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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Foristek SemanTIK : Teknik Informasi Just TI (Jurnal Sains Terapan Teknologi Informasi) Jurnal Pengabdian Masyarakat Ilmu Terapan (JPMIT) JPNM : Jurnal Pustaka Nusantara Multidisiplin AnoaTIK: Jurnal Teknologi Informasi dan Komputer ANIMATOR
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Optimalisasi Rute Pengangkutan Sampah Dengan Konsep Reduce-Reuce-Recycle (3R) Berbasis Webgis Menggunakan Algoritma Hill Climbing (Studi Kasus: TPS 3R Kambu, Perumahan Dosen UHO) Wahyu Nahda Putra; Jumadil Nangi; Natalis Ransi
JPNM Jurnal Pustaka Nusantara Multidisiplin Vol. 3 No. 4 (2025): December : Jurnal Pustaka Nusantara Multidisiplin (ACCEPTED)
Publisher : SM Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59945/jpnm.v3i4.801

Abstract

Permasalahan pengelolaan sampah yang terus meningkat di wilayah perkotaan menuntut adanya sistem yang mampu mengoptimalkan proses pengangkutan secara efisien. Penelitian ini bertujuan untuk mengembangkan sistem WebGIS optimalisasi rute pengangkutan sampah berbasis konsep Reduce, Reuse, Recycle (3R) dengan menerapkan algoritma Hill Climbing. Algoritma ini digunakan untuk menentukan rute terpendek dan paling efisien bagi petugas pengangkut sampah di wilayah TPS 3R Kambu, Perumahan Dosen Universitas Halu Oleo, dengan memanfaatkan data spasial dari OpenStreetMap. Proses optimasi dilakukan melalui iterasi hingga diperoleh rute dengan jarak minimal berdasarkan nilai evaluasi jarak antar titik. Hasil pengujian User Acceptance Test (UAT) menunjukkan bahwa sistem memperoleh tingkat kelayakan sebesar 88.07% dari kelompok admin/petugas dan 79.74% dari pengguna layanan, keduanya termasuk kategori Baik. Hal ini menunjukkan bahwa sistem mudah digunakan, stabil, serta mampu memenuhi kebutuhan pengelolaan sampah di lapangan. Sementara itu, hasil pengujian akurasi algoritma menunjukkan perbedaan jarak sebesar 40 meter atau sekitar 4,4% antara hasil perhitungan sistem (860 meter) dan data manual Google Maps (900 meter). Selisih ini disebabkan penggunaan jarak Euclidean pada sistem, namun hasilnya tetap mendekati kondisi nyata. Secara keseluruhan, sistem WebGIS berbasis algoritma Hill Climbing dinilai layak dan akurat dalam menentukan rute optimal pengangkutan sampah. Sistem ini terbukti dapat meningkatkan efisiensi operasional TPS 3R dan mendukung implementasi pengelolaan sampah berbasis 3R. Penelitian ini berpotensi dikembangkan lebih lanjut melalui integrasi data real-time, prediksi volume sampah, serta kombinasi dengan algoritma heuristik lain guna meningkatkan akurasi dan performa sistem.
ANALISIS SENTIMEN APLIKASI PEMINJAMAN ONLINE BERDASARKAN ULASAN PADA PLAY STORE MENGGUNAKAN METODE NAÏVE BAYES DAN SUPPORT VECTOR MACHINE (STUDI KASUS : ADAKAMI DAN EASYCASH) La Ode Muhammad Hafidz Abdillah Sam Mongkito; Natalis Ransi; La Surimi; Andi Tenriawaru; Gunawan Gunawan; Budi Wijaya Rauf
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.71

Abstract

This research aims to analyze the sentiment of online lending applications based on reviews on the Google Play Store using the Naïve Bayes and Support Vector Machine methods and determine which online lending applications are more trustworthy. AdaKami is an online lending application under the auspices of PT Pemfinaan Digital Indonesia. EasyCash is an online lending application which is a financial technology company owned by PT. Indonesia Fintopia Technology which provides a digital financial service portal, especially online lending. However, to determine whether this online lending application is reliable or trustworthy, it requires a collection of information that comes from previous user experience. The Naïve Bayes and Support Vector Machine methods are used to analyze loan application sentiment based on relevant review data which is processed using the Python programming language with Google Colabs as a tool for carrying out the research stage. The research results show that the Naïve Bayes and Support Vector Machine methods can be applied in analyzing the sentiment of online lending applications and based on the results of application analysis using the Naïve Bayes Adakami method, it is more trusted by previous users because it produces 95% positive review data and the Easycash application produces positive review data of 95%. 93% and the results using the Adakami Support Vector Machine method produced positive review data of 91% and the Easycash application produced positive review data of 83%.review data while the Easycash application produces 93% positive review data.
ANALISIS PENGGUNAAN APLIKASI E-VOTING PEMIRA UNIVERSITAS HALU OLEO: PERLUASAN TECNOLOGY ACCEPTANCE MODEL DENGAN TRUST IN INTERNET SEBAGAI VARIABEL MODERATOR Fazlul Rachmat Mubbaraq; Natalis Ransi; Ferdinand Murni Hamundu
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 2 No 2 (2024): Desember 2024
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v2i2.72

Abstract

This study aims to conduct an in-depth analysis of the level of acceptance of the e-voting application in the Halu Oleo University PEMIRA using TAM. This research is a quantitative research, using the SPSS application.The Technology Acceptance Model (TAM) is a framework that can be used to understand user behavior towards technology. TAM is a model that explains how technology users accept and use it. According to this theory, a person's behavior model is influenced by behavioral goals. The attitude towards the behavior determines the purpose of the behavior. In this context, the variables used are perceived usefulness and perceived ease of use, Attitude Toward Using, Behavioural Intension to Use Actual Use and Trust In Internet.  Of the 6 variables, there are 8 hypotheses and of  these 8 hypotheses 7 hypotheses are accepted and the rest are rejected. Based on the results of the analysis, trust in the internet is able to moderate the relationship between perceived usefulness and behavior to use, the contribution of the influence of the PU variable on the BITU variable after the moderation variable is 97.3%.
KLASIFIKASI STATUS GIZI BAYI MENGGUNAKAN METODE K-NEAREST NEIGHBOR Sri Ayu Lestari; Natalis Ransi; Muhammad Arfan
AnoaTIK: Jurnal Teknologi Informasi dan Komputer Vol 3 No 2 (2025): Desember 2025
Publisher : Program Studi Ilmu Komputer FMIPA-UHO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33772/anoatik.v3i2.117

Abstract

The development of a baby nutritional status classification system was carried out by applying the K-Nearest Neighbor (KNN) method with the aim of supporting more accurate monitoring of infant growth and development. The system determines the nutritional status of infants based on input data including age, weight, height, and mid-upper arm circumference, which are then compared with available training data. The system development process employed the waterfall approach, encompassing requirements analysis, system design, implementation, and testing stages. Testing was conducted using black box testing to ensure that all system functions operated according to requirements, as well as a confusion matrix to measure classification accuracy. The results showed that all system features functioned properly and the achieved accuracy rate reached 97.30%, indicating that the system has very good performance in effectively supporting the monitoring of infant nutritional status.
Co-Authors Ahmad Faldhi Yudianto Ambo Wonua Nusantara Andi Tenriawaru Arman Arman Bambang Pramono Budi Wijaya Rauf Dessy Santi Dian Safitri Duruka Edi Cahyono Edi Cahyono Edi Winarko Elvi Saktiawati Salemaku Fazlul Rachmat Mubbaraq Gunawan Gunawan Ihsan Sarita Jufra Jufra Jumadil Nangi L.M Fid Aksara La Ode Muhammad Hafidz Abdillah Sam Mongkito La Ode Saidi La Surimi Muhammad Alfian Izzah Muhammad Arfan Muhammad Ihsan Sarita Muhammad Yamin paditya septiansa Rosliana Eso Sri Ayu Lestari Statiswaty Wahyu Nahda Putra Waode Hardianas Shalawati Waode Nur Lailah