga dalam proses penginputan kembali membutuhkan waktu lama, karena staf Dinas Pemberdayaan Masyarakat dan Desa juga masih harus datang langsung ke kecamatan yang lokasinya cukup jauh untuk mengumpulkan usulan Musrenbang dari desa. Untuk itu perlu adanya sistem informasi yang dapat memudahkan dalam menginput usulan rencana kerja dan pembangunan Desa. Sistem ini dirancang dengan bahasa pemrograman PHP, basis data MySQL, metode SDLC dan memanfaatkan diagram UML. Hasil penelitian ini berupa sistem informasi berbasis web yang bertujuan untuk mengelola data usulan Musrenbang Desa agar informasi data Musrenbang Desa dapat dikoordinir dan dapat diakses oleh pihak-pihak terkait sehingga mempercepat proses pembuatan laporan Musrenbang Desa.
Penerapan Metode Analitycal Hierarchy Process dalam Sistem Pendukung Keputusan Kelayakan Rumah Tangga Penerima Listrik Gratis Siti Andini Utiarahman; Hastuti Dalai
JURIKOM (Jurnal Riset Komputer) Vol 9, No 5 (2022): Oktober 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i5.4857

Abstract

One of the government programs includes free electricity connection assistance for underprivileged households through the Targeted Electricity Subsidy (SLTS) program. In implementing the SLTS program, recipients of free electricity must meet several predetermined criteria to qualify as recipients. Every year there are a lot of registrants for RT candidates who receive free electricity in Gorontalo province, so obtaining information takes a long time because accuracy is required in the selection process to determine the eligibility of RT candidates to receive free electricity. The purpose of the study was to apply the AHP method to the decision support system for the eligibility of households receiving free electricity by calculating the value of the priority results of the sub-criteria and the feasibility value. The calculation process is carried out based on the criteria, the results of the priority sub-criteria are obtained where the applicant with a feasibility value = 1 gets a decent status. On the other hand, applicant 2 with a sub-criteria priority of 0.2983 and applicant 3 with a sub-criteria priority of 0.0847 gets an unfeasible status because the value obtained is < 1. So it can be concluded that the AHP method can be used in a decision support system to assist related parties in determining the eligibility of households receiving free electricity
Analisa dan Perancangan Sistem E-Voting Pemilu Raya BEM di Universitas Ichsan Gorontalo: Analisa dan Perancangan Sistem E-Voting Pemilu Raya BEM di Universitas Ichsan Gorontalo sulistiawati Rahayu Ahmad; Siti Andini Utiarahman; Jorry Karim
JSAI (Journal Scientific and Applied Informatics) Vol 5 No 3 (2022): November 2022
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v5i3.1953

Abstract

The Student Executive Board (BEM) is among the organizations in universities formed by students. Through BEM, students can learn to socialize, politics and democracy. Every year Ichsan University conducts BEM ELECTION activities to elect BEM Presidential Candidates. In the process, there is a problem where the BEM ELECTIONS have decreased student political participation because students have to come to campus, and the process of recapitulation of vote counting is quite long. The purpose of the study was to design a web-based e-voting application that all active students can use to participate in the UNISAN BEM ELECTION without having to come directly to campus. The process and results of the UNISAN BEM ELECTIONS were fast, effective and transparent. Data collection techniques carried out observations, interviews and literature studies with system development using the waterfall method. The system design is in the form of a UML diagram. Creation with PHP and MySQL languages for databases. The test results resulted in cyclomatic complexity. In the calculation of cyclomatic complexity, if V(G) = E-N+2, the result is equal to V(G) = P+1. The results of the UNISAN BEM ELECTION research were fast, effective and transparent.
Pelatihan Akuntansi Berbasis SAK-EMKM untuk UKM Menggunakan Aplikasi Pencatatan Informasi Keuangan Mikro Kecil (Si APIK) Maryati Kadir Thalib; Siti Andini Utiarahman; Novita Adam; Nurjana Suleman; Nur Oktavin Idris; Sri Oktavia Dai; Satriadi D. Ali
Dikmas: Jurnal Pendidikan Masyarakat dan Pengabdian Vol 2, No 4 (2022): December
Publisher : Magister Pendidikan Nonformal Pascasarjana Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/dikmas.2.4.1189-1196.2022

Abstract

Pentingnya penyusunan dan penyajian laporan keuangan bagi dunia usaha, khususnya UKM, telah mendorong lahirnya standar keuangan baru yakni Standar Akuntansi Keuangan Entitas Mikro, Kecil, dan Menengah (SAK EMKM) yang diterbitkan oleh Ikatan Akuntan Indonesia (IAI). Standar ini merupakan salah satu standar pelaporan keuangan yang memudahkan penyusunan dan penyampaian laporan akuntansi yang lebih sederhana dan mudah dipahami bagi para pelaku usaha. Tujuan dilaksanakannya kegiatan PKM ini adalah untuk memberikan pelatihan kepada UKM binaan di desa Tinelo tentang cara menyusun laporan keuangan sesuai SAK EMKM dengan menggunakan aplikasi akuntansi berbasis Android Si APIK. Jumlah peserta yang ikut dalam kegiatan pengabdian kepada masyarakat ini sebanyak 8 UMKM binaan. Pengabdian Kepada Masyarakat ini dilaksanakan di Aula Kantor Desa Tinelo berlokasi di jalan Adam Poliama. Hasil PKM ini, seluruh peserta akan dapat menyusun laporan keuangan kegiatan usahanya dengan menggunakan aplikasi akuntansi Si APIK.
Pengembangan Sistem Informasi Pengaduan Eksploitasi Anak Berbasis Android Farid Farid; Siti Andini Utiarahman; Moh. Fachrinanda Putra Bowta
JURIKOM (Jurnal Riset Komputer) Vol 9, No 6 (2022): Desember 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v9i6.5116

Abstract

Children have the right to live, grow and develop and receive protection from violence and discrimination. Exploitation is a complex and modern type of violence against humanity. In the city of Gorontalo there is still a lot of exploitation of children. The Gorontalo city government provides services to the community to be able to report violence and exploitation that occurs in their environment with a web-based complaint information system. The website-based complaint information system is still considered less flexible, because some websites are less responsive. In addition, the complaint website created by the Gorontalo city government is not optimal because it does not have a location tracking feature to find out the location of the complainant. The author aims to develop an Android-based child exploitation complaint information system to be used by the public to report acts of child exploitation to speed up the investigation of reports reported by the public anywhere, anytime and add a tracking location menu to find out the location of the complainant and the feature to send pictures or videos as evidence of the report. complaint. The research uses research and development methods. The results of testing the test case system obtained that the registration module obtained a value of V(G) = 2 and Cyclometic Complexity (CC) = 2, the authors concluded that the logic flow in the registration module in the system designed to run effectively
K-Nearest Neighbor for Gorontalo City Chili Price Prediction Using Feature Selection, Backward Elimination, and Forward Selection Labolo, Abdul Yunus; Utiarahman, Siti Andini; Lasulika, Mohamad Efendi; Drajana, Ivo Colanus Rally; Bode, Andi
International Journal Software Engineering and Computer Science (IJSECS) Vol. 3 No. 3 (2023): DECEMBER 2023
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v3i3.1709

Abstract

This study addresses chili price volatility, an important concern that impacts the national economy and societal welfare. Fluctuations in chili prices in the retail market greatly influence market demand, thereby influencing farming decisions, especially chili cultivation. To help make better decisions, Researchers use forecasting, which is defined as the projection of future trends based on the analysis of historical data, using statistical methods. The K-Nearest Neighbor (K-NN) algorithm is used because of its resistance to high noise on large training datasets. However, challenges arise in determining the optimal value of 'k' and selecting related attributes. To overcome this, Feature Selection is applied to refine the model by removing irrelevant features, resulting in a significant reduction in the model error rate. This improvement indicates an increase in the efficiency of the K-NN algorithm with the incorporation of Feature Selection. Our findings show that the model, with backward elimination in Feature Selection, achieves a Root Mean Square Error (RMSE) of 0.202, outperforming the model using forward selection. The prediction accuracy of this model reaches an average of 78.86%, which is much higher than the baseline data of 50%. This shows the success of the proposed method in predicting chili prices.
Analisis Perbandingan Metode Teorema Bayes dan Certainty Factor Pada Diagnosis Gangguan Kecemasan Gobel, Citra Yustitya; Lasena, Marlin; Puspa, Misrawati Aprilyana; Utiarahman, Siti Andini
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7683

Abstract

Anxiety disorders are a mental health problem that is increasing in prevalence, but the lack of public knowledge about anxiety disorders means that many people are not aware of anxiety disorders, so information technology is needed to understand symptoms and diagnosis using more relevant methods in intelligent systems. Intelligent systems are able to help in analyzing various symptoms and identifying initial diagnosis results with wider accessibility, but the problem of this research is focused on selecting the most effective method for intelligent systems as a basis for clinical data analysis, so in this research we will compare the level of accuracy of applying the method, namely Bayes' theorem and Certanty factor for the diagnosis of anxiety disorders. Bayes' Theorem is a classic statistical approach, offering a structured and measurable framework for calculating the probability of disease based on clinical evidence, while the Certainty Factor is a method for proving the certainty value of a fact in the form of a metric in an intelligent system. The aim of this research is to analyze the performance of the Bayes Theorem method and certainty factor by examining the percentage results obtained by applying the two methods. that the percentage result of the Bayes Theorem calculation method is higher, namely 84%, compared to the percentage result of the certainty factor, namely 70%, so it can be concluded that the application of Bayes' theorem is better than the certainty factor, especially in the diagnosis of people with anxiety disorders.
Analisis Perbandingan KNN, SVM, Decision Tree dan Regresi Logistik Untuk Klasifikasi Obesitas Multi Kelas Utiarahman, Siti Andini; A. Mulawati M. Pratama
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1871

Abstract

Obesity has become a concerning global health issue, with continuously increasing prevalence. Early identification and accurate classification of obesity are crucial for implementing appropriate prevention and treatment strategies. This study aims to analyze and compare the performance of four popular classification algorithms: K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Tree, and Logistic Regression, in performing multi-class obesity classification based on Body Mass Index (BMI)  according to World Health Organization (WHO) standards. Using a dataset reflecting population diversity, this research evaluates the ability of each algorithm to classify obesity into several categories, such as normal, overweight, obesity grade 1, obesity grade 2, and obesity grade 3. The study utilizes 2.111 records with 17 attributes. Results indicate that the Decision Tree Algorithm outperforms other algorithms, achieving an accuracy of 99.3%, precision of 0.97-1.00, recall of 0.98-1.00, and f1-score of 0.98-1.00. KNN follows with an accuracy of 99.0%, precision of 0.98-1.00, recall of 0.98-1.00 and f1-score of 0.98-1.00. meanwhile, the Logistic Regression algorithm achieves an accuracy of 98%, precision of 0.95-1.00, recall of 0.95-1.00, and f1-score of 0.95-1.00. SVM demontrates slightly lower performance, although still showing overall good results with an accuracy of 96.6%, precision of 0.90-0.99, recall of 0.94-1.00, and f1-score of 0.93-0.99..
Penerapan Support Vector Machine dan Random Forest Classifier Untuk Klasifikasi Tingkat Obesitas Utiarahman, Siti Andini; Pratama, Andi Mulawati Mas
JURNAL FASILKOM Vol. 14 No. 3 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i3.8104

Abstract

Obesitas telah menjadi masalah kesehatan global yang semakin mengkhawatirkan, dengan 2.5 miliar penduduk dewasa mengalami kelebihan berat badan dan 890 juta teridentifikasi obesitas pada tahun 2022. Penelitian ini bertujuan untuk mengembangkan dan membandingkan model klasifikasi tingkat obesitas menggunakan algoritma Support Vector Machine (SVM) dan Random Forest, serta menganalisis faktor-faktor yang mempengaruhi obesitas. Data yang digunakan berasal dari dataset publik yang terdiri dari 1610 records dengan 15 variabel yang mencakup karakteristik demografis, faktor keluarga, pola makan dan gaya hidup. Metodologi penelitian meliputi tahap pra-pemrosesan data, pembagian dataset dengan rasio 70:30 untuk data training dan testing, serta evaluasi performa menggunakan metrik evaluasi, presisi, recall dan f1-score. Hasil penelitian menunjukkan bahwa Random Forest menghasilkan performa yang lebih unggul dengan akurasi 94%, meningkat 3% dari SVM yang mencapai akurasi 91.01%. Random Forest menunjukkan konsistensi yang lebih baik dalam klasifikasi seluruh kelas, khususnya mencapai hasil optimal untuk kelas 4 dengan presisi 100% dan recall 99%. Analisis faktor menunjukkan bahwa gaya hidup dan pola makan memiliki pengaruh signifikan terhadap tingkat obesitas. Model yang dikembangkan dapat diimplementasikan sebagai alat bantu dalam sistem kesehatan untuk memprediksi dan mengklasifikasikan tingkat obesitas secara akurat, memungkinkan intervensi yang lebih tepat sasaran berdasarkan faktor resiko yang terindentifikasi
Co-Authors A. Mulawati M. Pratama Adam, Novita Alang Alang Alang, Alang Ali, Satriadi D Andi Bode Andi Mulawati Mas Pratama Citra Yustitya Gobel Dalai, Hastuti R Drajana, Ivo Colanus Rally Farid Hastuti Dalai Ishak Fardiansyah Mohamad Jorry Karim Labolo, Abdul Yunus Marlin Lasena Maryati Kadir Thalib Mas Pratama, A. Mulawati Misrawati Aprilyana Puspa Moh. Fachrinanda Putra Bowta Mohamad Efendi Lasulika Mokodompit, Rian Anugrawan Muh. Fitra Yusuf Nur Oktavin Idris Nurjana Suleman Olha Musa Pratama, Andi Mulawati Mas Rapika Anwar Satriadi D. Ali Satriadi D. Ali Sri Oktavia Dai Suleman, Fitriyanti Suleman, Nurjana Sulistiawati Rahayu Ahmad Utiarahman, Isra Mirna Yundari, Yundari Yusrianto Malago Zufrianto K Dunggio