Judul: Evaluasi proses perhitungan Indeks Pembangunan Manusia: studi kasus di Jadebotabek
Abstrak: The preparation of an index intended to obtain quantitative data on performance or characteristic of a situation. Indexing should pay attention to the characteristics that must be owned by an index. Human development as the overall development of performance measures established by the three basic dimensions of a long and healthy life, knowledge, and a decent life which each dimension is represented by the indicators. Human Development Index (HDI) is a series of three dimensions. Evaluation of the Human Development Index figures calculated using principal component analysis and this evaluation is expected to further improve the accuracy of the results of the Human Development Index. The results of the evaluation was done in the calculation of the Human Development Index that has been done by the United Nations concluded that the calculations made so far have been relevant in accordance with the principles of statistics.
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Judul: Pengelompokan Data Indeks Pembangunan Manusia di Pulau Jawa dengan Algoritme ST-DBSCAN dan Bahasa Pemrograman Python
Abstrak: Human Development Index (HDI) is an indicator commonly used by the United Nations Development Programme (UNDP) to assess the success of development. Three elements forming the HDI value are the level of health, education, and economics. The HDI data per district used in this research only cover Java region in 2012, obtained from the Central Bureau of Statistics including spatial data (area coordinates), temporal data (years), and non-spatial data (HDI). Data mining technique applied in this research is clustering with ST-DBSCAN using Python programming language. Clustering can be used to found similar grouping based on HDI in each region. Visualization of HDI data objects produces a map of the cluster spread. By using spatial distance parameter (Eps1)=0.4, temporal distance (Eps2)=0, size of the tolerated difference in value of non-spatial atributes (Δ)=2, and minimum number of members in each cluster (MinPts)=5 resulted in 4 clusters and 18 point of noise with silhouette coefficient worth 0.020.
Keyword: Bogor Agricultural University (IPB), ST-DBSCAN, Python, human development index, clustering

Judul: Sintesis 1-Kloro-2-metoksi-6-propilnaftalena-1,3-dioksolana (1:1) sebagai Prekursor Asam (S)-(+)-(6-Metoksi-2-naftil)propanoat
Abstrak: Senyawa 1-kloro-2-metoksi-6-propilnaftalena-1,3-dioksolana (1:1) sebagai prekursor asam (S)-(+)-(6-metoksi-2-naftil)propanoat disintesis dari bahan awal 2-metoksinaftalena. Tahapan sintesis diawali dengan klorinasi menggunakan 2 jenis pereaksi klorinasi, yakni isosianurat terklorinasi dan NaOCl. Klorinasi dengan isosianurat terklorinasi berhasil menyintesis 1-kloro-2-metoksinaftalena sebagai produk monoklorinasi melalui pencirian dengan kromatograf gas-spektrometer massa (GC-MS). Nisbah konversi produk paling efisien diperoleh pada laju penambahan 2.5 mmol/jam. Sebaliknya, klorinasi dengan NaOCl menghasilkan produk triklorinasi. 1-Kloro-2-metoksinaftalena selanjutnya diasilasi dengan propanoil klorida, tetapi analisis dengan GC menunjukkan bahwa produk asilasi tidak terbentuk. Sistem bebas-air diperlukan untuk keberhasilan proses asilasi tersebut.
Keyword: isosianurat terklorinasi, NaOCl, nisbah konversi